TinyFn
Server Details
500+ deterministic tools for AI agents: math, conversion, validation, hashing, encoding, date/time.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 3.2/5 across 513 of 572 tools scored. Lowest: 1.9/5.
Many tools have overlapping purposes, such as multiple random generators (random_integer, random_number), duplicate hashing functions (hash_md5, md5_checksum), and near-identical tools (compare, compare_2, compare_decimals). The sheer number of tools and lack of clear boundaries make it difficult for an agent to differentiate.
Naming is highly inconsistent. There are duplicate tools with different names (camel_case vs to_camel_case, slug vs slugify), arbitrary suffixes like '_2', and mixing of patterns (e.g., generate_password vs password_entropy). No clear convention is followed.
With 572 tools, the server is massively overpopulated for any coherent purpose. It includes trivial endpoints (true_endpoint, null, hello_world) and numerous duplicates, far exceeding a well-scoped utility set.
While the server covers many domains (math, strings, dates, colors, etc.), the presence of duplicate and trivial tools indicates a lack of thoughtful curation. There are gaps in basic operations (e.g., no dedicated file or network tools), and many tools are redundant.
Available Tools
572 toolsabsolute_valueAInspect
Get the absolute value of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| absolute_value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It accurately describes the operation as non-destructive and straightforward, but does not disclose any additional behavioral traits beyond the basic math function. Output schema exists, so return format is covered elsewhere.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. It is appropriately sized and front-loaded, conveying the essential purpose without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, no nested objects, output schema exists), the description is complete enough for an agent to understand and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'number', with a description 'The number'. The tool description adds no extra meaning beyond what the schema already provides, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Get' and the resource 'absolute value of a number'. It is specific and distinguishes this tool from sibling math operations like 'add', 'subtract', etc., as it is the only one dedicated to absolute value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. For a simple mathematical function, context may be less critical, but the description does not provide any hints on prerequisites or conditions for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
acres_to_hectaresBInspect
Convert acres to hectares.
| Name | Required | Description | Default |
|---|---|---|---|
| acres | Yes | Area in acres |
Output Schema
| Name | Required | Description |
|---|---|---|
| acres | Yes | |
| hectares | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavior. It only states the conversion, without mentioning edge cases (e.g., negative values), precision, or return type. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. Very concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is adequate. However, it lacks context on error handling or precision, which could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; the parameter is described as 'Area in acres' in the schema. The tool description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert acres to hectares' uses a specific verb and resource, clearly indicating the conversion. It distinguishes itself from sibling conversion tools like celsius_to_fahrenheit, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives or any prerequisites. The description does not mention exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
addAInspect
Add two or more numbers together.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers to add |
Output Schema
| Name | Required | Description |
|---|---|---|
| sum | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly states the operation (addition) and accepted input format (comma-separated numbers). It does not disclose handling of overflow, non-numeric input, or floating-point precision, but for a simple arithmetic tool these are generally understood.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. The description is front-loaded with the action and resource, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple addition tool, the description covers the core functionality. The output schema (not shown) can detail return type. However, it does not mention error handling (e.g., invalid numbers) or limits, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds the constraint 'two or more numbers', which is not explicit in the schema (which only states 'Comma-separated numbers'). This provides additional context beyond the schema's description. Schema coverage is 100%, but the tool description still adds value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Add' and the resource 'numbers', with the specific constraint 'two or more', which distinguishes it from other addition-related tools like 'sum_numbers' (which might handle arrays). It is a specific verb+resource combination.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus siblings like 'sum_numbers', 'add_time', or 'add_business_days'. The description implies usage for basic arithmetic addition, but does not provide exclusions or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_business_daysBInspect
Add business days to a date.
| Name | Required | Description | Default |
|---|---|---|---|
| days | Yes | Business days to add | |
| start_date | Yes | Start date (YYYY-MM-DD) |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| result_day | No | |
| start_date | No | |
| result_date | No | |
| business_days_added | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It fails to explain what constitutes a business day (e.g., weekends, holidays), how edge cases like start dates falling on weekends are handled, or any limitations. The user gains no insight into the tool's internal logic.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is front-loaded and immediately conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters and an output schema, but the description lacks essential behavioral context (e.g., business day definition). It is minimally adequate but leaves significant gaps for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the schema adequately documents the parameters. The description adds no new semantic meaning beyond 'add business days', which is already implied. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Add') and resource ('business days to a date'). It is specific and unambiguous, distinguishing it from sibling tools like 'business_days' (likely for calculating difference) and 'add_time' (general time addition).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives (e.g., 'add_time' for non-business days). There is no mention of prerequisites, expected inputs, or scenarios where this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_query_paramCInspect
Add a query parameter to a URL.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Parameter key | |
| url | Yes | URL to modify | |
| value | Yes | Parameter value |
Output Schema
| Name | Required | Description |
|---|---|---|
| modified | Yes | |
| original | Yes | |
| added_param | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose key behaviors such as what happens if the parameter already exists (overwrite, duplicate, error), or that it returns the modified URL. The agent is left guessing about side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence, immediate and clear. While it could include more detail, it is concise and front-loaded, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three required parameters and no annotations, the description is too brief. It omits expected details like return value (though output schema exists) and behavior on duplicate keys, leaving the agent with uncertainty about the tool's exact effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter schema coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema's short descriptions (e.g., 'Parameter key', 'URL to modify'), but does not detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'add' and the resource 'query parameter to a URL', making the tool's purpose obvious. However, it does not distinguish from sibling tools like 'remove_query_param' or 'build_url', which manipulate URLs similarly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'build_url' or 'remove_query_param'. The description is too minimal to help an agent choose between similar URL manipulation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_timeCInspect
Add time to a date.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Start date (ISO format) | |
| days | No | Days to add | |
| hours | No | Hours to add | |
| weeks | No | Weeks to add | |
| minutes | No | Minutes to add | |
| seconds | No | Seconds to add |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| added | No | |
| error | No | |
| result | No | |
| original | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only says 'Add time to a date.', omitting details such as return format, handling of negative values, whether it modifies input, or any limitations. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) but at the cost of omitted critical information. It is underspecified for a tool with 6 parameters and date arithmetic functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description is completely inadequate. It fails to explain return value, edge cases, or the combined effect of multiple time units. A more detailed description is necessary for effective tool use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides for parameters like date, days, hours, etc. No examples or composite behavior explained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add time to a date.' clearly states the action and resource, but it is vague and does not differentiate from similar tools like add_time_2 or add_business_days. It lacks specificity about the scope or distinct behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, nor does it mention any prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_time_2CInspect
Add time to a datetime.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Days to add | |
| hours | No | Hours to add | |
| minutes | No | Minutes to add | |
| seconds | No | Seconds to add | |
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| added | No | |
| error | No | |
| result | No | |
| original | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the core function, omitting details such as whether the input is modified, what the output format is, or how errors are handled.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and front-loaded. However, it may be too brief for a tool with multiple parameters and no annotation support.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and full parameter descriptions, the single-sentence description is minimally adequate. It does not elaborate on return values or usage examples, but the schema fills some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter description coverage, so the schema already explains the parameters. The description adds no additional meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Add time to a datetime' clearly states the verb and resource. However, it does not differentiate from the sibling tool 'add_time', which likely performs a similar function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'add_time', 'subtract_time', or 'subtract_time_2'. This lack of context makes it harder for the agent to choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
adler32_checksumCInspect
Calculate Adler-32 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to checksum |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| adler32 | Yes | |
| adler32_int | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is minimal and does not disclose any behavioral traits beyond the name. Annotations are absent, so the description carries full burden, yet it omits details like output format, determinism, or performance characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is appropriately sized for a simple tool. It is front-loaded and contains no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of many sibling tools performing similar checksums, the description lacks completeness. It does not explain the output format, usage context, or how it differs from hash_adler32.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter 'text' already described as 'Text to checksum'. The description adds no additional meaning beyond the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate Adler-32 checksum', specifying the exact algorithm. It distinguishes from other hash tools like crc32 or md5 by name, though the presence of hash_adler32 as a sibling causes potential confusion not resolved by the description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus other checksum or hash tools (e.g., crc32_checksum, hash_adler32). No context about appropriate use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
analogous_colorsBInspect
Get analogous colors (adjacent colors on color wheel).
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color to get analogous colors for |
Output Schema
| Name | Required | Description |
|---|---|---|
| triadic | No | |
| original | Yes | |
| tetradic | No | |
| analogous | No | |
| split_complementary | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states what it does, not how many colors it returns or any other behavioral traits. The agent cannot infer details about the output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence that front-loads the purpose with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Has an output schema, so return values are covered elsewhere. However, for a color tool, the description is minimal and does not explain the number of colors or angle. Adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, which is already well-described in the schema. The description adds no extra meaning beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'analogous colors (adjacent colors on color wheel)', which is specific and distinguishes it from sibling tools like complement_color and triadic_colors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like triadic_colors or tetradic_colors. The description provides no usage context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
analyze_passwordCInspect
Analyze password strength and characteristics.
| Name | Required | Description | Default |
|---|---|---|---|
| password | Yes | Password to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| score | Yes | |
| issues | Yes | |
| length | Yes | |
| strength | Yes | |
| entropy_bits | Yes | |
| characteristics | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states 'analyze password strength and characteristics' without disclosing specific behavioral traits like return format, scoring mechanism, or whether it checks common passwords.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise at one sentence, but lacks substantive information. Could be more structured to include key details without increasing length significantly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description is minimal. For a tool with multiple potential characteristics, it provides incomplete guidance on what analysis is performed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter 'password' described as 'Password to analyze'. The description adds no additional meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool analyzes password strength and characteristics, with a specific verb and resource. It distinguishes from siblings like 'validate_password_strength' by implying broader analysis, though it's somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'password_entropy' or 'generate_password'. The description does not provide context for selection among many password-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_compactAInspect
Remove falsy values (empty strings) from array.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| removed | Yes | |
| original | Yes | |
| compacted | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the core behavior (removing empty strings) but fails to mention that the input is a comma-separated string (only inferred from schema) and does not clarify handling of whitespace or other potential falsy values. With no annotations, the description carries the burden but is marginally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (6 words) and front-loads the key action and criteria. However, it uses 'array' rather than 'comma-separated string', which could cause minor confusion. Every word earns its place, though slightly more detail would improve clarity without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and full schema coverage. The description, combined with the schema, provides enough context for an agent to invoke the tool correctly. The return value is not explained, but the presence of an output schema mitigates this. It could be enhanced by explicitly stating the input format and output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes the 'items' parameter as 'Comma-separated items', but the description adds the crucial transformation logic: that falsy values (empty strings) are removed. This adds significant meaning beyond the schema, especially given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Remove') and target ('falsy values (empty strings)') from an array. It distinguishes itself from siblings like array_dedupe or array_fill by specifying the exact transformation, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., array_fill, array_reverse). There is no mention of prerequisites, limitations, or when not to use it. Given the large sibling list, explicit would help agent selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_dedupeCInspect
Remove duplicates from array.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items | |
| preserve_order | No | Preserve original order |
Output Schema
| Name | Required | Description |
|---|---|---|
| deduped | Yes | |
| original | Yes | |
| duplicates_removed | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks behavioral disclosure beyond the basic function. It does not mention that order is preserved by default (only implied by the schema's preserve_order parameter), nor does it describe return value format or performance characteristics. With no annotations, the description should compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence. While it is efficient, it could provide slightly more context (e.g., input format) without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description is minimally adequate. However, it does not explain the output format or edge cases like empty input.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description adds no additional meaning. The tool description does not elaborate on the parameters, but the schema already documents them adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool removes duplicates from an array, with a specific verb and resource. It is distinguishable from sibling tools like array_compact or array_union, though it does not specify the input format (comma-separated string) which is only in the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools like array_compact (remove falsy values) or array_union (merge and dedupe) have different purposes, but no comparison is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_differenceAInspect
Get difference of two arrays (items in array1 not in array2).
| Name | Required | Description | Default |
|---|---|---|---|
| array1 | Yes | First comma-separated array | |
| array2 | Yes | Second comma-separated array |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| union | No | |
| array1 | Yes | |
| array2 | Yes | |
| difference | No | |
| intersection | No | |
| symmetric_difference | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It states it returns items from array1 not in array2, implying a read-only computation. However, it does not disclose ordering, duplicate handling, or performance characteristics, which are typical for array operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and contains no unnecessary words. Every part contributes to understanding the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple set difference tool with two string parameters, the description is largely complete. An output schema exists, so return values are not needed. Minor omission: does not specify if order or duplicates are preserved, but these are often intuitive for this operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both parameters described as 'comma-separated array' and 'First'/'Second'. The description adds no additional meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Get difference' and resource 'of two arrays', clearly defining it as set difference. It distinguishes from sibling tools like array_intersection (common items) and array_union (all items) by specifying 'items in array1 not in array2'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for set difference but does not explicitly state when to use this tool versus alternatives like array_intersection or array_union. No explicit exclusions or context are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_fillCInspect
Create an array filled with a value.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Value to fill | |
| length | Yes | Array length |
Output Schema
| Name | Required | Description |
|---|---|---|
| array | Yes | |
| value | Yes | |
| length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the action without mentioning any behavioral traits such as idempotency, side effects, or constraints beyond the schema. For a pure function-like tool, more transparency (e.g., that it creates a new array) would be helpful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is concise and front-loaded. While extremely short, it earns its place by being to the point, though it could benefit from a brief example or condition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (two scalar params, no nested objects), the description is minimally complete. An output schema exists to clarify return values, but for a tool with many siblings, additional context (e.g., that the value is repeated, not cloned) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description does not add any meaning beyond what the schema already provides ('Value to fill', 'Array length'). It is adequate but does not enhance understanding of the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Create an array filled with a value' clearly states the tool's function: it creates an array by repeating a single value. It is specific and uses a verb+resource structure. However, it does not differentiate from similar sibling tools like array_repeat, which may create similar arrays.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Given the large number of array-related sibling tools (e.g., array_repeat, array_dedupe), the absence of usage context is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_firstAInspect
Get first n items from array.
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | Number of items to get | |
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | |
| last | No | |
| array | Yes | |
| first | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It states the basic function but lacks detail on edge cases (e.g., n larger than array length) or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity and presence of output schema, description is nearly sufficient. Lacks edge-case guidance, but sufficient for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters fully (100%). Description adds minimal value beyond rephrasing schema descriptions; does not clarify the comma-separated format or default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get first n items from array' with specific verb and resource, distinguishing it from siblings like array_last and array_slice.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use versus alternatives like array_slice or array_last. Usage is implied but not compared.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_frequencyBInspect
Count frequency of each item.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| array | Yes | |
| frequency | Yes | |
| most_common | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does not disclose behavior like output format (likely an object), handling of empty input, or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool and the existence of an output schema, the description is minimally complete but could benefit from mentioning the output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no additional meaning beyond the parameter details in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Count frequency of each item' clearly communicates the verb (count) and resource (frequency of each item), distinguishing it from sibling tools like array_compact or count_items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as count_items or contains. The description does not mention context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_interleaveCInspect
Interleave two arrays.
| Name | Required | Description | Default |
|---|---|---|---|
| array1 | Yes | First comma-separated array | |
| array2 | Yes | Second comma-separated array |
Output Schema
| Name | Required | Description |
|---|---|---|
| array1 | Yes | |
| array2 | Yes | |
| interleaved | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It does not explain how interleaving works (e.g., handling of uneven arrays, order preservation, output format) beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence. While it is efficient, it may be too minimal, but it avoids unnecessary verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and simple parameters, the description is adequate but could be more complete by explaining behavior for edge cases or differentiating from similar sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with clear descriptions for each parameter (comma-separated arrays). The tool description adds no additional meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'interleave' and the resource 'two arrays'. It distinguishes the tool from siblings by specifying a unique operation, but it does not explicitly differentiate from similar tools like array_zip.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like array_zip, array_union, etc. There is no mention of prerequisites or context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_intersectionCInspect
Get intersection of two arrays.
| Name | Required | Description | Default |
|---|---|---|---|
| array1 | Yes | First comma-separated array | |
| array2 | Yes | Second comma-separated array |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| union | No | |
| array1 | Yes | |
| array2 | Yes | |
| difference | No | |
| intersection | No | |
| symmetric_difference | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It does not mention whether order is preserved, how duplicates are handled, or any side effects. The description is too minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence. It is front-loaded and to the point, but could be expanded with behavioral details without becoming overly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description does not need to explain return values. However, it lacks details on duplicate handling and input format validation, making it adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already defines both parameters as comma-separated arrays. The description adds no further semantic meaning, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action and resource: 'Get intersection of two arrays.' It is specific but does not differentiate from sibling tools like array_union or array_difference, which are also array operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., array_difference, array_union). The description only states what it does without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_lastAInspect
Get last n items from array.
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | Number of items to get | |
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | |
| last | No | |
| array | Yes | |
| first | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. It only states the basic operation without details on error handling, return format, or behavior when n exceeds array length.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with no unnecessary words; front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with clear schema and output schema present, the description is sufficient but could mention behavior for edge cases like n > array length.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover both parameters (n: 'Number of items to get', items: 'Comma-separated items') with 100% coverage; description adds no additional semantic value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action ('get') and resource ('last n items from array'), distinguishing it from sibling tools like 'array_first' and 'array_slice'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives; usage is implied by the name and description but not directly stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_nthBInspect
Get item at specific index.
| Name | Required | Description | Default |
|---|---|---|---|
| index | Yes | Index (0-based, negative for from end) | |
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| item | No | |
| array | Yes | |
| error | No | |
| index | Yes | |
| valid_range | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No behavioral traits beyond the basic operation are disclosed. The description does not explain what happens with out-of-bounds indices, empty strings, or malformed input. Without annotations, this is a significant gap for a read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) and front-loaded. While efficient, it omits useful behavioral clues, slightly reducing its value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and full schema coverage, the description is minimally adequate. However, it lacks completeness regarding edge cases (bounds, empty input) which an agent might need, especially since no output schema details are visible.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters are documented. However, the description adds no extra meaning beyond what the schema provides (e.g., 'index' is 0-based, negative for from end). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get item at specific index' clearly states the action (get) and the resource (item at index), distinguishing it from siblings like array_first (first element) and array_last (last element). It is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as array_first or array_last. It does not mention scenarios or exclusions, leaving the agent to infer its applicability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_partitionCInspect
Partition array into chunks of specified size.
| Name | Required | Description | Default |
|---|---|---|---|
| size | Yes | Partition size | |
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| size | Yes | |
| original | Yes | |
| partitions | Yes | |
| num_partitions | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only states 'partition array into chunks' without specifying that the input is a string, how chunks are formed, or whether order is preserved. Key details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with one sentence front-loading the core purpose. However, it could be improved by clarifying the input type (string vs array) without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple partition tool, the description is acceptable but lacks details like output format or behavior with edge cases. An output schema exists but its content is unknown; the description does not mention return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, describing 'items' as comma-separated and 'size' as partition size. The description adds no significant meaning beyond the schema, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (partition) and the resource (array into chunks). However, the input is a comma-separated string, not an array, which could cause confusion. The sibling tool 'chunk_array' likely performs a similar function, reducing differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over similar siblings like 'chunk_array'. There is no mention of the input format (comma-separated string) or how it differs from array operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_repeatCInspect
Repeat an array n times.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items | |
| times | Yes | Times to repeat |
Output Schema
| Name | Required | Description |
|---|---|---|
| times | Yes | |
| original | Yes | |
| repeated | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks disclosure of side effects, constraints (e.g., max times from schema), or output format. With no annotations, the description should provide more behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and front-loaded. However, it could include output details without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description doesn't explain the return format or behavior beyond repeating. The input type confusion (array vs string) and lack of detail on the result reduce completeness for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The tool description adds minimal value beyond 'Comma-separated items' and 'Times to repeat', meeting the baseline for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Repeat an array n times' clearly states the action and resource. However, there is a slight mismatch as the input is a comma-separated string, not an actual array type. It distinguishes from sibling 'repeat' which likely handles strings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'repeat' or other array operations. No context on prerequisites or scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_reverseCInspect
Reverse an array.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| reversed | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose behavioral traits (e.g., input format, output format). With no annotations, the description carries full burden and fails to add behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short (4 words), no wasted text, but borders on underspecification. Could be slightly improved.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with output schema present; description covers core operation but omits details on output format. Adequate for minimal tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already describes parameter as 'Comma-separated items' (100% coverage). Description adds no additional meaning, baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Reverse' and resource 'array'. Distinguishable from siblings like array_rotate, but lacks explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use versus alternatives like array_rotate or array_slice. Missing context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_rotateBInspect
Rotate an array by n positions.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items | |
| positions | Yes | Positions to rotate (positive=right, negative=left) |
Output Schema
| Name | Required | Description |
|---|---|---|
| rotated | Yes | |
| original | Yes | |
| positions | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral details such as handling of positions larger than array length, wrapping, and output format. It only states the operation without these details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is efficiently front-loaded with the essential verb and object. It earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with a clear schema and output schema, the description is minimally adequate. However, it omits expected behavior like wrapping and output format, making it less complete than ideal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and already explains the parameters ('comma-separated items', 'positive=right, negative=left'). The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'rotate' and resource 'array', and specifies the rotation amount. It distinguishes from sibling tools like array_reverse and array_slice. However, it doesn't clarify that the input is a comma-separated string, not a native array.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like array_reverse or other array operations. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_sliceCInspect
Slice an array.
| Name | Required | Description | Default |
|---|---|---|---|
| end | No | End index (exclusive) | |
| items | Yes | Comma-separated items | |
| start | No | Start index |
Output Schema
| Name | Required | Description |
|---|---|---|
| end | No | |
| start | Yes | |
| sliced | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the burden of behavioral disclosure. It does not mention that the tool likely returns a new array (non-destructive), how invalid indices are handled, or any edge cases. The description is insufficient for understanding the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (two words), which is not concise but rather underspecified. It does not front-load any useful information beyond what the name conveys, wasting the opportunity to add value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. However, it fails to explain concepts like exclusive end index or the comma-separated input format, which are only clear from the schema. It is not complete for an AI agent unfamiliar with the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all three parameters (items, start, end), so the schema already provides clear semantics. The description adds no additional meaning, which is acceptable given the schema coverage, but it does not compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Slice an array' which identifies the verb (slice) and resource (array), but it is extremely brief and does not differentiate from sibling array tools like array_partition or array_dedupe. The purpose is clear only because of the tool name, but the description adds little value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., array_fill, array_reverse). There are no examples or context for when slicing is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_symmetric_differenceBInspect
Get symmetric difference (items in either but not both).
| Name | Required | Description | Default |
|---|---|---|---|
| array1 | Yes | First comma-separated array | |
| array2 | Yes | Second comma-separated array |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| union | No | |
| array1 | Yes | |
| array2 | Yes | |
| difference | No | |
| intersection | No | |
| symmetric_difference | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the basic result of symmetric difference. It does not disclose how duplicates are handled, whether order is preserved, or any edge cases. The description is minimal and lacks behavioral depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core functionality. It is concise and front-loaded, but could potentially add a bit more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is minimally adequate. However, it lacks details on duplicate handling, result ordering, or expectations for input format (e.g., whitespace handling). It is somewhat complete but could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters described as 'First comma-separated array' and 'Second comma-separated array'. The description adds no extra meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the operation 'symmetric difference' and explains it as 'items in either but not both'. This is specific and distinguishes it from sibling tools like array_difference (items in first but not second) and array_intersection (items in both).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly provide guidance on when to use this tool versus alternatives like array_difference or array_union. The usage is implied by the mathematical definition, but no contextual clues or when-not-to-use are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_unionAInspect
Get union of two arrays.
| Name | Required | Description | Default |
|---|---|---|---|
| array1 | Yes | First comma-separated array | |
| array2 | Yes | Second comma-separated array |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| union | No | |
| array1 | Yes | |
| array2 | Yes | |
| difference | No | |
| intersection | No | |
| symmetric_difference | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavior. It implies a read operation combining elements, but does not specify duplicate handling, order preservation, or that result contains unique elements. Basic transparency but lacking detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with no redundancy. Front-loaded with the core action and resource. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and simple parameters, the description is minimally adequate. However, it lacks guidance on usage and behavior, which could be improved for better agent understanding among sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions ('First comma-separated array', 'Second comma-separated array'). The description adds minimal extra meaning beyond 'union' context. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get union of two arrays' clearly states the action (union) and the resource (two arrays). It directly conveys the set operation, distinguishing it from sibling array operations like intersection or difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., array_intersection, array_difference). The description does not mention context or prerequisites, leaving the agent without direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_unzipBInspect
Unzip array of pairs into two arrays.
| Name | Required | Description | Default |
|---|---|---|---|
| pairs | Yes | JSON array of pairs, e.g., [[1,2],[3,4]] |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| pairs | No | |
| array1 | No | |
| array2 | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the basic operation without covering error handling, input validation, or expected behavior for malformed inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single-sentence description is concise and front-loaded. For a simple tool, every word earns its place, though more context could be added without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, clear operation, and existing output schema), the description is nearly complete. It lacks usage context but suffices for basic invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'pairs' parameter with type and example, covering 100% of parameters. The description adds no extra meaning beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Unzip array of pairs into two arrays' uses a specific verb and resource, clearly defining the transformation. It distinguishes itself from sibling tools like array_zip, array_compact, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives or any prerequisites. It lacks context for context-aware selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
array_zipBInspect
Zip two arrays together.
| Name | Required | Description | Default |
|---|---|---|---|
| array1 | Yes | First comma-separated array | |
| array2 | Yes | Second comma-separated array |
Output Schema
| Name | Required | Description |
|---|---|---|
| array1 | Yes | |
| array2 | Yes | |
| zipped | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It does not disclose what happens if arrays have different lengths, the output format, or any side effects. The single sentence lacks behavioral depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no superfluous words. It is maximally concise for the information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple zip operation, the description captures the essence. However, it omits details like element-wise pairing and handling of unequal lengths. Since an output schema exists, return values are not required in the description, but behavioral completeness is still slightly lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both array1 and array2 have descriptions ('First comma-separated array', 'Second comma-separated array'). The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Zip two arrays together' clearly indicates the action (zip) and the resource (two arrays). It is a specific verb+resource combination. However, it does not explicitly distinguish itself from similar sibling tools like array_interleave, which might be considered a variant.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives such as array_interleave or array_union. There is no mention of prerequisites, typical use cases, or scenarios where different behavior is expected.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ascii_decodeBInspect
Convert ASCII codes to text.
| Name | Required | Description | Default |
|---|---|---|---|
| codes | Yes | Space-separated ASCII codes |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| codes | No | |
| error | No | |
| decoded | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not disclose any behavioral traits such as error handling for invalid codes, range of accepted codes, or the format of the output. With no additional context, the agent cannot infer important usage nuances.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with only a single sentence that clearly states the tool's purpose. No extraneous words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple input and likely a straightforward output (decoded text), but the description lacks details about handling invalid inputs, output format, or edge cases. With an output schema existing but not detailed, the description is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter described as 'Space-separated ASCII codes'. The description adds no further meaning beyond what the schema already states, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Convert' and clearly identifies the resource 'ASCII codes to text'. It distinguishes from the sibling tool 'ascii_encode' which performs the inverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'ascii_encode' or other decoding tools. The description provides no context for appropriate usage or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ascii_encodeAInspect
Get ASCII codes for text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to ASCII encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| ascii_codes | Yes | |
| ascii_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, but description indicates a read-only transformation. No hidden side effects. Transparent for a simple encode operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, clear, front-loaded. No wasted words. Efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-param tool with output schema, description covers purpose sufficiently. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. Description repeats parameter purpose ('Text to ASCII encode') but doesn't add substantial meaning beyond schema. Baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb ('Get') and resource ('ASCII codes for text'), with a specific operation. It distinguishes from sibling ascii_decode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives. Implied by description, but lacks guidance on context or exclusions. Simple tool reduces need, but still minimal.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
averageCInspect
Calculate the average of a list of numbers.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| min | Yes | |
| sum | Yes | |
| count | Yes | |
| average | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as error handling for non-numeric input, the type of average (presumably arithmetic), or the output format (if any). This is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it lacks necessary details that would improve usability without significantly increasing length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description omits output details and behavioral context. Given no output schema is shown, the description should compensate, but it does not.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the `numbers` parameter. The description adds minimal extra meaning beyond the schema, aligning with the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate the average of a list of numbers' clearly states the verb and resource. However, it does not differentiate from sibling tools like `calculate_mean`, `calculate_median`, etc., which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., mean vs median). The description lacks context for appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
base64_decodeBInspect
Decode base64 to text.
| Name | Required | Description | Default |
|---|---|---|---|
| encoded | Yes | Base64 string to decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| decoded | No | |
| encoded | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, so the description must disclose behavior. It does not mention error handling (e.g., invalid base64), encoding assumptions, or any side effects. The output schema is not described, leaving the agent uninformed about the result format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. However, it is perhaps too minimal, lacking useful context without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description is minimally adequate but fails to cover edge cases (e.g., invalid input) or the output structure. It is not fully complete given the existence of sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the parameter 'encoded' already described as 'Base64 string to decode'. The description adds no new semantic detail, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('decode'), the resource ('base64'), and the result ('text'). It is specific and easily distinguishable from siblings like base64_encode and other decode tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives (e.g., ascii_decode, hex_decode). There is no mention of prerequisites, context, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
base64_encodeAInspect
Encode text to base64. Properly handles Unicode.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| encoded | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'Properly handles Unicode', which is a key behavioral trait, but does not describe the output format or any edge cases. This adds some value but leaves gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. It efficiently communicates the tool's purpose and a key behavioral detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description covers the essential purpose and Unicode handling, leaving little ambiguity. It is sufficiently complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter 'text' described as 'Text to encode'. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'encode' and the resource 'text to base64', distinguishing it from the sibling 'base64_decode' and other encoding tools like 'hex_encode'. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when base64 encoding of text is needed, and notes Unicode handling, which guides usage. However, it does not explicitly mention when not to use it or suggest alternatives like other encoding methods, but the simplicity makes it adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
base_convertAInspect
Convert a number between different bases.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to convert | |
| to_base | Yes | Target base | |
| from_base | Yes | Source base |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| input | No | |
| result | No | |
| decimal | No | |
| to_base | No | |
| from_base | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It states the basic operation but does not disclose return format, error behavior, or any side effects. However, the operation is mathematically pure, so the minimal transparency is acceptable but not exemplary.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no redundant words. Every word contributes to understanding the tool's core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (3 simple params) and presence of an output schema, the description adequately covers the basic conversion. However, it lacks context about the string format of the number and the output, which could be inferred but is not explicit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are already well-documented. The description adds no additional meaning beyond the schema, which already explains what 'number', 'from_base', and 'to_base' are. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert a number between different bases' clearly states the tool's purpose with a specific verb and resource. It distinguishes itself from sibling tools like decimal_to_binary by being a general converter for any base between 2 and 36.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. the many specific conversion siblings (e.g., decimal_to_binary). The description does not mention preferred scenarios or alternatives, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
basic_sentimentCInspect
Basic sentiment analysis using word lists.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | Input text (truncated to 100 chars if longer) |
| score | Yes | Sentiment score (-1 to 1, positive = positive sentiment) |
| sentiment | Yes | Overall sentiment: positive, negative, or neutral |
| negative_words | Yes | Negative words found in the text |
| positive_words | Yes | Positive words found in the text |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only mentions 'using word lists', hinting at a simplistic approach, but fails to clarify limitations (e.g., no context awareness, no negation handling) or output specifics (e.g., polarity vs. score). The agent is left uninformed about potential pitfalls.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that efficiently states the tool's purpose. It is front-loaded and avoids verbosity. However, it could be slightly more informative without becoming lengthy, which prevents a higher score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description does not inform the agent about the nature of the output (e.g., label vs. score, range of values). For a tool with complexity as low as one parameter, the description still feels incomplete because it fails to set expectations beyond 'sentiment analysis'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'text' which has a clear description 'Text to analyze'. The tool description adds 'using word lists' but does not provide additional semantic constraints (e.g., length, language). The baseline of 3 is appropriate as the schema already conveys the parameter's meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs 'basic sentiment analysis using word lists'. It identifies the action (analysis), resource (text), and method (word lists). While not specifying the output format (e.g., positive/negative or score), it is distinct from sibling tools and adequately conveys the core purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are no exclusions, prerequisites, or mention of other tools (e.g., readability_score or text_similarity). The description leaves it to the agent to infer use cases without explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
binary_decodeCInspect
Decode binary to text.
| Name | Required | Description | Default |
|---|---|---|---|
| binary | Yes | Binary string to decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| binary | No | |
| decoded | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral disclosure. It fails to mention expected binary format (e.g., ASCII '0' and '1' only, spaces allowed?), error handling for invalid input, or whether it handles multi-byte characters. The minimal description leaves significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. It is appropriately brief for a simple tool, though it could benefit from slightly more structure (e.g., mentioning input format). It is not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, single action) and presence of an output schema, the description is minimally adequate. However, it lacks context about output format and fails to distinguish from similar tools, making it less complete for informed selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already describes the 'binary' parameter as 'Binary string to decode'. The description adds no additional meaning beyond the schema, so it meets the baseline for high coverage but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Decode binary to text' clearly states the action (decode) and resource (binary). It is specific and directly describes the tool's purpose, but does not differentiate itself from sibling decoding tools like base64_decode, hex_decode, or morse_decode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternative decode tools. There is no mention of input format, prerequisites, or comparison to siblings, leaving the agent to guess the appropriate context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
binary_encodeCInspect
Encode text to binary.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to binary encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| binary | Yes | |
| original | Yes | |
| binary_no_spaces | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It does not mention the output format (e.g., string of '0's and '1's), edge cases, or error handling, leaving significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with one sentence, but it omits important details that could be included without significant bloat. It earns its place but is not optimally informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although the tool is simple and has an output schema, the description is too brief to fully inform an AI. It fails to clarify the output format or contrast with similar tools, leaving gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameter 'text' is fully documented in the schema. The description adds no extra meaning beyond the schema's own description ('Text to binary encode'). Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('encode') and the target ('text to binary'), which distinguishes it from other encoding tools like base64_encode or hex_encode. It is specific and not a tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives such as base64_encode or hex_encode. Given the many sibling encoding tools, this omission makes it harder for an AI to select the correct tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
binary_to_decimalBInspect
Convert binary to decimal.
| Name | Required | Description | Default |
|---|---|---|---|
| binary | Yes | Binary number string |
Output Schema
| Name | Required | Description |
|---|---|---|
| binary | Yes | |
| decimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose input validation, error handling, or limitations (e.g., handling of non-binary characters). The burden of transparency falls entirely on the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence with no wasted words. However, it could be slightly more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with an output schema, the description is minimally adequate. It fails to mention that the input must be a valid binary string, but the tool's low complexity reduces the gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'binary' described as 'Binary number string'. The description adds no additional meaning beyond the schema, but for a single-param tool the baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert binary to decimal' uses a specific verb and resource, clearly distinguishing it from sibling tools like decimal_to_binary, hexadecimal_to_decimal, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like base_convert or other base conversion tools. The description is too minimal to provide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
blend_colorsBInspect
Blend two colors together.
| Name | Required | Description | Default |
|---|---|---|---|
| color1 | Yes | First hex color | |
| color2 | Yes | Second hex color | |
| weight | No | Blend weight (0-1, 0.5 = equal mix) |
Output Schema
| Name | Required | Description |
|---|---|---|
| color1 | Yes | |
| color2 | Yes | |
| weight | Yes | |
| blended | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It states 'Blend' but does not specify the algorithm (linear interpolation? weighted average?), edge cases (e.g., invalid hex, alpha support), or that the weight parameter controls the mix proportion.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 5 words is concise and front-loaded. However, it is slightly under-specified for the task; a bit more detail could improve clarity without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks context about the blending method (e.g., additive, subtractive, linear), default behavior, and assumptions. Given many color-related siblings, this brevity is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description adds no extra meaning beyond 'Blend', so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Blend two colors together' uses a specific verb ('Blend') and resource ('colors'), clearly distinguishing it from siblings like lighten_color, darken_color, or analogous_colors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs other color manipulation tools (e.g., mix vs hsl_to_hex). The purpose is implied but no explicit context or alternatives are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bounding_boxCInspect
Calculate bounding box around a point.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Center latitude | |
| lon | Yes | Center longitude | |
| unit | No | Unit: km or mi | km |
| radius | Yes | Radius |
Output Schema
| Name | Required | Description |
|---|---|---|
| unit | Yes | |
| center | Yes | |
| radius | Yes | |
| bounding_box | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden, but it only says 'calculate bounding box'. It does not disclose whether the output includes min/max corners, how edge cases (e.g., near poles) are handled, or what assumptions are made about the earth model. This is insufficient for safe usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at one sentence, which is appropriate for a simple tool. However, it may be too terse given the four parameters and potential complexity of geospatial calculations. It sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the four parameters and existence of an output schema, the description still lacks essential context such as what the bounding box represents (e.g., a square in lat/lon degrees?), how the unit affects the radius, or how the result is structured. More context is needed for effective use, especially among many sibling geospatial tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; for example, it does not clarify that 'radius' is the half-extent of the box. It meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (calculate) and the resource (bounding box) with a modifier (around a point), making the purpose specific and understandable. However, it does not differentiate from sibling geospatial tools like haversine_distance or point_in_polygon, which slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It lacks any mention of context, prerequisites, or exclusions. The agent is left to infer usage from the name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
break_evenCInspect
Calculate break-even point.
| Name | Required | Description | Default |
|---|---|---|---|
| fixed_costs | Yes | Fixed costs | |
| cost_per_unit | Yes | Variable cost per unit | |
| price_per_unit | Yes | Price per unit |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| fixed_costs | No | |
| cost_per_unit | No | |
| price_per_unit | No | |
| break_even_units | No | |
| break_even_revenue | No | |
| contribution_margin | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic purpose and does not explain what the return value represents (e.g., units needed, revenue), nor any side effects or permissions required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but arguably too minimal. It could be slightly longer to add useful context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's financial nature and three required parameters, the description should explain what the break-even point means (e.g., units to sell to cover costs). The existence of an output schema does not compensate for the lack of contextual explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents all three parameters with titles and descriptions. The tool description adds no additional meaning beyond what the schema provides, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates a break-even point, which is a specific verb+resource. Among siblings, it's distinct from other financial calculations like calculate_margin or calculate_markup, though no explicit differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use break_even versus other financial tools. The description lacks context on prerequisites or scenarios, leaving the agent to infer usage solely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
build_urlBInspect
Build a URL from components.
| Name | Required | Description | Default |
|---|---|---|---|
| base | Yes | Base URL | |
| path | No | Path to append | |
| params | No | Query params as key=value&key2=value2 |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| base | Yes | |
| path | Yes | |
| params | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist. The description does not disclose behavioral traits such as encoding, error handling, or how the URL is assembled (e.g., trailing slash, query parameter ordering). This is insufficient for a constructive tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is appropriately concise and structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks essential behavioral details (e.g., parameter composition order, encoding, error conditions) needed for safe and correct use. It is too minimal for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The tool description adds no additional semantic value beyond what the schema already provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool builds a URL from components, using a specific verb and resource. It distinguishes from sibling tools like parse_url or add_query_param by implying construction from multiple parts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., build_url_2, parse_url, add_query_param). The description lacks context for appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
build_url_2CInspect
Build a URL from components.
| Name | Required | Description | Default |
|---|---|---|---|
| host | Yes | Hostname | |
| path | No | URL path | |
| port | No | Port number | |
| query | No | Query string (without ?) | |
| scheme | No | URL scheme | https |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| components | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose default behaviors (e.g., scheme defaults to 'https', path and query default to empty), error handling, authentication needs, or side effects. The description is insufficient for an agent to anticipate behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that is front-loaded. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and constructs a URL, the description lacks details on how components are combined (order, handling of leading slashes, query formatting). Although an output schema exists, the description should provide enough context for an agent to know what kind of URL is produced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are documented in the schema. The description adds no semantic enrichment beyond what is already in the schema, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Build' and the resource 'URL from components', indicating a constructive operation. It distinguishes from siblings like parse_url (decompose URL) and add_query_param (modify single param). However, the phrase 'from components' is slightly vague and does not differentiate from build_url.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like build_url or add_query_param. There is no mention of prerequisites, when not to use, or contextual cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
business_daysAInspect
Count business days between two dates (excluding weekends).
| Name | Required | Description | Default |
|---|---|---|---|
| end_date | Yes | End date (YYYY-MM-DD) | |
| start_date | Yes | Start date (YYYY-MM-DD) |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| end_date | No | |
| start_date | No | |
| total_days | No | |
| weekend_days | No | |
| business_days | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It states the core behavior (counting business days, excluding weekends) but does not clarify inclusivity of dates, holiday handling, or edge cases. This is minimal but not fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly states the purpose. It is front-loaded with the key action and resource, with no extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two parameters and an output schema (not shown). The description covers the essential purpose and behavior. It would benefit from clarifying inclusivity of dates, but overall it is adequate for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for each parameter (start_date and end_date). The description adds no additional meaning beyond what the schema provides, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Count' with resource 'business days between two dates' and clearly distinguishes from sibling tools like 'date_diff' by specifying 'excluding weekends'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for counting weekdays only but does not explicitly state when to use this tool versus alternatives like 'date_diff' or 'add_business_days'. No explicit when-not-to-use guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
bytes_to_humanCInspect
Convert bytes to human-readable format.
| Name | Required | Description | Default |
|---|---|---|---|
| bytes_val | Yes | Size in bytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| bytes | Yes | |
| gigabytes | Yes | |
| kilobytes | Yes | |
| megabytes | Yes | |
| human_readable | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not disclose return format, units, precision, rounding behavior, or handling of edge cases like negative values. For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it omits important details such as output format. It is not overly long, but could be more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity (1 param), the description fails to mention return format or that the output is a string. Has output schema true, but no output schema text provided in the definition, so completeness is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has full coverage of parameters with a description 'Size in bytes'. The tool description adds no additional meaning beyond what the schema already provides, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'bytes' to a human-readable format. It is specific and easy to understand, but does not differentiate from sibling tool 'format_bytes' which may have similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'format_bytes'. The description does not mention prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_ageBInspect
Calculate age from birthdate.
| Name | Required | Description | Default |
|---|---|---|---|
| birthdate | Yes | Birth date (YYYY-MM-DD) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| age_days | No | |
| age_years | No | |
| birthdate | No | |
| age_months | No | |
| next_birthday | No | |
| days_until_birthday | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It only says 'calculate age from birthdate' without disclosing assumptions (e.g., current date, output format, validity constraints). The behavior is minimally transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists (presumably), the description does not clarify what the output contains (e.g., years only). For a simple tool it is adequate, but completeness could be improved by stating output type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter described in the schema. The description adds no extra meaning beyond what the schema already provides, so baseline score 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate age from birthdate,' specifying the verb and resource. It is specific and unambiguous, though it does not differentiate from the sibling tool calculate_age_2.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like calculate_age_2, nor are there any prerequisites or context hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_age_2BInspect
Calculate age from birthdate.
| Name | Required | Description | Default |
|---|---|---|---|
| as_of | No | Calculate age as of date (YYYY-MM-DD) | |
| birthdate | Yes | Birthdate (YYYY-MM-DD) |
Output Schema
| Name | Required | Description |
|---|---|---|
| as_of | No | |
| error | No | |
| age_years | No | |
| birthdate | No | |
| age_months | No | |
| total_days | No | |
| total_weeks | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only states the basic action without disclosing behavioral traits like leap year handling, timezone considerations, or behavior for future dates. The output schema exists but its content is unknown; the description adds no transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so return values are presumably documented. However, the description omits the optional 'as_of' parameter and does not explain the calculation context (e.g., calendar, age in years). For a simple tool it is minimally adequate but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents both parameters adequately. The description does not add any parameter-specific meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and resource 'age from birthdate'. However, it does not differentiate from the sibling tool 'calculate_age', which likely has similar purpose. The optional 'as_of' parameter is not mentioned, but the core purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'calculate_age'. The description does not specify prerequisites, context, or situations where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_bearingBInspect
Calculate bearing (direction) between two coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
| lat1 | Yes | Latitude of start point | |
| lat2 | Yes | Latitude of end point | |
| lon1 | Yes | Longitude of start point | |
| lon2 | Yes | Longitude of end point |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose output format (e.g., degrees vs radians), precision, or whether 0 degrees is north. Lacks details on behavior beyond the basic calculation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 8 words, no redundancy. Front-loaded with the core purpose. Efficiently provides essential information without waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with 4 numeric params, but the description omits what the return value represents (e.g., a decimal number in degrees). With no output schema, this is a notable gap in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter having a concise description. The tool description adds no additional semantic context beyond the schema, which is adequate but not improved.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates bearing between two coordinates, with a specific verb 'calculate' and resource 'bearing'. It distinguishes from sibling tools like haversine_distance (distance) and destination_point.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., haversine_distance). No prerequisites or context about coordinate validity or expected input format.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_bmiCInspect
Calculate Body Mass Index (BMI).
| Name | Required | Description | Default |
|---|---|---|---|
| height_cm | Yes | Height in centimeters | |
| weight_kg | Yes | Weight in kilograms |
Output Schema
| Name | Required | Description |
|---|---|---|
| bmi | Yes | |
| category | Yes | |
| height_cm | Yes | |
| weight_kg | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states the basic function, omitting details such as that it is a pure calculation with no side effects, or that it requires positive inputs (already in schema).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence) and front-loaded, but it is too minimal, lacking useful context. It could include the formula or a note about standard units.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and has an output schema, so completeness is less critical. Still, the description is bare and could benefit from mentioning that BMI is weight/height^2.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the parameter names and units provided in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool calculates Body Mass Index (BMI), providing the full name and acronym. However, it does not differentiate from sibling tools like 'calculate_bmr' or 'ideal_weight'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided; there is no indication of when to use this tool versus alternatives, any prerequisites, or contexts where it is inappropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_bmrAInspect
Calculate Basal Metabolic Rate (BMR) using Mifflin-St Jeor equation.
| Name | Required | Description | Default |
|---|---|---|---|
| age | Yes | Age in years | |
| sex | Yes | Sex: male or female | |
| height_cm | Yes | Height in centimeters | |
| weight_kg | Yes | Weight in kilograms |
Output Schema
| Name | Required | Description |
|---|---|---|
| age | Yes | |
| sex | Yes | |
| height_cm | Yes | |
| weight_kg | Yes | |
| bmr_calories | Yes | |
| tdee_by_activity | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavior. It states the calculation method but omits any information about side effects, permissions, or the nature of the operation (read-only). It is adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that front-loads the purpose. There is no extraneous information, and every word contributes to clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally complete. It names the equation but could benefit from briefly explaining what BMR represents or typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents parameters with units. The description adds no additional meaning beyond what is in the schema, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates BMR using the Mifflin-St Jeor equation. It provides a specific verb and resource, distinguishing it from sibling tools like calculate_bmi or calculate_macros.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no guidance on when to use this tool versus alternatives. It does not mention any prerequisites or context, leaving the agent to infer usage purely from the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_correlationBInspect
Calculate Pearson correlation coefficient.
| Name | Required | Description | Default |
|---|---|---|---|
| x | Yes | Comma-separated X values | |
| y | Yes | Comma-separated Y values |
Output Schema
| Name | Required | Description |
|---|---|---|
| x | No | |
| y | No | |
| code | No | |
| count | No | |
| error | No | |
| r_squared | No | |
| correlation | No | |
| interpretation | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description merely states the calculation. It fails to disclose behavioral traits such as handling of missing values, input validation, output range, or data length constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. However, it lacks structure (e.g., separate sections for purpose, parameters, output). Still, for a simple tool it is appropriately sized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description omits key context such as typical use cases, interpretation of the coefficient, and behavior with mismatched list lengths. It is insufficient for a statistical tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with meaningful descriptions ('Comma-separated X values' and 'Comma-separated Y values'). The description adds no additional parameter context beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate Pearson correlation coefficient' uses a specific verb ('calculate') and resource ('Pearson correlation coefficient'), clearly distinguishing it from sibling tools like 'calculate_covariance' or 'calculate_mean'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., 'calculate_covariance' or other statistical tools). Usage is implied only by the tool's name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_covarianceBInspect
Calculate covariance between two datasets.
| Name | Required | Description | Default |
|---|---|---|---|
| x | Yes | Comma-separated X values | |
| y | Yes | Comma-separated Y values | |
| population | No | Population covariance vs sample |
Output Schema
| Name | Required | Description |
|---|---|---|
| x | No | |
| y | No | |
| code | No | |
| type | No | |
| count | No | |
| error | No | |
| covariance | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It fails to disclose that inputs expect comma-separated numeric values or that population/sample covariance is parameterized. Minimal disclosure beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single clear sentence with no extraneous information. Ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists (not shown), so return values need not be explained. However, description omits constraints like equal-length datasets and numeric values, which are critical for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already explains parameters (x, y as comma-separated strings, population boolean). Description adds no additional semantic value beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Calculate covariance between two datasets,' clearly indicating the verb (calculate) and resource (covariance). It distinguishes from siblings like calculate_correlation and calculate_variance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The sibling list includes many statistical functions, but the description lacks context for selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_discountCInspect
Calculate discounted price.
| Name | Required | Description | Default |
|---|---|---|---|
| original_price | Yes | Original price | |
| discount_percent | Yes | Discount percentage |
Output Schema
| Name | Required | Description |
|---|---|---|
| final_price | Yes | |
| original_price | Yes | |
| discount_amount | Yes | |
| discount_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behaviors like rounding, handling of negative values, or the formula used. It only repeats the purpose without added behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. It could include more information without losing conciseness, but it is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and existence of output schema, the description is too minimal. It lacks details on the calculation formula or expected behavior, which is needed for unambiguous use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description does not need to add parameter meaning. It adds nothing beyond what the schema provides, meeting baseline expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Calculate discounted price', which clearly indicates the verb and resource. However, it does not differentiate from sibling tools like 'calculate_margin' or 'calculate_tip' that also compute prices with percentages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention any prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_macrosCInspect
Calculate macronutrient targets.
| Name | Required | Description | Default |
|---|---|---|---|
| goal | No | Goal: lose, maintain, gain | maintain |
| calories | Yes | Daily calorie target |
Output Schema
| Name | Required | Description |
|---|---|---|
| goal | Yes | |
| macros | Yes | |
| calories | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses zero behavioral traits: no mention of whether it uses standard formulas, what happens with invalid inputs, or any side effects. This is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (two words) but under-specified. While it is front-loaded, it fails to provide essential information, making it more 'minimal' than 'concisely informative.'
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description is incomplete. It does not hint at what macronutrients are calculated (e.g., protein, carbs, fat) or how the goal parameter influences results. A more descriptive summary is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters described in schema). Description adds no extra meaning beyond what the schema already provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb and resource: 'Calculate macronutrient targets.' It is specific enough to indicate the tool's purpose, but does not differentiate from sibling tools like calculate_bmi or calculate_bmr, which are also nutrition-related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description lacks context about prerequisites or conditions (e.g., requiring user's weight, activity level), leaving the agent to guess.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_marginBInspect
Calculate profit margin.
| Name | Required | Description | Default |
|---|---|---|---|
| cost | Yes | Cost price | |
| selling_price | Yes | Selling price |
Output Schema
| Name | Required | Description |
|---|---|---|
| cost | Yes | |
| profit | Yes | |
| selling_price | Yes | |
| margin_percent | Yes | |
| markup_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states only 'Calculate profit margin' with no mention of side effects, return behavior, or required permissions. The existence of an output schema partially compensates, but the description itself adds no transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that efficiently conveys the tool's purpose. There is no extraneous information, and the key action and resource are front-loaded, making it highly scannable for an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter calculation tool with an output schema, the description is minimally adequate. However, it lacks context about the formula (e.g., (selling_price - cost)/selling_price * 100), edge cases (e.g., zero cost), or related tools, which could improve decision-making given the large sibling list.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters ('Cost price', 'Selling price'), so the schema already defines their meaning. The description adds no additional context beyond the schema, resulting in baseline adequacy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and the resource 'profit margin', defining the tool's core function. It is specific enough to distinguish from siblings like 'calculate_markup' or 'break_even', though it lacks detail on the formula (e.g., gross vs net margin).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'calculate_markup' or 'break_even'. The description does not specify prerequisites, limitations, or exclusions, leaving the agent without context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_markupBInspect
Calculate selling price from cost and markup.
| Name | Required | Description | Default |
|---|---|---|---|
| cost | Yes | Cost price | |
| markup_percent | Yes | Markup percentage |
Output Schema
| Name | Required | Description |
|---|---|---|
| cost | Yes | |
| profit | Yes | |
| selling_price | Yes | |
| markup_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavioral traits such as how markup percent is interpreted (e.g., 20 for 20% or 0.2), rounding behavior, or error handling for invalid inputs like zero cost.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) and front-loaded with the verb, making it easy to parse. No wasted words, though it could include a formula or example without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is adequate but lacks examples, edge case notes, or formula hints. It does not fully prepare the agent for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with minimal descriptions ('Cost price', 'Markup percentage'), and the tool description adds no additional meaning or examples beyond what the schema already provides. Baseline is 3 since schema is complete.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Calculate') and resource ('selling price'), and distinguishes from siblings like 'calculate_margin' or 'calculate_discount' by naming the specific inputs (cost and markup).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives (e.g., 'calculate_margin'), nor does it explain the difference between markup and margin. No contextual hints for agent decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_meanBInspect
Calculate arithmetic mean (average).
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| mean | Yes | |
| count | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is minimal and does not disclose behavioral traits such as edge cases, limitations, or return format. With no annotations, the burden falls on the description, which it fails to address adequately.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence that front-loads the purpose. Every word is necessary and there is no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity and presence of an output schema, the description is minimally complete. However, it could benefit from clarifying the return value or distinguishing from similar tools like 'average'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter already described as 'Comma-separated numbers'. The description adds no additional meaning beyond the schema, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates the arithmetic mean (average), which is a specific verb and resource. However, it does not distinguish itself from the sibling tool 'average', which may cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like geometric_mean or harmonic_mean. The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_medianCInspect
Calculate median.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| median | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to mention that the input must be comma-separated, how ties are handled, or what the return value looks like. This is a critical gap for a tool that might have edge cases (e.g., even-length lists).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (two words), but this is underspecification rather than conciseness. It lacks necessary detail to be useful. A concise description would pack more information efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (one parameter, output schema present), the description is incomplete. It doesn't explain the median calculation behavior, error handling, or return format. The output schema might help, but the description should complement it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: the only parameter 'numbers' has a description 'Comma-separated numbers'. The description 'Calculate median' does not add any meaning beyond what the schema already provides, but since the schema is fully descriptive, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate median' clearly states the action and resource, matching its name. However, it does not distinguish itself from sibling tools like 'calculate_mean' or 'calculate_mode', which severely limits its utility for an agent selecting among many similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, limitations, or when not to use it. An agent would have no basis to prefer this over other statistical calculators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_midpointCInspect
Calculate geographic midpoint between two coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
| lat1 | Yes | Latitude of point 1 | |
| lat2 | Yes | Latitude of point 2 | |
| lon1 | Yes | Longitude of point 1 | |
| lon2 | Yes | Longitude of point 2 |
Output Schema
| Name | Required | Description |
|---|---|---|
| point1 | Yes | |
| point2 | Yes | |
| midpoint | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states 'calculate geographic midpoint' without disclosing the underlying model (e.g., great-circle or spherical Earth assumptions). No behavioral traits like edge cases or error handling are mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no extraneous words. Front-loaded and efficient. Could be slightly expanded for clarity without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description is adequate but omits the geographic model used. It is complete enough for basic use but lacks details that would help in more nuanced spatial contexts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema's parameter descriptions (e.g., 'Latitude of point 1').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate geographic midpoint between two coordinates' clearly states the verb and resource, and distinguishes it from sibling tools like 'distance' or 'haversine_distance'. However, it does not explicitly differentiate from all geographic tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'bounding_box' or 'point_in_polygon'. No prerequisites or limitations are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_modeBInspect
Calculate mode (most frequent value).
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| mode | Yes | |
| numbers | Yes | |
| frequency | Yes | |
| is_multimodal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as handling of multiple modes, empty input, or non-numeric values. The tool's behavior is mostly inferred from the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one sentence. It is front-loaded but lacks structure for edge cases; still, it earns its place without verbosity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description covers the basic functionality. However, it omits behavior on ties or invalid inputs, making it slightly incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a description for the 'numbers' parameter. The tool description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifically states 'Calculate mode (most frequent value)', which clearly identifies the tool's purpose and distinguishes it from sibling tools like calculate_mean and calculate_median.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as calculate_mean or calculate_median. Usage is implied but not explicitly clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_percentileBInspect
Calculate a specific percentile.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers | |
| percentile | Yes | Percentile to calculate |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| value | Yes | |
| numbers | Yes | |
| percentile | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only says 'Calculate a specific percentile' without disclosing behavioral traits like interpolation method, sorting behavior, or handling of empty/non-numeric input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately sized for the tool's simplicity and front-loads the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists to document return values, the description lacks details on edge cases (e.g., empty input, non-numeric strings) and algorithmic behavior (e.g., sorting, interpolation method), which are important for a statistical calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters (comma-separated numbers and percentile value). The description adds no extra meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates a specific percentile, which is a clear verb and resource. It distinguishes from siblings like calculate_median or calculate_quartiles by specifying 'specific percentile' but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not provide context or exclusions, leaving the agent without direction on selecting this tool over similar statistical tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_productBInspect
Calculate product of numbers.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| numbers | Yes | |
| product | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides only a generic one-liner. It does not disclose behavioral traits like error handling (e.g., empty input), output format, or safety (e.g., non-destructive). Annotations are absent, so the description should carry the burden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, making it concise. However, it could include more useful information without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one string parameter, output schema exists), the description is mostly complete for basic understanding. However, it lacks details on return type or edge cases, which are partially compensated by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (one parameter with explicit description 'Comma-separated numbers'). The tool description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Calculate product of numbers,' which is clear about the action and resource. However, it does not distinguish itself from sibling tools like 'multiply,' which may cause confusion about when to use which.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as 'multiply' or 'add.' The description lacks context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_quartilesBInspect
Calculate quartiles (Q1, Q2, Q3).
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| q1 | Yes | |
| q3 | Yes | |
| iqr | Yes | |
| max | Yes | |
| min | Yes | |
| count | Yes | |
| numbers | Yes | |
| q2_median | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only says 'calculate quartiles'. It does not disclose behavior on incomplete data, rounding, or how it handles an even number of values.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence, front-loaded with the core purpose. However, it could add useful context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and only one parameter, the description is minimally complete. However, it lacks behavior details and usage guidance, which a more complete description would include.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% with a single parameter 'numbers' described as 'Comma-separated numbers'. The description does not add meaning beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates quartiles Q1, Q2, Q3, which is a specific verb+resource combination. It distinguishes itself from sibling tools like calculate_median or calculate_percentile by explicitly naming the quartiles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like calculate_percentile or calculate_median. There is no mention of handling tied quartiles or distribution types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_rangeBInspect
Calculate range (max - min).
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| min | Yes | |
| range | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose edge case handling (e.g., empty input, non-numeric strings). The behavioral impact is minimal for a basic operation, but the description fails to add any behavioral context beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant information. It is efficiently front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and has an output schema, the description lacks information on error handling, return format, or input validation. Given the nature of the tool, this is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with a description for the single parameter. The description adds no additional meaning beyond the schema's 'Comma-separated numbers'. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and the resource 'range', explicitly defining the operation as 'max - min'. This distinguishes it from sibling tools like 'calculate_mean' or 'calculate_median'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'calculate_stddev' or 'calculate_variance'. The description lacks context about appropriate use cases or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_stddevCInspect
Calculate standard deviation.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers | |
| population | No | Use population std dev vs sample std dev |
Output Schema
| Name | Required | Description |
|---|---|---|
| mean | Yes | |
| type | Yes | |
| count | Yes | |
| numbers | Yes | |
| variance | Yes | |
| standard_deviation | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It merely repeats the tool's name without describing what the tool returns, how it handles edge cases, or the effect of the 'population' parameter. The description adds minimal behavioral insight beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately short for a simple tool, though it could benefit from a brief mention of the parameters or return value. It is concise but not excessively so.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has an output schema (present but not shown), the description need not detail return values. However, it omits important context such as the distinction between population and sample standard deviation, which the 'population' parameter controls. For a tool with two parameters and a boolean flag, the description is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the schema already documents both parameters ('numbers' as comma-separated values, 'population' as boolean). The tool description adds no additional parameter meaning beyond what the schema provides, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate standard deviation' states the verb 'calculate' and resource 'standard deviation' clearly. However, it does not differentiate from sibling tools like 'calculate_variance' or 'describe_data', which are related statistical tools. The purpose is clear but not uniquely distinguishing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'calculate_variance', 'calculate_mean', or 'describe_data'. There are no exclusions, prerequisites, or context about the appropriate use of population vs sample standard deviation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_sumBInspect
Calculate sum of numbers.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| sum | Yes | |
| count | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description should disclose behavioral aspects. It only repeats the basic function without detailing output format, error handling, or constraints. The schema provides some parameter info, but the description adds no extra behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one sentence that immediately conveys the purpose. There is no wasted text, and it is front-loaded effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is somewhat adequate but lacks context to differentiate it from many similar sibling math tools. It does not explain the scope (e.g., list vs. two numbers) or when to prefer this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter described as 'Comma-separated numbers'. The description does not add any additional meaning beyond the schema, so it meets the baseline for a high-coverage schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Calculate sum' and the resource 'numbers', which is specific enough. However, it does not differentiate from sibling tools like 'add' or 'sum_numbers', which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives like 'sum_numbers' or 'add', nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_tipBInspect
Calculate tip and split bill.
| Name | Required | Description | Default |
|---|---|---|---|
| split | No | Number of people to split | |
| amount | Yes | Bill amount | |
| tip_percent | No | Tip percentage |
Output Schema
| Name | Required | Description |
|---|---|---|
| total | Yes | |
| per_person | Yes | |
| split_ways | Yes | |
| tip_amount | Yes | |
| bill_amount | Yes | |
| tip_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states 'Calculate tip and bill split' without specifying how results are returned (e.g., total tip, per-person amounts, rounding behavior), leaving significant ambiguity about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core functionality with no unnecessary words. It is front-loaded and clear, earning its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (3 parameters) and the existence of an output schema (not shown), the description is minimally adequate. However, it fails to contextualize what the user gets back (e.g., total tip, per-person amounts), relying entirely on the output schema. A more complete description would briefly mention return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions, so the schema already explains each parameter's meaning. The description adds no extra semantic value beyond the schema; it does not elaborate on relationships like 'amount is the pre-tip total' or 'split divides the final bill equally'. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Calculate' and the resources 'tip' and 'bill split', making the tool's purpose immediately obvious. It distinguishes itself from sibling math/utility tools by indicating it handles a complete tip-and-split scenario.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. While it is the only tip calculator among siblings, there is no mention of when to use it instead of manually calculating with basic math tools like 'add' or 'percentage'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_varianceCInspect
Calculate variance.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers | |
| population | No | Use population variance (N) vs sample variance (N-1) |
Output Schema
| Name | Required | Description |
|---|---|---|
| mean | Yes | |
| type | Yes | |
| count | Yes | |
| numbers | Yes | |
| variance | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description adds no behavioral details beyond the basic operation. It does not disclose error handling, performance, or that it is a pure calculation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
At only two words, the description is extremely concise with no wasted content. However, it could be slightly expanded for clarity without losing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (though not shown), the description doesn't need to explain return values. However, it omits mention of the population vs sample distinction, which is important for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes the parameters (comma-separated numbers, boolean for population). The description adds no additional meaning, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate variance' clearly states the verb and resource. It is specific but does not distinguish from sibling statistical tools like calculate_stddev or calculate_covariance.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as calculate_mean or calculate_stddev. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_vatCInspect
Calculate VAT (Value Added Tax).
| Name | Required | Description | Default |
|---|---|---|---|
| amount | Yes | Amount | |
| vat_rate | No | VAT rate percentage | |
| inclusive | No | Is amount VAT inclusive? |
Output Schema
| Name | Required | Description |
|---|---|---|
| vat_rate | Yes | |
| net_amount | Yes | |
| vat_amount | Yes | |
| gross_amount | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose any behavioral traits such as side effects, authorization needs, or rate limits. It only says 'calculate,' which implies a pure function, but without explicit statement, the agent lacks crucial behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, very concise, and front-loaded with the core purpose. It has no wasted words, but it could be slightly expanded without breaking conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and full parameter documentation, the description could be adequate but lacks usage guidelines and behavioral details. For a simple calculation tool, it is minimally viable but incomplete in context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the baseline is 3. The description adds no extra meaning beyond the schema; it does not provide examples or clarify the relationship between inclusive and exclusive calculations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate VAT (Value Added Tax).' It uses a specific verb and resource, and among many calculation siblings, it uniquely identifies the VAT calculation tool. However, it is brief and does not differentiate from similar tools like calculate_discount.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are no exclusions, prerequisites, or context about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calculate_zscoreCInspect
Calculate z-score (standard score).
| Name | Required | Description | Default |
|---|---|---|---|
| mean | Yes | Population mean | |
| value | Yes | Value to calculate z-score for | |
| stddev | Yes | Population standard deviation |
Output Schema
| Name | Required | Description |
|---|---|---|
| mean | Yes | |
| value | Yes | |
| z_score | Yes | |
| standard_deviation | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It does not disclose any edge cases (e.g., behavior if stddev is zero, which the schema prevents) or output format. The behavior is implied but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no fluff. It is front-loaded and efficient, though slightly under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the output schema exists and parameters are fully described in the schema, the description is minimally adequate. However, for a tool with no annotations and many siblings, a bit more context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the three parameters. The description adds no additional meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates a z-score (standard score). It is specific enough, but does not differentiate from sibling statistical tools like calculate_stddev or calculate_mean, which are related but distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't explain that it normalizes a value relative to a distribution, nor does it contrast with other statistical functions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
calories_burnedCInspect
Estimate calories burned during activities.
| Name | Required | Description | Default |
|---|---|---|---|
| activity | Yes | Activity type | |
| weight_kg | Yes | Body weight in kg | |
| duration_minutes | Yes | Duration in minutes |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| activity | No | |
| met_value | No | |
| weight_kg | No | |
| calories_burned | No | |
| duration_minutes | No | |
| available_activities | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only states the action, with no mention of accuracy, assumptions, or side effects. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words, but it could benefit from slightly more detail without being verbose. It is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is marginally complete. However, it lacks information about the output (e.g., unit of measure, formula used) and does not mention any constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema's parameter titles and descriptions, which are minimal themselves.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool estimates calories burned during activities, using a specific verb and resource. However, it does not distinguish from similar health tools like calculate_bmr or estimate_body_fat.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, nor any context about limitations or prerequisites. The description does not help an agent decide between this and sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
camel_caseCInspect
Convert text to camelCase.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| camel_case | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only states 'Convert text to camelCase' with no details on edge cases (e.g., special characters, numbers, whitespace) or return format, which is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, using a single sentence. However, it could be more structured by adding key details while maintaining brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple string conversion tool with one parameter and an output schema, the description is minimally adequate. However, it lacks information about conversion rules and edge cases, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter is described in the schema. The description adds no extra meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: converting text to camelCase. However, it does not distinguish between the many sibling case conversion tools (e.g., to_camel_case, pascal_case), which limits its clarity for selection.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention context, prerequisites, or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capitalizeCInspect
Capitalize the first letter of each word.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to capitalize |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| capitalized | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden but only states the basic action. It does not disclose edge cases (e.g., non-alphabetic characters) or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, but it lacks necessary details for understanding nuances, making it adequate but with clear gaps.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the many similar sibling tools, the description is insufficient to help an agent choose correctly. It does not address output schema or behavioral details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% as the only parameter 'text' is described. The description adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool capitalizes the first letter of each word. However, with many similar sibling tools like 'capitalize_text', 'title_case', and 'smart_title_case', it lacks differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool vs alternatives like 'capitalize_text' or 'title_case'. No context or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capitalize_textAInspect
Capitalize first letter only.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to capitalize |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the core behavior (first letter only) but does not disclose edge cases (e.g., empty string, special characters) or results. It is minimally sufficient but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundancy. Every word is purposeful and directly conveys the tool's function. It is optimally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description conveys the core operation. However, it omits mention of the return value (presumably the capitalized string). Could be improved by explicitly stating the output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (parameter 'text' described as 'Text to capitalize'). The tool description adds 'Capitalize first letter only', clarifying the transformation beyond the schema's generic label. This adds meaningful context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Capitalize first letter only' clearly specifies the action (capitalize) and the scope (first letter only), distinguishing it from siblings like 'capitalize' which may capitalize all words. It is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'capitalize', 'title_case', or 'upper_case'. The description does not mention prerequisites or context, leaving the agent with no comparative information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ceilAInspect
Round up to nearest integer.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to ceil |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description is straightforward but does not mention edge cases (e.g., negative numbers, infinity). It meets minimal expectations for a simple operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no extraneous information. It is perfectly front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple math function with one parameter and an output schema, the description provides all necessary context. No gaps or omissions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes the parameter as 'Number to ceil'. The description adds no additional semantic meaning beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Round up to nearest integer' clearly states the action and the resource, and distinguishes from sibling tools like floor or round_number.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives guidance. Usage is implied by the function name and description, but formal guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
celsius_to_fahrenheitAInspect
Convert Celsius to Fahrenheit.
| Name | Required | Description | Default |
|---|---|---|---|
| celsius | Yes | Temperature in Celsius |
Output Schema
| Name | Required | Description |
|---|---|---|
| celsius | Yes | |
| fahrenheit | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose any behavioral traits beyond the conversion itself (e.g., rounding, precision, or edge cases). For a simple tool, this is minimally acceptable but leaves room for improvement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly conveys the tool's purpose without any unnecessary information, earning top marks for efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is largely complete. However, it could optionally mention that the conversion uses the standard formula (C * 9/5 + 32) for added clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the parameter (celsius) with a title and description. The tool description adds no additional meaning beyond what is in the schema, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert Celsius to Fahrenheit' clearly states the action and resource, distinguishing it from sibling tools like 'fahrenheit_to_celsius'. It is specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No context on when to use this tool versus alternatives (e.g., fahrenheit_to_celsius) is provided. The usage is implied but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
celsius_to_kelvinBInspect
Convert Celsius to Kelvin.
| Name | Required | Description | Default |
|---|---|---|---|
| celsius | Yes | Temperature in Celsius |
Output Schema
| Name | Required | Description |
|---|---|---|
| kelvin | Yes | |
| celsius | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It does not disclose any behavioral traits such as idempotency, side effects, or safety. For a simple conversion, the lack of detail is somewhat acceptable but still leaves ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) and front-loaded, but it omits useful context. It earns its place but could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description is complete enough. It covers the essential purpose without needing to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add any extra meaning beyond the schema's parameter description. It is adequate but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the specific conversion 'Celsius to Kelvin', distinguishing it from sibling tools like fahrenheit_to_celsius or kelvin_to_celsius.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or context. It is a simple conversion, but agents lack information on when to prefer this over other temperature converters.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
centimeters_to_inchesAInspect
Convert centimeters to inches.
| Name | Required | Description | Default |
|---|---|---|---|
| centimeters | Yes | Length in centimeters |
Output Schema
| Name | Required | Description |
|---|---|---|
| inches | Yes | |
| centimeters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It implies a simple mathematical conversion with no side effects, which is adequate for a straightforward tool, but it does not mention precision, error handling, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that directly communicates the tool's purpose with zero wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter) and the presence of an output schema, the description is adequately complete. It does not explain precision but is sufficient for its narrow conversion purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the single parameter 'centimeters' as 'Length in centimeters' (100% coverage). The tool description adds no additional semantics beyond this, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the conversion from centimeters to inches. It is specific and clearly distinguishes from the sibling tool 'inches_to_centimeters'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs other conversion tools. The description simply states what it does without any context or alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
chunk_arrayAInspect
Split items into chunks of specified size.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Chunk size | |
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| chunks | Yes | |
| original | Yes | |
| chunk_size | Yes | |
| num_chunks | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states the core behavior but does not disclose edge cases (e.g., empty items, size larger than items), output format, or error handling. The existence of an output schema partially mitigates this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, entirely to the point. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity tool with full schema coverage and an output schema, the description is adequate but lacks contextual details about input format (comma-separated) and chunking behavior, which could be inferred from the schema or output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The tool description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'split' and the resource 'items into chunks of specified size', making the tool's purpose unambiguous. It distinguishes from sibling tools like array_slice or array_partition.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., array_partition, array_nth). No mention of prerequisites or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cidr_infoBInspect
Get information about a CIDR range.
| Name | Required | Description | Default |
|---|---|---|---|
| cidr | Yes | CIDR notation (e.g., 192.168.1.0/24) |
Output Schema
| Name | Required | Description |
|---|---|---|
| cidr | No | |
| code | No | |
| error | No | |
| netmask | No | |
| version | No | |
| hostmask | No | |
| last_host | No | |
| num_hosts | No | |
| first_host | No | |
| is_private | No | |
| num_addresses | No | |
| prefix_length | No | |
| network_address | No | |
| broadcast_address | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description must fully convey behavioral traits. It only states 'Get information', implying a read operation, but does not mention side effects, permissions, rate limits, or any constraints. The lack of detail is a gap for safe agent decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words. It is appropriately sized for the simplicity of the tool, conveying the core action and resource efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown) that presumably defines return values, so the description need not list them. However, it lacks context about what 'information' includes (e.g., network address, broadcast). Given the low complexity and good schema coverage, it is minimally complete but could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of the 'cidr' parameter. The tool description adds no additional meaning beyond the schema. Since schema coverage is high, a baseline of 3 is appropriate; no compensation needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get information about a CIDR range' uses a specific verb and resource. It clearly indicates the tool provides data about a CIDR range, distinguishing it from sibling tools like 'expand_cidr' or 'subnet_calculator' that have different outputs. However, 'information' is somewhat vague, lacking details on exactly what is returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'expand_cidr', 'subnet_calculator', or 'network_info'. The description does not mention context, exclusions, or conditions that would help an agent decide between tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cidr_to_netmaskBInspect
Convert CIDR prefix length to subnet mask.
| Name | Required | Description | Default |
|---|---|---|---|
| prefix | Yes | CIDR prefix length (0-32) |
Output Schema
| Name | Required | Description |
|---|---|---|
| netmask | Yes | |
| cidr_prefix | Yes | |
| total_hosts | Yes | |
| wildcard_mask | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states 'convert' without disclosing any behavioral traits such as error handling, edge cases (e.g., prefix 0 or 32), or the exact format of the output. The schema already documents the parameter constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence with zero wasted words. However, it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one simple parameter and an output schema exists, the description is minimally adequate. However, it does not explain the output format or provide context about the conversion process.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no additional meaning beyond the schema. The parameter 'prefix' is fully described in the schema with title, description, and constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert CIDR prefix length to subnet mask' clearly states the verb (convert) and resource (CIDR prefix length to subnet mask), and it distinguishes itself from sibling tool 'netmask_to_cidr' which does the reverse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives like 'cidr_info' or 'netmask_to_cidr'. It does not mention any prerequisites or context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
clampBInspect
Clamp a number within a range.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to clamp | |
| maximum | Yes | Maximum value | |
| minimum | Yes | Minimum value |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| min | Yes | |
| number | Yes | |
| clamped | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It accurately conveys the basic operation (clamping), but does not disclose edge cases (e.g., min > maximum) or return type. With no annotations, a score of 3 is appropriate for minimal but correct disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words. It is front-loaded and effectively communicates the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the 3 required parameters and presence of an output schema, the description is too brief. It lacks details on return behavior, error handling, or edge cases. For a simple numeric function this might be acceptable, but it could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described in the input schema. The description adds no additional meaning beyond the schema's field descriptions. Baseline 3 is correct since the description does not compensate or enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'clamp' and clearly indicates the resource ('a number within a range'). It distinguishes itself from sibling tools like min/max (which return extremes of multiple values) and in_range (which checks membership) by implying a bounded transformation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use clamp versus alternatives (e.g., min, max, in_range). The description does not mention prerequisites, typical use cases, or exclusion criteria, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cmyk_to_hexBInspect
Convert CMYK to hex color.
| Name | Required | Description | Default |
|---|---|---|---|
| c | Yes | Cyan (0-100) | |
| k | Yes | Key/Black (0-100) | |
| m | Yes | Magenta (0-100) | |
| y | Yes | Yellow (0-100) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| rgb | Yes | |
| cmyk | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but is minimal. It does not disclose any behavioral traits such as validation of input ranges (0-100), rounding behavior, or whether the output includes a '#' prefix. The description is too brief for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no fluff. However, it could be slightly more informative while still being concise, such as adding 'Returns a 6-character hex string without #'.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, full schema coverage, and the presence of an output schema, the description is sufficiently complete for the core purpose. However, it could mention that the output format is a hex string without the '#' prefix if that is the case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides full descriptions for all four parameters (c, m, y, k) with their ranges (0-100). The description adds no additional meaning beyond what is in the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert CMYK to hex color' clearly states the action (convert) and the specific transformation (CMYK to hex). It directly distinguishes from sibling tools like 'hex_to_cmyk' and other color converters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Since there are many color conversion siblings, the agent would benefit from explicit context such as 'Use when you have CMYK values and need a hex string.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
collatz_sequenceBInspect
Generate Collatz sequence for a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Starting number |
Output Schema
| Name | Required | Description |
|---|---|---|
| start | Yes | |
| length | Yes | |
| sequence | Yes | |
| max_value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It fails to note determinism, handling of large numbers (though schema limits to 10 million), or any side effects, leaving the agent uninformed about operational details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, effectively conveying the core purpose. It is appropriately concise for such a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and an output schema likely exists (not shown), the description lacks mention of return format or behavior. It is minimally complete, but additional context about the sequence output would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the only parameter ('Starting number'), so the description adds little beyond what the schema already provides, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action 'Generate Collatz sequence' and the resource 'for a number', effectively distinguishing it from sibling tools like 'fibonacci' or 'generate_sequence' that deal with other sequences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives (e.g., for generating a specific sequence like Collatz vs. general number sequences), nor does it mention any prerequisites or limitations beyond what the schema provides.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compareCInspect
Compare two numbers (e.g., is 0.9 greater than 0.11?).
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First number | |
| b | Yes | Second number |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | Yes | |
| b | Yes | |
| ratio | No | |
| symbol | Yes | |
| a_is_less | Yes | |
| are_equal | Yes | |
| comparison | Yes | |
| difference | Yes | |
| description | Yes | |
| a_is_greater | Yes | |
| absolute_difference | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should fully disclose behavior. It does not explain the output format (e.g., boolean, comparison result) or edge cases like equality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with an example, no wasted words. However, it lacks structured separation of purpose and behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is adequate but could be improved by clarifying comparison semantics and return type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description adds no extra meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares two numbers and gives an example. However, it does not specify the return type or distinguish itself from siblings like 'compare_2' or 'compare_decimals'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as 'compare_2' or 'compare_decimals'. The description lacks usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_2CInspect
Compare two values.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First value | |
| b | Yes | Second value |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | Yes | |
| b | Yes | |
| type | Yes | |
| equal | Yes | |
| a_length | No | |
| b_length | No | |
| a_greater | No | |
| b_greater | No | |
| difference | No | |
| equal_ignore_case | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It fails to disclose any behavioral traits such as case sensitivity, data type handling, or what action 'compare' performs (e.g., equality check, ordering). This is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but too brief to be informative. It fits a single sentence but lacks substance, making it less helpful than a slightly longer description could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the parameters and the existence of an output schema, the description is incomplete. It does not mention the return type, edge cases, or any behavior beyond the basic action, leaving the agent guessing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes the parameters as 'First value' and 'Second value'. The description adds no additional meaning beyond that, meeting the baseline but not improving understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Compare two values' clearly states the verb and resource, but lacks specificity about what the comparison yields (e.g., boolean, difference) and does not differentiate from the sibling tool 'compare'. The purpose is clear but not sufficiently detailed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'compare'. There is no mention of context, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_decimalsAInspect
Compare decimal numbers with detailed explanation (handles 0.9 vs 0.11 correctly).
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First decimal number as string | |
| b | Yes | Second decimal number as string |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | No | |
| b | No | |
| code | No | |
| error | No | |
| symbol | No | |
| a_as_float | No | |
| b_as_float | No | |
| comparison | No | |
| difference | No | |
| description | No | |
| explanation | No | |
| larger_number | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior fully. It mentions 'detailed explanation' suggesting the output includes explanatory text, but fails to specify what exactly is returned (e.g., comparison result, explanation string), leaving important gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the main purpose and key distinguishing feature, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description provides the essential purpose and an example but lacks details on edge cases, return value structure, or any constraints on input values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema's parameter descriptions, simply repeating that inputs are decimal numbers as strings.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares decimal numbers with a detailed explanation, specifying the resource and distinguishing from sibling tools like generic 'compare' or 'compare_2' through its focus on decimal precision issues.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for decimal comparisons where handling of trailing zeros matters, as illustrated by '0.9 vs 0.11 correctly', but does not explicitly exclude alternative tools or provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compare_hashesBInspect
Compare two hashes in constant time (timing-safe).
| Name | Required | Description | Default |
|---|---|---|---|
| hash1 | Yes | First hash | |
| hash2 | Yes | Second hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash1 | Yes | |
| hash2 | Yes | |
| are_equal | Yes | |
| comparison_method | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions timing-safe behavior, which is a key behavioral trait. However, it does not disclose other aspects such as return values, edge cases, or any side effects. Since no annotations are provided, the description partially fulfills the transparency requirement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one sentence that conveys the core functionality. It is front-loaded with the most important information but could benefit from a bit more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (two string inputs) and the presence of an output schema (not shown), the description is minimally adequate. However, it lacks context on the output format, potential errors, and differentiation from similar sibling tools, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for both parameters ('First hash' and 'Second hash'). The description does not add any additional meaning beyond what the schema already provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares two hashes in constant time, specifying the action and resource. However, it does not differentiate from the sibling tool 'constant_time_compare', which likely serves a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, especially the sibling 'constant_time_compare'. There is no mention of typical use cases, prerequisites, or situations where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
complement_colorAInspect
Get the complementary color (opposite on color wheel).
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color to get complement of |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| complement | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries behavioral burden. It implies a simple read operation with no side effects. Could mention input validity or output format, but not necessary. Adequate for a simple function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One clear sentence, front-loaded with verb and resource. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has low complexity (1 param, simple operation) and output schema is present. Description fully covers the use case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers 100% with one parameter 'hex_color' described as 'Hex color to get complement of'. Description adds no extra meaning; baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool's purpose: 'Get the complementary color (opposite on color wheel).' It uses a specific verb ('Get') and resource ('complementary color') and distinguishes well from sibling color tools like 'analogous_colors' and 'blend_colors'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many sibling color tools (e.g., analogous_colors, triadic_colors), the description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
compound_interestCInspect
Calculate compound interest.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual interest rate (as percentage, e.g., 5 for 5%) | |
| time | Yes | Time in years | |
| principal | Yes | Initial principal | |
| compounds_per_year | No | Compounding frequency per year |
Output Schema
| Name | Required | Description |
|---|---|---|
| principal | Yes | |
| time_years | Yes | |
| final_amount | Yes | |
| rate_percent | Yes | |
| interest_earned | Yes | |
| compounds_per_year | Yes | |
| effective_annual_rate | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It fails to mention the formula, handling of defaults (e.g., compounds_per_year=12), or edge cases. Only states the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence), but it is too terse and lacks necessary detail for a 4-parameter tool. It is not well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and a relatively complex input schema, the description is incomplete. It does not explain the return value (output schema exists but unmentioned) or usage context, leaving gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The tool description adds no new meaning beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate compound interest.' clearly states the verb and resource, distinguishing it from siblings like simple_interest. However, it could be more specific about the formula or scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like simple_interest or future_value. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
constant_time_compareAInspect
Compare two strings in constant time (timing-safe).
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First string | |
| b | Yes | Second string |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | Yes | |
| equal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavior. It only mentions constant-time comparison but omits details like return type, case sensitivity, handling of blanks, or whether it returns boolean or integer. The output schema may exist but is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence (10 words) that gets straight to the point. No wasted words; efficiently conveys the core purpose and key feature.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (context signal), the description adequately distinguishes the tool from many sibling comparison tools via timing safety. However, it lacks details on return value and edge-case behavior, leaving some gaps for complex use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions ('First string', 'Second string'). The description adds the constant-time context but no additional parameter semantics. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: comparing two strings. The key differentiator of constant-time (timing-safe) is explicitly mentioned, distinguishing it from sibling comparison tools like 'compare', 'compare_2', and 'compare_decimals'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for security-sensitive operations (timing-safe) but does not explicitly state when to use or avoid this tool, nor does it reference alternatives. The context is adequate but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
containsCInspect
Check if text contains a substring.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to search in | |
| search | Yes | The text to search for | |
| case_sensitive | No | Case sensitive search |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| search | Yes | |
| contains | Yes | |
| case_sensitive | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description carries full burden. It does not mention return type (likely boolean), case sensitivity default behavior, or other behavioral traits beyond the basic check.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no wasted words. Could benefit from brief addition of output type or case sensitivity note without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Low complexity tool with complete schema and output schema (assumed). Still lacks explicit mention of return value or behavior details, making it minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema provides 100% coverage (text, search, case_sensitive). Description adds no additional meaning beyond what schema already describes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states verb 'Check' and resource 'text contains a substring', clearly conveying the tool's function. However, it does not differentiate from similar sibling tools like starts_with or ends_with.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., count_substring for counting occurrences, starts_with for prefix check). Agent must infer usage from name and description alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
contrast_ratioBInspect
Calculate contrast ratio between two colors (WCAG).
| Name | Required | Description | Default |
|---|---|---|---|
| color1 | Yes | First hex color | |
| color2 | Yes | Second hex color |
Output Schema
| Name | Required | Description |
|---|---|---|
| color1 | Yes | |
| color2 | Yes | |
| wcag_aa_large | Yes | |
| contrast_ratio | Yes | |
| wcag_aa_normal | Yes | |
| wcag_aaa_large | Yes | |
| wcag_aaa_normal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions WCAG but does not disclose behavioral traits such as rounding, handling of invalid hex codes, or whether the ratio is computed as defined by WCAG 2.1. With no annotations, the description provides insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with key action. Could include more context without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with output schema available, the description is adequate but could mention expected return value (e.g., ratio or pass/fail level). Still functional.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters described as hex colors. The description adds no additional semantic detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb (Calculate), a clear resource (contrast ratio), and specifies the standard (WCAG). It distinguishes from sibling color tools like hex_to_rgb or lighten_color.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other color tools (e.g., random_color, hex_to_hsl). No mention of prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_all_casesBInspect
Convert text to all case formats at once.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| conversions | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of disclosure. It states 'all case formats' but does not list which formats, nor any behavioral traits (e.g., non-destructive, return structure). Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, very concise. Could list example formats, but no waste. Efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Description covers the basic purpose. With output schema present, return values need not be explained. However, listing the case formats would improve completeness. Adequate but leaves some questions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter (text). The description 'Text to convert' adds little beyond the schema. Baseline 3 is appropriate given high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts text to all case formats at once, specifying verb (convert), resource (text), and scope (all case formats). It distinguishes well from sibling tools that convert to single cases.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when multiple case formats are needed, but lacks explicit guidance on when to use this over individual case converters (e.g., camel_case, kebab_case). No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_timestampBInspect
Convert Unix timestamp to date.
| Name | Required | Description | Default |
|---|---|---|---|
| timestamp | Yes | Unix timestamp (seconds) |
Output Schema
| Name | Required | Description |
|---|---|---|
| iso | Yes | |
| date | Yes | |
| time | Yes | |
| timestamp | Yes | |
| day_of_week | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It fails to specify the output format (e.g., string, date object) or timezone handling, leaving significant ambiguity. The minimal description does not compensate for missing annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) and front-loaded with the essential action. Every word is necessary with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and presence of an output schema, the description is adequate but incomplete. It does not clarify what 'date' means (e.g., string format) or if timezone is considered, leaving minor gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter description already clarifies it expects Unix timestamp in seconds. The tool description adds no additional meaning beyond the schema, earning the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool converts Unix timestamp to date using a specific verb and resource. However, it does not differentiate from sibling tools like convert_timestamp_ms or unix_to_datetime, which likely perform similar conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as convert_timestamp_ms for milliseconds or unix_to_datetime for different output formats. The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_timestamp_msBInspect
Convert Unix timestamp (milliseconds) to date.
| Name | Required | Description | Default |
|---|---|---|---|
| timestamp_ms | Yes | Unix timestamp (milliseconds) |
Output Schema
| Name | Required | Description |
|---|---|---|
| iso | Yes | |
| date | Yes | |
| time | Yes | |
| timestamp | Yes | |
| timestamp_ms | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully convey behavioral traits. It only states the conversion without addressing details like timezone handling, output format (though output schema exists), or edge cases (e.g., negative timestamps). This lack of transparency is a gap for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded and free of redundant or extraneous information. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with a documented schema and output schema, the description is mostly complete. It lacks information about timezone or output format, but these are covered by the output schema. Minor contextual improvements could be made.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'timestamp_ms' is fully described in the schema (100% coverage). The description adds no additional meaning about the parameter beyond what the schema already provides, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'Unix timestamp (milliseconds) to date'. It specifies the input unit (milliseconds), which helps differentiate from other timestamp conversion tools like 'convert_timestamp' or 'unix_to_datetime', though it does not explicitly compare to siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives such as 'convert_timestamp' or 'unix_to_datetime', nor does it mention any prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
convert_timezoneBInspect
Convert datetime between timezones.
| Name | Required | Description | Default |
|---|---|---|---|
| to_tz | No | Target timezone | EST |
| from_tz | No | Source timezone | UTC |
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| date | No | |
| time | No | |
| error | No | |
| original | No | |
| converted | No | |
| to_timezone | No | |
| from_timezone | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states 'Convert datetime between timezones' without mentioning DST handling, accepted timezone formats, or error conditions. The schema descriptions partially cover parameter intent but not behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. It is well-structured and directly states the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity of the tool, the existence of an output schema (not shown but present), and the schema covering parameters, the description is mostly complete. However, it lacks usage context that would be helpful given the many sibling time tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all three parameters (e.g., 'Datetime in ISO format'). The tool description adds no additional meaning beyond what the schema already provides, placing it at the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert datetime between timezones' uses a specific verb 'convert' and resource 'datetime between timezones', clearly distinguishing it from sibling tools like 'convert_timestamp' (which converts to Unix time) and 'timezone_offset' (which gets offset).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Sibling tools like 'convert_timestamp' and 'timezone_offset' exist for related but different tasks, but the description does not mention exclusions or preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cosAInspect
Calculate the cosine of an angle.
| Name | Required | Description | Default |
|---|---|---|---|
| angle | Yes | Angle in radians |
Output Schema
| Name | Required | Description |
|---|---|---|
| cos | Yes | |
| angle_radians | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure burden. It does not mention side effects, domain restrictions, or return values, but the schema covers the input unit (radians) and an output schema exists. The description is adequate but lacks explicit behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-front-loaded sentence of just 4 words, with no unnecessary information. Every word contributes to the purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical function with complete input schema and an output schema, the description is reasonably complete. It does not elaborate on edge cases or behavior, but the tool's simplicity reduces the need for extensive detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with the parameter 'angle' described as 'Angle in radians'. The description adds no additional meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate the cosine of an angle' clearly states the action (calculate) and the resource (cosine of an angle). It distinguishes from sibling tools like sin or tan by specifying the trigonometric function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context (calculating cosine) but does not explicitly state when to use this tool versus alternatives like sin or tan. However, for a standard math function, the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
count_all_charsBInspect
Count occurrences of each character in text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| digits | Yes | |
| spaces | Yes | |
| letters | Yes | |
| punctuation | Yes | |
| character_counts | Yes | |
| total_characters | Yes | |
| unique_characters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It does not disclose behaviors like case sensitivity, whitespace handling, or performance characteristics. Minimal transparency beyond the core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, description covers the basic operation. However, it could mention details like character set or edge cases (e.g., empty input).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers the single parameter 'text' fully (100% coverage). Description adds no extra meaning beyond the schema's 'The text to analyze'. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'count' and resource 'occurrences of each character in text'. It is specific and unambiguous, but does not differentiate from sibling tools like count_char or count_substring.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as count_char for a single character or count_substring for substrings. Lacks usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
count_charAInspect
Count occurrences of a character (e.g., how many 'r' in 'strawberry').
| Name | Required | Description | Default |
|---|---|---|---|
| char | Yes | Character to count | |
| text | Yes | The text to search in | |
| case_sensitive | No | Case sensitive counting |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| count | Yes | |
| character | Yes | |
| positions | Yes | |
| case_sensitive | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not mention behavioral traits such as case sensitivity (though the parameter case_sensitive exists) or handling of multi-character input. The example uses a lowercase character, which may suggest default behavior but is not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear, and efficient sentence. It front-loads the purpose and includes a useful example without excess words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool, the description is largely complete. It has an output schema (context notes), so return values are covered. However, brief guidance on the case_sensitive parameter or edge cases would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with all parameters described. The description adds no additional meaning beyond the schema, only an example. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('count occurrences of a character') and provides a concrete example ('how many 'r' in 'strawberry''). It distinguishes this tool from siblings like count_all_chars or count_substring by focusing on a single character.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage via the example but does not explicitly state when to use this tool versus alternatives like count_substring or count_all_chars. No when-not or context guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
count_digitsCInspect
Count the number of digits.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to count digits |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| digit_count | Yes | |
| digit_frequency | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description fails to disclose edge cases (e.g., zero, negative numbers, large integers) or clarify what qualifies as a digit; leaves agent guessing about behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at one sentence, but could include a few more details without harming brevity; still efficient for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and the tool is simple, the description is minimally adequate, but lacks critical behavioral context for robust agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with a clear parameter description ('Number to count digits'), so the tool description adds no extra meaning but is not deficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it counts digits, but lacks differentiation from sibling tools like sum_digits or count_char, and does not specify handling of negative signs or decimals.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as count_all_chars, sum_digits, or count_items; the description is too minimal to help an agent choose effectively.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
count_itemsCInspect
Count occurrences of each item.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| items | Yes | |
| total | Yes | |
| counts | Yes | |
| unique | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It fails to disclose that items are comma-separated, the split logic, or the output structure (e.g., a frequency map). Key behavioral details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence), but it is overly minimal, lacking essential details. It achieves conciseness at the expense of completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity and the presence of an output schema, the description still fails to clarify the input format (comma-separated) and the expected output. Compared to sibling tools, it is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema description 'Comma-separated items' already explains the parameter. The description adds no additional meaning beyond what the schema provides, so baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Count occurrences of each item' which gives a general verb+resource, but it is vague about what constitutes an 'item'. The input schema indicates comma-separated items, but the description does not clarify this, making it less specific than siblings like 'count_substring' or 'array_frequency'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'count_all_chars', 'count_substring', or 'array_frequency'. There is no indication of input format requirements or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
count_substringBInspect
Count occurrences of a substring.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to search in | |
| substring | Yes | Substring to count | |
| overlapping | No | Count overlapping occurrences | |
| case_sensitive | No | Case sensitive counting |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| count | Yes | |
| positions | Yes | |
| substring | Yes | |
| overlapping | Yes | |
| case_sensitive | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It does not mention that the tool supports overlapping and case-sensitive counting, nor does it describe edge cases (e.g., empty substring). The schema parameters cover these details, but the description adds no behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence) and front-loaded with the core purpose. Every word earns its place with no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a 4-parameter tool with an output schema, the description is minimal. It doesn't mention the output type or the configurable parameters (overlapping, case_sensitive). However, the output schema fills the return value gap, and the parameter descriptions in the schema provide necessary details, making the description adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter already described. The tool description adds no additional meaning or context for the parameters, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Count occurrences of a substring' clearly states the verb ('count') and resource ('occurrences of a substring'). It distinguishes from siblings like 'contains' (boolean) and 'count_all_chars' (character count), though it doesn't explicitly mention these distinctions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'contains', 'count_char', or 'find_all_matches'. The description only restates the obvious purpose without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
crc32_checksumCInspect
Calculate CRC32 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to checksum |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| crc32 | Yes | |
| crc32_int | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations and a terse description, the tool's behavior is minimally disclosed. There is no mention of side effects, performance characteristics, or required permissions, which leaves the agent uninformed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It is front-loaded and efficiently communicates the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema present), the description is adequate but fails to provide context about the CRC32 algorithm or its typical use cases, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a description for 'text' as 'Text to checksum'. The description adds no additional meaning beyond what the schema provides, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Calculate') and resource ('CRC32 checksum'), making the tool's purpose unambiguous. However, it does not differentiate from the sibling 'hash_crc32', which likely performs the same operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like 'hash_crc32' or other checksum tools. The description lacks context for appropriate usage or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cubeCInspect
Calculate the cube of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to cube |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It does not disclose that the tool is read-only, returns a number, or requires no special permissions. The minimal description adds no behavioral context beyond the obvious computation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately conveys the purpose. It is front-loaded and efficient, though slightly more detail could be added without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of output schema, the description is adequate. However, it fails to address the context of sibling tools and does not specify the return format, which could be inferred from schema but not explicitly stated.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the parameter. The description adds no extra meaning beyond what the schema provides; the parameter description 'Number to cube' already conveys the necessary info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the cube of a number, with a specific verb and resource. However, it does not distinguish from sibling tools like 'square', 'cube_root', or 'nth_cube', which are similar mathematical operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Given the many sibling math tools, a brief note on when to prefer 'cube' over 'square' or 'nth_cube' would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cube_rootAInspect
Calculate the cube root of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to find cube root of |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It states the operation succinctly but lacks additional behavioral details such as handling of negative numbers or precision. For a simple mathematical function, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no unnecessary words. It is appropriately front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of both a full input schema and an output schema, the description provides sufficient context. No additional details are necessary for an agent to understand or use this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the parameter has a description). The tool description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the cube root of a number, using a specific verb and resource. It distinguishes itself from siblings like square_root and nth_root, which are different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. No explicit context or exclusions are given, leaving the agent to infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cups_to_millilitersBInspect
Convert US cups to milliliters.
| Name | Required | Description | Default |
|---|---|---|---|
| cups | Yes | Volume in cups (US) |
Output Schema
| Name | Required | Description |
|---|---|---|
| cups_us | Yes | |
| milliliters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits like rounding behavior, handling of negative values, or precision limits. For a simple conversion, minimal disclosure is acceptable but still missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no unnecessary words, making it maximally concise and easy to process.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the description is sufficient for a straightforward conversion, it omits details about conversion precision, edge cases, or the assumption of US cups. Given the simplicity, it is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a well-described parameter. The description adds minimal value (specifying 'US cups') beyond the schema, meeting the baseline for a fully documented parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the specific resources 'US cups' and 'milliliters', distinguishing it from sibling conversion tools like 'milliliters_to_cups' or 'liters_to_gallons_us'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as when dealing with UK cups or other volume units. The description lacks explicit context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
current_timeAInspect
Get current time in specified timezone.
| Name | Required | Description | Default |
|---|---|---|---|
| timezone_name | No | Timezone name (e.g., UTC, EST, PST, JST) | UTC |
Output Schema
| Name | Required | Description |
|---|---|---|
| date | Yes | |
| time | Yes | |
| datetime | Yes | |
| timezone | Yes | |
| timestamp | Yes | |
| utc_offset | Yes | |
| day_of_week | Yes | |
| day_of_year | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states a safe read operation ('Get') without side effects, but does not disclose any potential behaviors like network dependency, caching, or error handling. However, the simplicity of the operation makes this minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence of 7 words, front-loading the purpose. No extraneous information, earning its place perfectly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 param, simple operation, output schema exists), the description is largely complete. It covers the core functionality and parameter. The only minor gap is no mention of return format, but the output schema likely addresses this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single parameter, including examples. The description adds the default value and examples, but the schema already provides a description. Baseline score of 3 is appropriate as the description adds modest context beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'current time in specified timezone', making the purpose immediately clear. It distinguishes from siblings like format_date or convert_timezone by focusing on retrieving current time, not converting or formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for use (get current time in a timezone) but does not explicitly state when not to use it or mention alternative tools. For example, it doesn't differentiate from timezone_offset or list_timezones, leaving the agent to infer usage without guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dad_jokeAInspect
Get a random dad joke.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| setup | Yes | |
| punchline | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose behavioral traits such as idempotency or safety. For a simple read-like tool, it is adequate but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, zero waste. Front-loaded and directly states the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an output schema, the description is sufficient. It could mention output format briefly, but not necessary due to schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. The description does not need to add parameter info; baseline for 0 parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool gets a random dad joke, a specific verb+resource. It distinguishes itself from siblings like random_trivia or random_text by being a dedicated dad joke generator.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives. The description does not mention when to choose this over other random generators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
daily_water_intakeCInspect
Calculate recommended daily water intake.
| Name | Required | Description | Default |
|---|---|---|---|
| weight_kg | Yes | Weight in kilograms | |
| activity_level | No | Activity level: low, moderate, high | moderate |
Output Schema
| Name | Required | Description |
|---|---|---|
| weight_kg | Yes | |
| glasses_250ml | Yes | |
| activity_level | Yes | |
| recommended_ml | Yes | |
| recommended_liters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, required permissions, or the nature of the calculation (e.g., deterministic, no external dependencies). The tool is a simple computation, but the description lacks transparency about its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence. However, it could be slightly expanded to include e.g., the formula basis (e.g., based on weight and activity level). But given the tool's simplicity, it is well-structured and not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown but indicated), so return value documentation exists. However, the description does not mention the output unit (e.g., milliliters, ounces) or the formula used. For a tool with two parameters and no nested objects, the description is minimally adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions (weight_kg with exclusiveMinimum, activity_level with default and enum-like description). The tool description does not add additional meaning beyond the schema. Since schema_coverage is high, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool calculates recommended daily water intake, specifying the verb 'calculate' and resource 'daily water intake'. However, it does not distinguish itself from sibling tools that perform other calculations, but the verb+resource is specific enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not mention when to use this tool, prerequisites, or alternatives among the many sibling tools. For example, it doesn't clarify if this is for general hydration or specific contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
darken_colorBInspect
Darken a color by a percentage.
| Name | Required | Description | Default |
|---|---|---|---|
| amount | No | Amount to darken (0-100) | |
| hex_color | Yes | Hex color to darken |
Output Schema
| Name | Required | Description |
|---|---|---|
| amount | Yes | |
| darkened | No | |
| original | Yes | |
| lightened | No | |
| saturated | No | |
| desaturated | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It only states 'Darken a color by a percentage' without explaining that the amount is an integer 0-100, how invalid hex colors are handled, or whether the result is a new hex string. This is minimal disclosure beyond what the input schema already provides.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately communicates the tool's purpose. It contains no unnecessary words or repetition, making it optimally front-loaded for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two well-documented parameters and an existing output schema (as indicated by context signals), the description is adequately complete. It could briefly mention the return type (e.g., 'Returns a new hex color') but is otherwise sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already has 100% description coverage for both parameters (hex_color and amount), including default, min, and max for amount. The description adds no additional meaning or context for these parameters, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Darken a color by a percentage' clearly specifies the verb (darken), the resource (a color), and the manner (by a percentage). It effectively distinguishes from sibling tools like lighten_color, saturate_color, and desaturate_color, making the tool's unique function immediately apparent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., lighten_color, saturate_color). An agent given only this description would not know that darken_color is specifically for reducing brightness, and might not consider the other color manipulation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
date_diffCInspect
Calculate difference between two dates.
| Name | Required | Description | Default |
|---|---|---|---|
| date1 | Yes | First date (ISO format) | |
| date2 | Yes | Second date (ISO format) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| date1 | No | |
| date2 | No | |
| error | No | |
| difference | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose important behaviors such as whether the difference is absolute or signed, what timezone handling applies, or if time components are included. The description is insufficient to predict tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it sacrifices clarity and completeness. It could be improved by specifying the output unit or behavior without adding much length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown), the description still fails to contextualize the tool's purpose among many date/time siblings. It does not explain what 'difference' means (e.g., number of days, milliseconds) or the return format, leaving the agent with uncertainty.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes parameters clearly (ISO format dates). The description adds no additional meaning beyond what the schema provides. Since schema coverage is 100%, baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Calculate difference between two dates' which is clear but vague—it doesn't specify the unit (e.g., days, hours) or distinguish from similar tools like time_difference or datetime_to_unix. It lacks specificity to differentiate among many date-related siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No mention of prerequisites, expected input format nuances, or what kind of difference is computed. Leaves the agent without context for appropriate invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
datetime_to_unixBInspect
Convert datetime to Unix timestamp.
| Name | Required | Description | Default |
|---|---|---|---|
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| datetime | No | |
| timestamp | No | |
| timestamp_ms | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states conversion without mentioning error handling, supported formats beyond ISO, timezone handling, or any side effects. The description is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that effectively communicates the core function. It is front-loaded with the action and resource, with no extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with an output schema (implied), the description is adequate but not complete. It lacks details on input format constraints, error behavior, and timezone assumptions. Given the complexity and schema coverage, a score of 3 reflects minimum viability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for the single parameter 'datetime_str', with a description stating 'Datetime in ISO format'. The tool description adds no additional meaning beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: converting datetime to Unix timestamp. It uses a specific verb ('Convert') and resource ('datetime to Unix timestamp'), and it distinguishes itself from sibling tools like unix_to_datetime which does the reverse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like convert_timestamp or date_to_timestamp. There is no mention of prerequisites, limitations, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
date_to_timestampBInspect
Convert date to Unix timestamp.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Date string (YYYY-MM-DD or ISO format) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| date | No | |
| error | No | |
| timestamp | No | |
| timestamp_ms | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It does not disclose timezone handling, error behavior, or output format (Unix timestamp in seconds). The description is too brief to compensate for missing annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is maximally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema present), the description is minimally adequate but lacks details on timezone handling or input format nuances, which are important for a date conversion tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action and resource: 'Convert date to Unix timestamp.' However, it does not differentiate from similar sibling tools like datetime_to_unix or convert_timestamp, which may cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., datetime_to_unix, convert_timestamp). No exclusions or context are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
day_of_yearBInspect
Get the day of year for a date.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Date (YYYY-MM-DD) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| date | No | |
| error | No | |
| day_of_year | No | |
| days_remaining | No | |
| percentage_of_year | No | |
| total_days_in_year | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It merely states the function without mentioning edge cases (e.g., invalid dates, leap years), return type, or potential errors. The output schema exists but the description adds no extra behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no extraneous words. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one parameter, output schema present), the description is minimally adequate. However, in the context of many sibling date tools, additional context like 'returns an integer 1-366' would improve completeness. The description is functional but could be more helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes the single parameter 'date' with format. The description does not add meaning beyond the schema (e.g., no extra constraints or examples). Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the day of year for a date.' uses a specific verb and resource, clearly stating what the tool does. It is unambiguous and distinguishes itself from sibling date tools like 'date_diff' or 'format_date'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. No context on when to use it, when not to, or any prerequisites (e.g., valid date format beyond what schema already specifies).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
days_in_monthCInspect
Get the number of days in a month.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Year | |
| month | Yes | Month (1-12) |
Output Schema
| Name | Required | Description |
|---|---|---|
| days | Yes | |
| year | Yes | |
| month | Yes | |
| month_name | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It only restates the basic purpose and fails to mention any side effects, leap year handling, or other behaviors beyond what the name implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 8 words, extremely concise. It is front-loaded with the key action and resource, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and existence of an output schema, the description is minimal. However, it lacks important context such as leap year handling and the difference from the sibling 'days_in_month_2'. This makes it incomplete for robust agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% parameter descriptions, so by baseline this is a 3. The tool description adds no additional meaning to the parameters beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the number of days in a month' clearly states the verb and resource. It is explicit about what the tool returns. However, it does not differentiate from the sibling tool 'days_in_month_2', which may have similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No mention of prerequisites or context. The presence of a sibling 'days_in_month_2' suggests a related but possibly different functionality, but no explanation is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
days_in_month_2CInspect
Get the number of days in a month.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Year | |
| month | Yes | Month (1-12) |
Output Schema
| Name | Required | Description |
|---|---|---|
| days | Yes | |
| year | Yes | |
| month | Yes | |
| month_name | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention any behavioral traits such as handling of leap years, error conditions for invalid dates, or whether it is deterministic. The description is too minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, it lacks front-loaded detail that would help the agent quickly understand the tool's purpose. It is not verbose, but it could be more informative without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is moderately complete. However, it does not address the existence of a similar sibling tool (`days_in_month`) or clarify nuances like leap year handling, which would be helpful for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptive parameter titles and descriptions. The tool's description adds no additional meaning beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get') and the resource ('number of days in a month'). It is a specific verb+resource combination. However, it does not differentiate from the sibling tool `days_in_month`, which likely has a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like `days_in_month` or `is_leap_year`. No context about prerequisites or use cases is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
decimal_to_binaryAInspect
Convert decimal to binary.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Decimal number |
Output Schema
| Name | Required | Description |
|---|---|---|
| binary | Yes | |
| decimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It does not disclose edge cases like negative numbers or output format. However, the input schema and expected output schema (not shown) likely provide supplemental information, making it minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is perfectly concise and structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no nested objects, output schema present), the description is complete enough to convey the tool's function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add extra meaning beyond what the schema provides for the 'number' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'decimal to binary'. It is specific and distinguishes from the sibling 'binary_to_decimal'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for decimal-to-binary conversion, and the sibling tools provide the reverse. No explicit alternatives or exclusions are given, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
decimal_to_dmsBInspect
Convert decimal degrees to DMS (degrees, minutes, seconds).
| Name | Required | Description | Default |
|---|---|---|---|
| decimal | Yes | Decimal degrees | |
| coordinate_type | Yes | Type: lat or lon |
Output Schema
| Name | Required | Description |
|---|---|---|
| dms | Yes | |
| decimal | Yes | |
| dms_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits, but it merely restates the conversion. It does not mention handling of invalid inputs, sign conventions, rounding, or output format, leaving the agent with insufficient behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's function without any extraneous words. It is front-loaded and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the minimal description, the tool is simple and the output schema likely covers return values. The description is adequate for this straightforward conversion, though it could briefly mention precision or sign handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described ('Decimal degrees' and 'Type: lat or lon'). The description adds no additional meaning beyond the schema, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'convert' and the resource 'decimal degrees to DMS (degrees, minutes, seconds)', making the tool's purpose obvious. While it does not explicitly distinguish from the sibling tool 'dms_to_decimal', the direction of conversion is implicit, earning a 4 rather than 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only states what the tool does but provides no guidance on when to use it versus alternatives like 'dms_to_decimal'. It lacks context for when this conversion is appropriate or any exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
decimal_to_hexadecimalBInspect
Convert decimal to hexadecimal.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Decimal number |
Output Schema
| Name | Required | Description |
|---|---|---|
| decimal | Yes | |
| hexadecimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It only states the conversion without detailing behavior (e.g., handling negative numbers, output format, or potential overflow). Since an output schema exists, some behavior may be implied but not explicitly disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and easy to parse. Every word is necessary and contributes to understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no enums, output schema present), the description is largely adequate. However, it could briefly mention that the output is a hexadecimal string, though the output schema may cover that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the parameter. The description adds no extra meaning beyond what is in the schema (e.g., 'Decimal number'). Baseline 3 applies as the description does not improve parameter clarity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the conversion from decimal to hexadecimal with a specific verb and resource. However, it does not differentiate from sibling tools like decimal_to_binary or decimal_to_octal, which perform similar conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks any context about prerequisites, edge cases, or suitable scenarios for conversion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
decimal_to_octalCInspect
Convert decimal to octal.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Decimal number |
Output Schema
| Name | Required | Description |
|---|---|---|
| octal | Yes | |
| decimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden, but it only states the conversion. It does not disclose input constraints (e.g., integer or floating point), output format, or side effects. The behavior is opaque beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it omits critical details about output and usage. It is adequately sized for the simplicity but lacks information that would not be verbose to include.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description is incomplete. It does not state the output type (e.g., octal string) or any constraints. Sibling tools with similar descriptions would confuse an agent without further context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the parameter 'number' as 'Decimal number' with 100% coverage. The description adds no new meaning beyond confirming the conversion. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the conversion from decimal to octal, but does not distinguish from sibling tools like decimal_to_binary or decimal_to_hexadecimal. The verb and resource are specific but lack differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as decimal_to_binary or hexadecimal_to_decimal. The description does not mention context, prerequisites, or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
deg_to_radAInspect
Convert degrees to radians.
| Name | Required | Description | Default |
|---|---|---|---|
| degrees | Yes | Angle in degrees |
Output Schema
| Name | Required | Description |
|---|---|---|
| degrees | Yes | |
| radians | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Simple operation with no annotations. The description does not disclose edge cases or rounding behavior, but for a straightforward math conversion it is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (5 words). Efficient, but could benefit from a brief mention of the formula or output unit without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter conversion with output schema, the description is sufficient. However, adding a note about the output being in radians would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. Description adds no extra meaning beyond the schema's 'Angle in degrees'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb and resource: 'Convert degrees to radians.' Distinguishes from sibling tools like rad_to_deg and other angle functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like rad_to_deg or trigonometric functions. The description is too minimal to provide context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
desaturate_colorAInspect
Decrease color saturation by a percentage.
| Name | Required | Description | Default |
|---|---|---|---|
| amount | No | Amount to desaturate (0-100) | |
| hex_color | Yes | Hex color to desaturate |
Output Schema
| Name | Required | Description |
|---|---|---|
| amount | Yes | |
| darkened | No | |
| original | Yes | |
| lightened | No | |
| saturated | No | |
| desaturated | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the operation but does not disclose traits such as pure function, return value format, or side effects. However, given the simplicity and non-destructive nature, the description is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that conveys the tool's purpose without any wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (two parameters, no nested objects) and the presence of an output schema, the description sufficiently explains what the tool does.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers both parameters with descriptions (100% coverage). The description adds 'by a percentage' which aligns with the amount parameter but provides no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Decrease color saturation by a percentage' clearly states the action (decrease) and the resource (color saturation), distinguishing it from sibling tools like 'saturate_color' and other color transformations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for desaturation but does not explicitly provide when-to-use or when-not-to-use guidance, nor does it mention alternatives like 'saturate_color' or 'grayscale_color'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
describe_dataCInspect
Get descriptive statistics for a dataset.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| q1 | Yes | |
| q3 | Yes | |
| iqr | Yes | |
| max | Yes | |
| min | Yes | |
| sum | Yes | |
| mean | Yes | |
| count | Yes | |
| range | Yes | |
| median | Yes | |
| std_dev | Yes | |
| variance | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose what specific statistics are computed, how edge cases (empty input, non-numeric values) are handled, or the format of the output. With no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at one sentence. While it could add more useful detail, it is not overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimal given the tool's complexity. Even with an output schema, listing which statistics are included would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the parameter as comma-separated numbers. The description adds no further meaning, so baseline 3 is appropriate given 100% coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool computes descriptive statistics for a dataset, which distinguishes it from sibling tools that compute individual statistics like calculate_mean or median.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this aggregated tool versus individual statistic tools, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
deslugifyBInspect
Convert a slug back to readable text.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Slug to convert back to text | |
| separator | No | Word separator in slug | - |
| capitalize | No | Capitalize words |
Output Schema
| Name | Required | Description |
|---|---|---|
| slug | Yes | |
| text | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states the general purpose without detailing edge cases, side effects, or behavior for empty slugs or custom separators. It does not add behavioral context beyond what the parameter schema implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately states the tool's function. There is no superfluous text, and it is efficiently front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity of the tool and that the input schema fully describes parameters (100% coverage) and an output schema exists, the description is adequate. However, it could be more complete by explicitly stating that it reverses the slugification process or indicating what constitutes 'readable text' (e.g., splitting by separator, capitalizing words).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add additional meaning beyond the schema; each parameter (slug, separator, capitalize) is already described in the input schema. The tool description merely restates the tool's overall purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert a slug back to readable text' clearly states the verb 'convert' and resource 'slug', implying the reverse operation of slugify. It distinguishes from siblings like 'slugify' by indicating the inverse direction, but does not explicitly contrast with other text transformation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are many text transformation tools among siblings (e.g., slugify, camel_case, etc.), and the description does not include context for when deslugify is appropriate or mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
destination_pointBInspect
Calculate destination point given start, bearing, and distance.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Starting latitude | |
| lon | Yes | Starting longitude | |
| unit | No | Unit: km or mi | km |
| bearing | Yes | Bearing in degrees | |
| distance | Yes | Distance to travel |
Output Schema
| Name | Required | Description |
|---|---|---|
| unit | Yes | |
| origin | Yes | |
| bearing | Yes | |
| distance | Yes | |
| destination | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits like the underlying spherical Earth model, unit assumptions, or error handling. The brief description adds little beyond the schema's parameter details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the core action and inputs, containing no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema likely documents return values, the description lacks context about accuracy, Earth model (spherical vs ellipsoidal), and practical usage scenarios. For a geospatial tool with 5 parameters and many siblings, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents parameters. The description adds minimal extra meaning by naming 'start, bearing, and distance', but does not clarify constraints like bearing range or distance units beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and the resource 'destination point', identifying the inputs. However, it does not differentiate from sibling tools like 'bounding_box' or 'haversine_distance', relying on the tool name for distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'distance' or 'calculate_bearing'. The description lacks context about its specific geospatial purpose, leaving the agent to infer usage from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
detect_caseBInspect
Detect the case style of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| detected_cases | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full responsibility for behavioral disclosure, but it only states 'detect the case style'. It does not mention what case styles are recognized, the format of the output, or any limitations (e.g., ambiguous input handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. However, it could be slightly expanded with additional context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. It explains what the tool does but lacks details on the possible return values or behavior for edge cases, which a more complete description would include.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with a description for 'text' ('Text to analyze'). The tool description adds no additional meaning beyond the schema, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: detecting the case style of text. It uses a specific verb 'detect' and a clear resource 'case style of text'. This distinguishes it from sibling tools that convert or manipulate case (e.g., camel_case, kebab_case).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives (like case conversion tools) or when not to use it. The agent receives no context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
digital_rootAInspect
Calculate the digital root (repeated digit sum until single digit).
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to calculate digital root for |
Output Schema
| Name | Required | Description |
|---|---|---|
| steps | Yes | |
| number | Yes | |
| iterations | Yes | |
| digital_root | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description accurately describes a pure, deterministic calculation. It does not mention edge cases, but the schema's minimum constraint on input covers non-negativity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, precise sentence with no wasted words. The parenthetical explanation efficiently clarifies the algorithm.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description is adequate. Could mention the result range (0-9) but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters, and the description adds the concept of 'repeated digit sum until single digit', which is not present in the schema's parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool calculates the digital root and explains the method (repeated digit sum until single digit). It clearly distinguishes from siblings like 'sum_digits' which sums digits once.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like 'sum_digits'. The usage is implied for digital root calculation but lacks comparative context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
distanceBInspect
Calculate Euclidean distance between two points.
| Name | Required | Description | Default |
|---|---|---|---|
| x1 | Yes | X coordinate of point 1 | |
| x2 | Yes | X coordinate of point 2 | |
| y1 | Yes | Y coordinate of point 1 | |
| y2 | Yes | Y coordinate of point 2 |
Output Schema
| Name | Required | Description |
|---|---|---|
| point1 | Yes | |
| point2 | Yes | |
| distance | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does not disclose any behavioral traits such as precision, handling of invalid input, or side effects. This is a significant gap for a math tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence with no waste, but it is extremely minimal. Still, it is concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is adequate but lacks any context on precision, edge cases, or comparison to similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions for each parameter, so baseline 3. The description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Calculate' and the resource 'Euclidean distance between two points', which is specific and distinguishes it from siblings like haversine_distance (spherical distance).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no when-to-use or when-not-to-use guidance. It does not differentiate from similar tools like hypotenuse or haversine_distance, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
divideBInspect
Divide a by b.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | Dividend (number to be divided) | |
| b | Yes | Divisor (number to divide by) |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | No | |
| b | No | |
| code | No | |
| error | No | |
| result | No | |
| remainder | No | |
| integer_quotient | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the operation but fails to disclose important behavior such as handling of division by zero, precision, or return value specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words. It is concise and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple arithmetic tool, the description is minimally adequate but lacks details on edge cases (e.g., division by zero) and does not explain the return format. Given the output schema exists but is not described, completeness is average.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The tool description adds no additional semantic value beyond what the schema already provides for the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Divide a by b.' is a specific verb+resource that clearly states the operation. It distinguishes itself from sibling tools like add, subtract, and multiply.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives such as modulo or other arithmetic operations. There is no mention of prerequisites or contextual conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
dms_to_decimalBInspect
Convert DMS (degrees, minutes, seconds) to decimal degrees.
| Name | Required | Description | Default |
|---|---|---|---|
| degrees | Yes | Degrees | |
| minutes | Yes | Minutes | |
| seconds | Yes | Seconds | |
| direction | Yes | Direction: N, S, E, or W |
Output Schema
| Name | Required | Description |
|---|---|---|
| dms | Yes | |
| decimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the basic conversion without disclosing any behavioral traits such as input validation (e.g., direction must be N/S/E/W), handling of invalid seconds/minutes, or what happens if direction is missing. The agent lacks knowledge of constraints and error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core purpose without any waste. It is front-loaded and appropriate for such a straightforward tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema (not shown but referenced), the description is minimally adequate. However, it lacks any contextual details such as edge cases (e.g., negative degrees) or validation behavior, making it somewhat incomplete for an agent to fully understand the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, meaning all parameters are described in the input schema. The description adds no additional meaning beyond what the schema already provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts DMS (degrees, minutes, seconds) to decimal degrees. It uses a specific verb 'Convert' and a specific resource, and it distinguishes itself from sibling tools like 'decimal_to_dms' which does the reverse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of the sibling tool 'decimal_to_dms' or any context for when this conversion is appropriate. The agent is left without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
echoAInspect
Echo back the message. For testing.
| Name | Required | Description | Default |
|---|---|---|---|
| message | Yes | Message to echo back |
Output Schema
| Name | Required | Description |
|---|---|---|
| echo | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description directly states the behavior: echo back the message. With no annotations, it fully discloses the tool's action, and there is no hidden complexity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. Front-loaded with the core action, and the testing purpose is added succinctly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple echo tool with an output schema, the description is complete. No need to explain return values as the output schema covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter 'message' is already well-described in the schema. The description adds no additional semantic meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool echoes back a message and is for testing. It uses a specific verb 'Echo' and resource 'message', distinguishing it from siblings like 'hello_world' or other testing tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'for testing', providing context. However, it does not explicitly state when not to use or mention alternative tools, so it lacks full usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
empty_arrayAInspect
Returns an empty array.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fully discloses the behavior—it returns an empty array. No annotations exist, but the description adequately covers the tool's effect and lack of side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, precise sentence with no wasted words. Perfectly front-loaded and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and an output schema present, the description is complete. It explains the single output behavior sufficiently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, and schema coverage is 100%. With zero params, the description adds no extra meaning, but the baseline of 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Returns an empty array' clearly states the function with a specific verb ('Returns') and object ('empty array'). It distinguishes from sibling tools that manipulate or create non-empty arrays.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives like array_fill or array_repeat. Usage is implied: when an empty array is needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
empty_objectAInspect
Returns an empty object.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description fully discloses behavior: it returns an empty object. Since there are no annotations and the tool is simple (no parameters, no side effects), no further transparency is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no waste. Front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and an existing output schema, the description completely specifies the tool's behavior. No additional details are necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema description coverage is 100%. The description adds no param info, which is acceptable per baseline for 0 parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Returns') and the resource ('empty object'), distinguishing it from siblings like empty_array or null.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as empty_array or null. With many sibling tools, a brief usage note would improve agent selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
end_of_periodCInspect
Get the end of a time period.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Period: year, month, week, day, hour | day |
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| end | No | |
| error | No | |
| period | No | |
| original | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden but only states 'Get the end of a time period' without disclosing return behavior, edge cases, or assumptions (e.g., inclusive/exclusive, timezone handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence but is overly terse, omitting important details that would make it more helpful. It is concise but not optimally structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description should at least hint at the return value. It does not, leaving the agent without behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds no additional meaning beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the end of a time period' clearly states a verb and resource, and the sibling 'start_of_period' provides contrast. However, it lacks specificity about what 'end' means exactly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like 'start_of_period'. The description does not mention any exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ends_withAInspect
Check if text ends with a suffix.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to check | |
| suffix | Yes | The suffix to look for |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| suffix | Yes | |
| ends_with | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. While it accurately describes the operation, it does not mention case sensitivity, trimming, or edge cases, which are typical for string operations. For a simple tool, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, precisely front-loading the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, complete schema, and presence of an output schema, the description provides sufficient information for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description does not add meaning beyond the parameter names and schema descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if text ends with a suffix.' uses a specific verb ('check') and resource ('text ends with a suffix'), clearly distinguishing the tool from siblings like 'starts_with' and 'contains'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for checking suffixes, but does not explicitly state when to use or when not to use alternatives. However, the context is clear enough for an agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
escape_patternBInspect
Escape special regex characters in text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to escape for use in regex |
Output Schema
| Name | Required | Description |
|---|---|---|
| escaped | Yes | |
| original | Yes | |
| special_chars_escaped | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden of behavioral disclosure. It only states the core function without mentioning return format, edge cases, or side effects. For a simple utility, the description is too sparse to fully inform an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is perfectly front-loaded with the action and resource. Every word contributes meaning; there is no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and the output schema likely exists (not shown), the description does not mention the return value or any expected behavior. It is adequate for a basic utility but misses the opportunity to clarify output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (only one parameter 'text' with a clear description). The tool description adds no extra meaning beyond what the schema already provides. Baseline 3 applies since the schema carries the load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('escape') and resource ('special regex characters in text'), providing a specific verb+resource combination. However, it does not differentiate from sibling regex tools like regex_replace or regex_split, leaving some ambiguity about when to use this tool over others.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or specific contexts where escaping is needed, making it hard for an agent to decide between this and similar string escaping tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
estimate_body_fatCInspect
Estimate body fat percentage using US Navy method.
| Name | Required | Description | Default |
|---|---|---|---|
| sex | Yes | Sex: male or female | |
| hip_cm | No | Hip circumference in cm (required for females) | |
| neck_cm | Yes | Neck circumference in cm | |
| waist_cm | Yes | Waist circumference in cm | |
| height_cm | Yes | Height in cm |
Output Schema
| Name | Required | Description |
|---|---|---|
| sex | No | |
| code | No | |
| error | No | |
| hip_cm | No | |
| neck_cm | No | |
| category | No | |
| waist_cm | No | |
| height_cm | No | |
| body_fat_percent | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only names the method and fails to disclose whether the tool is read-only, requires specific units, or has limitations (e.g., accuracy, gender-specific requirements).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the core purpose. However, it is slightly underspecified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits crucial context: units must be in cm, hip_cm is conditionally required for females, and the formula assumes adult non-athlete populations. This leaves the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds no extra meaning beyond the method name, resulting in no added value for parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates body fat percentage using a specific method (US Navy method), indicating its unique purpose among health-related tools like calculate_bmi and ideal_weight.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as calculate_bmi, calculate_bmr, or ideal_weight. The description lacks context on appropriate scenarios or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
estimate_hash_timeBInspect
Estimate time to crack a password using brute force.
| Name | Required | Description | Default |
|---|---|---|---|
| password | Yes | Password to estimate crack time for |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| crack_times | No | |
| charset_size | No | |
| password_length | No | |
| total_combinations | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It mentions 'brute force' but does not disclose assumptions (e.g., hash type, GPU speed) or the output format (time unit). The behavior is under-specified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no redundant words. It is front-loaded and efficient, though it could include more context without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description might be adequate, but it omits details like the return format or units of time. The tool is simple, but more context would help, especially among many similar sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter, so the baseline is 3. The description adds 'using brute force', which clarifies intent but does not significantly enhance parameter understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'estimate', the resource 'time to crack a password', and the method 'using brute force'. This distinguishes it from sibling tools like analyze_password or identify_hash.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., identify_hash, verify_hash). The description does not mention prerequisites or limitations, such as the assumed hash algorithm or hardware speed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
expBInspect
Calculate e raised to the power of number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Exponent |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It only states the operation but does not mention input domain, potential overflow, or output type. The return format is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it could be slightly expanded to include context (e.g., 'natural exponentiation') without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple math function with an output schema, the description is minimally adequate. However, it lacks edge-case information (e.g., handling of large exponents) that would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'number' described as 'Exponent'. The description adds no further meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate e raised to the power of number' clearly states the verb 'calculate' and the resource 'e raised to the power', distinguishing it from siblings like 'power', 'square', and 'cube'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'power' (general exponentiation) or other exponential functions. The description does not mention context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
expand_cidrCInspect
Expand a CIDR to list of individual IPs.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum IPs to return | |
| network | Yes | Network in CIDR notation |
Output Schema
| Name | Required | Description |
|---|---|---|
| ips | No | |
| error | No | |
| network | No | |
| returned | No | |
| truncated | No | |
| total_addresses | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It fails to mention the limit parameter's effect or what happens if the CIDR exceeds the limit (max 1024 IPs). The behavior for large networks is unclear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with no wasted words. It is front-loaded and easy to parse, though it could benefit from additional context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits important behavioral details (e.g., limit enforcement, return format). For a tool with potential large outputs, significant gaps remain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented in the schema. The description adds minimal value beyond the schema, but the schema itself is clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Expand a CIDR') and the result ('list of individual IPs'), providing a specific verb-resource combination. It distinguishes the tool from other CIDR tools like cidr_info or cidr_to_netmask, but does so implicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., ip_in_network, subnet_calculator). No prerequisites or context for appropriate usage is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_domainBInspect
Extract domain from a URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to extract domain from | |
| include_subdomain | No | Include subdomain in result |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| domain | Yes | |
| hostname | Yes | |
| subdomain | No | |
| full_domain | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the basic operation, omitting details like error handling for invalid URLs, whether the scheme is stripped, or how the include_subdomain parameter affects output. The agent lacks key behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence. No wasted words. Efficiently communicates the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, an output schema exists (not shown), and both parameters are documented in the schema, the description is adequate but minimally complete. It lacks any usage context or behavioral guarantees, so it is not fully complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters described. The description adds no extra meaning beyond the schema—e.g., it does not explain the effect of include_subdomain or the default value. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Extract domain from a URL' clearly states the verb (extract) and resource (domain). However, it does not explicitly differentiate from sibling tools like parse_url, which might also extract domain components. Slight ambiguity reduces from 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., parse_url, extract_urls) or when to use include_subdomain parameter. The description provides zero context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_emailsBInspect
Extract all email addresses from text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to extract from |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| emails | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as performance, limitations (e.g., handling of malformed emails), or side effects. It relies solely on the basic function description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is concise and to the point, achieving clarity without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description is largely complete. It could briefly mention the return format (array of emails), but the output schema likely covers that. Slight room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'text' with a description. Schema coverage is 100%, so the description adds no additional meaning beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (extract), the object (email addresses), and the source (from text). It is specific and unambiguous, distinguishing it from sibling tools like 'extract_domain' or 'extract_numbers'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool, when not to, or what alternatives exist. For example, it does not mention that this tool only extracts email addresses and not other patterns, or that it might not handle all edge cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_groupsCInspect
Extract capture groups from a pattern match.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to search | |
| pattern | Yes | Pattern with capture groups |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | No | |
| error | No | |
| groups | No | |
| matched | No | |
| pattern | Yes | |
| full_match | No | |
| named_groups | No | |
| valid_pattern | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It only states the purpose without describing behavior such as whether it returns first match or all matches, support for named groups, or behavior on no match. Very minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, highly concise with no wasted words. However, it is so brief that it sacrifices completeness. The structure is front-loaded but lacks necessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, the description might be sufficient for a simple extraction tool. However, it lacks details on match behavior and output format. Minimal but functional for a low-complexity tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add any parameter semantics beyond what's in the schema. Parameters are well described in schema, so this is adequate but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Extract' and resource 'capture groups' from a 'pattern match', indicating regex capture group extraction. It distinguishes from siblings like test_pattern (boolean match) and find_all_matches (all matches), though it doesn't explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like find_all_matches or regex_replace. Sibling tools are not referenced, and no context for when extraction of groups is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_keywordsCInspect
Extract keywords from text based on frequency.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to extract keywords from | |
| top_n | No | Number of keywords |
Output Schema
| Name | Required | Description |
|---|---|---|
| keywords | Yes | Top keywords ranked by frequency |
| total_words | Yes | Total word count (excluding stop words filter) |
| unique_words | Yes | Number of unique words |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only mentions 'based on frequency', leaving out details like stop word handling, case sensitivity, stemming, or output format. The presence of an output schema is not leveraged in the description. This lacks necessary transparency for a text processing tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at one sentence, but it is too brief to be considered well-structured. While every word earns its place, the lack of additional sentences for context or examples reduces its effectiveness. It is not verbose but is under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of keyword extraction and the presence of many sibling text tools, the description is incomplete. It does not explain the algorithm, stop words, or output structure. The output schema exists but is not referenced, leaving the agent without critical operational context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema documents both parameters (text and top_n). The description adds no extra meaning or context beyond what the schema already provides. Baseline is appropriate as the description does not enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: extracting keywords from text using a frequency-based approach. It identifies the specific verb 'Extract' and the resource 'keywords', distinguishing it from sibling tools like extract_emails or extract_urls. However, it could be more explicit about extracting the most frequent words.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like basic_sentiment or other text analysis tools. It does not mention exclusions, prerequisites, or context. The single sentence implies usage for frequency-based keyword extraction but offers no comparative advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_numbersBInspect
Extract all numbers from text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to extract from |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry the full burden. It fails to disclose important details like what constitutes a 'number' (e.g., integers, decimals, negatives) or behavior for edge cases (e.g., numbers within words).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no wasted words. Could be slightly more descriptive without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and that an output schema likely clarifies the return format, the description is nearly complete. However, it lacks specifics on number types.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema's parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Extract all numbers from text.' clearly states the verb (extract) and resource (numbers), distinguishing it from sibling tools like extract_domain or extract_urls.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There is no mention of scenarios, exclusions, or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
extract_urlsBInspect
Extract all URLs from text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to extract from |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| urls | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description only states the basic action. It does not disclose how URLs are extracted (e.g., format, handling of relative URLs, encoding), leaving behavioral details unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is a single, clear sentence. It is efficient but could benefit from slight expansion for structure and key details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one required parameter and an output schema, but the description does not mention output format or edge cases. Adequate for a straightforward tool but lacks completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter described, but the description adds no additional meaning beyond the schema's parameter description. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool extracts all URLs from text, using a specific verb (extract) and resource (URLs). It distinguishes itself from sibling tools like extract_domain or extract_emails.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like extract_domain or extract_emails. Lacks context on prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
factorialAInspect
Calculate the factorial of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number (0-170) |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| factorial | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits beyond the operation itself. It is adequate for a simple mathematical function but lacks details like what the return value is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, zero waste, and front-loaded with the verb and object.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite its brevity, the description is sufficient for a simple one-parameter tool with an output schema. It does not explain edge cases like factorial of 0, but that is common knowledge.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (parameter 'number' described), and the tool description adds no additional meaning beyond the schema. Baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate the factorial of a number' uses a specific verb and resource, clearly distinguishing it from siblings like absolute_value or fibonacci.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternative mathematical tools like fibonacci or prime_factors. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fahrenheit_to_celsiusBInspect
Convert Fahrenheit to Celsius.
| Name | Required | Description | Default |
|---|---|---|---|
| fahrenheit | Yes | Temperature in Fahrenheit |
Output Schema
| Name | Required | Description |
|---|---|---|
| celsius | Yes | |
| fahrenheit | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention any behavioral traits like rounding behavior, precision, or error handling for invalid inputs, which is insufficient for a complete understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous content. It is concise and front-loaded with the core functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool is a straightforward conversion with an output schema likely documenting return values, the description is reasonably complete. However, it could mention output format or precision for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (one parameter with description 'Temperature in Fahrenheit'). The description adds no extra meaning beyond the schema, so it is adequate but not enhanced.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert Fahrenheit to Celsius' clearly states the verb (Convert) and resource (Fahrenheit to Celsius), making the tool's purpose unambiguous. It is specific and distinguishes itself from sibling conversion tools like celsius_to_fahrenheit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as celsius_to_fahrenheit or other temperature conversions. The description lacks explicit context for use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
false_endpointAInspect
Returns false.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The tool has no parameters and returns a constant boolean false. The description accurately captures all behavior. Since there are no side effects or hidden behaviors, the minimal description is fully transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two words, perfectly concise for the tool's simplicity. Every word earns its place; there is no unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and an output schema (not shown but indicated), the description is nearly complete. It could explicitly state 'boolean' but the name implies the return type. For such a simple tool, it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the baseline score is 4. The description adds nothing about parameters, which is acceptable because none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Returns false.' clearly states the output of the tool. It is specific and directly indicates the result. However, it does not distinguish from the sibling 'true_endpoint' or provide additional context, but the name itself is also descriptive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not mention when to use this tool versus alternatives like 'true_endpoint' or any other tool. There is no context for when returning false is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
feet_to_metersAInspect
Convert feet to meters.
| Name | Required | Description | Default |
|---|---|---|---|
| feet | Yes | Length in feet |
Output Schema
| Name | Required | Description |
|---|---|---|
| feet | Yes | |
| meters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states a simple conversion, implying deterministic and non-destructive behavior. However, it lacks any additional behavioral context (e.g., precision, side effects).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one front-loaded sentence and no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter conversion tool with an output schema, the description is adequate but minimal. It could mention units or that input is in feet and output in meters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add meaning beyond the schema, which already states 'Length in feet'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert feet to meters' clearly states the verb (convert) and resource (feet to meters). It is specific and distinguishes this tool from sibling tools like meters_to_feet, centimeters_to_inches, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives. Given the many sibling conversion tools, explicit when/when-not would be helpful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fibonacciBInspect
Get the nth Fibonacci number.
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | Position in sequence (0-1000) |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | |
| fibonacci | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It only states the operation without any details on performance, edge cases, or state changes. It neither confirms nor denies destructive or read-only nature, leaving ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 6 words, front-loaded with the core purpose. There is no fluff or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical function with a well-defined schema and presumably clear output, the description is adequate. The presence of an output schema reduces the need to describe return values. Missing a clear definition of the Fibonacci sequence (e.g., F0=0, F1=1) but not critical for most agents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents the parameter 'n' with a description ('Position in sequence (0-1000)') and constraints. The description adds the context 'nth Fibonacci number' but does not significantly enhance understanding beyond the schema. Baseline is 3 given 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the nth Fibonacci number,' which is specific about the verb and resource. It distinguishes from siblings like 'factorial' or 'nth_prime' by naming 'Fibonacci.' However, it does not clarify the base cases (F0=0, F1=1), which could aid precision.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'factorial' or 'nth_prime.' An AI agent would have no context about preferred usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
file_checksum_guideAInspect
Get command-line instructions for file checksums.
| Name | Required | Description | Default |
|---|---|---|---|
| algorithm | No | Algorithm: md5, sha1, sha256, sha512 | sha256 |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| commands | No | |
| algorithm | No | |
| available | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description solely states it provides instructions, not computes hashes. This is transparent but minimal, lacking details on what the output looks like or any side effects. It does not contradict annotations (none exist).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is appropriately front-loaded and efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but confirmed), the description is sufficiently complete for a simple guide tool. However, it could be slightly richer by mentioning the default algorithm or the format of instructions (e.g., for Unix/macOS/Windows).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'algorithm' has full schema coverage (100%), with the schema already describing it as 'Algorithm: md5, sha1, sha256, sha512'. The tool description adds no additional meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get command-line instructions for file checksums' uses a specific verb ('Get') and resource ('command-line instructions for file checksums'), clearly distinguishing it from sibling hash computation tools like hash_md5 or hash_sha1, which compute hashes rather than providing usage instructions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining command-line checksum instructions but provides no explicit guidance on when to use this tool versus alternative hash tools. It does not mention when not to use it or mention any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
filename_safeCInspect
Convert a string to a safe filename.
| Name | Required | Description | Default |
|---|---|---|---|
| filename | Yes | Filename to sanitize | |
| max_length | No | Maximum filename length | |
| replacement | No | Character to replace invalid chars with | _ |
Output Schema
| Name | Required | Description |
|---|---|---|
| safe | Yes | |
| original | Yes | |
| is_reserved_name | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It only states the conversion goal without explaining what makes a filename 'safe' (e.g., character removal, truncation, replacement behavior). The schema hints at parameters but the description adds no behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words, but it lacks any structure or breakdown of behavior. It is minimal but not necessarily concise in a helpful way, as important details are omitted.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and an output schema, the description should explain the transformation rules for a safe filename. It fails to address what invalid characters are, default behaviors, or edge cases, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters, setting a baseline of 3. The tool description adds no additional meaning beyond what the schema already provides, such as clarifying the effect of 'replacement' or 'max_length' on safety.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'convert' and resource 'string to a safe filename', indicating a specific purpose. However, it does not differentiate from sibling tools like 'slugify' or 'sanitize' that may also produce safe strings, lacking full distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives. Siblings include many string manipulation tools, but the description offers no context for selection, leaving the agent without usage boundaries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_all_matchesBInspect
Find all matches of a pattern in text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to search | |
| flags | No | Flags: i=ignore case, m=multiline, s=dotall | |
| pattern | Yes | Regular expression pattern |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | No | |
| count | No | |
| error | No | |
| matches | No | |
| pattern | Yes | |
| valid_pattern | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses that it finds all matches but doesn't detail return format (e.g., list of matched strings, with positions). Assumes regex behavior, but no mention of default flags or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with action. Efficient but could be more structured with additional context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, description doesn't need to explain return values, but lacks context about global matching behavior, overlapping matches, or performance considerations. Adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and description adds no additional meaning beyond what the schema already provides for text, pattern, and flags. Baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it finds all matches of a pattern in text, with a specific verb and resource. Distinguishes from siblings like test_pattern (boolean) and extract_groups (groups) by focusing on all matches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., test_pattern, regex_replace). No mention of prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fizzbuzzCInspect
The classic FizzBuzz. Enterprise-grade.
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | Number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes | |
| divisible_by_3 | Yes | |
| divisible_by_5 | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavior. It does not mention that the tool returns a string, how FizzBuzz logic works, or edge cases (n=3,5,15, etc.). The description is too brief to be transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short but at the expense of clarity. It fails to adequately describe the tool's function. Conciseness should not sacrifice informativeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Even though an output schema exists, the description lacks essential details about the tool's behavior. For a tool with a single parameter and no annotations, the description is insufficient to fully understand its operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'n' described as 'Number to check'. The description adds no additional meaning beyond the schema, but the schema itself is clear. Baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description references 'classic FizzBuzz', which is a well-known programming problem, so the purpose is implied. However, it does not explicitly state what the tool returns (e.g., string representation of FizzBuzz numbers). The 'Enterprise-grade' quip adds no clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'is_divisible' or other numeric tools. No exclusions or prerequisites mentioned. The sibling list includes many related tools, making this gap significant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flatten_arrayBInspect
Flatten a nested array.
| Name | Required | Description | Default |
|---|---|---|---|
| json_array | Yes | Nested JSON array to flatten |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| original | No | |
| flattened | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not specify whether flattening is shallow or deep, how nested arrays are handled, or any edge cases (e.g., empty arrays). This is a significant gap for a transformation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded. It is efficient but borders on under-specification due to lack of depth.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (array flattening) and the presence of an output schema, the description is insufficient. It does not explain return format, error conditions, or depth of flattening, making it incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the parameter 'json_array' is clearly described as a 'Nested JSON array to flatten'. The tool description does not add additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Flatten a nested array' uses a specific verb and resource, clearly stating the tool's function. It is distinct from sibling tools like array_compact and array_dedupe, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., array_compact, array_dedupe). There is no mention of context, prerequisites, or exclusions, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flatten_jsonCInspect
Flatten a nested JSON object.
| Name | Required | Description | Default |
|---|---|---|---|
| separator | No | Key separator | . |
| json_string | Yes | JSON string to flatten |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | No | |
| flattened | No | |
| key_count | No | |
| original_depth | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is minimal and does not disclose behavioral traits such as how deeply nested structures are handled, treatment of arrays, or error handling. With no annotations to fall back on, this description carries too little information about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but front-loads the main idea. However, it could be more informative without being verbose, such as mentioning the default separator or output format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. However, it lacks context about edge cases, and with a direct sibling 'unflatten_json', more detail would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds no meaning beyond what the schema provides, such as how the 'separator' affects flattening. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('flatten') and the resource ('nested JSON object'), making the purpose immediately understandable. However, it does not explicitly distinguish from the sibling 'unflatten_json' or other JSON manipulation tools, so it loses one point.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'json_minify', 'json_prettify', or 'unflatten_json'. The agent must infer usage from the name alone, which is insufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
flip_coinCInspect
Flip a coin.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of flips |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| flips | No | |
| heads | No | |
| tails | No | |
| result | No | |
| heads_percent | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description gives no information beyond the name. It does not disclose that the tool returns a random result (e.g., 'heads' or 'tails'), nor any behavioral traits. With no annotations, this is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise but under-specified. It lacks helpful details that are essential for a tool among many siblings. It is not merely concise; it is incomplete.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity and no required parameters, the description should at least explain the output. It fails to mention the random nature or return format, making it inadequate for proper selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'count' has a clear schema description ('Number of flips') and 100% coverage. The tool description adds no extra meaning, but the schema is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Flip a coin' clearly states the verb and resource, but it fails to differentiate from sibling tools like random_coin or random_boolean. The purpose is understood but not unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool instead of alternatives. Among many random generators, there is no context to help the agent choose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
floorBInspect
Round down to nearest integer.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to floor |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description does not disclose behavior for negative numbers (e.g., floor(-1.5) = -2) or other edge cases. While the name is standard, the description should include such details for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. It is appropriately front-loaded and concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description is adequate but could mention the return type (integer) or behavior for negative numbers. Output schema exists, so not required but helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter described as 'Number to floor' in the schema. The description adds no additional meaning beyond the schema, so baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Round down to nearest integer.' The verb 'Round down' and resource 'nearest integer' are specific and distinguish it from siblings like 'ceil' (round up) and 'round_number' (round to nearest).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. For a simple math function, usage is implied but no context is given for edge cases or comparisons with similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_bytesBInspect
Format bytes to human-readable size.
| Name | Required | Description | Default |
|---|---|---|---|
| binary | No | Use binary (1024) or decimal (1000) units | |
| bytes_value | Yes | Size in bytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| unit | Yes | |
| bytes | Yes | |
| value | Yes | |
| system | Yes | |
| formatted | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Lacks details on return format, behavior for edge cases (e.g., zero bytes, large values), or any side effects. No annotations provide additional behavioral cues.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, concise sentence that directly states the tool's purpose. No superfluous words or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple formatting tool, especially with an output schema present. However, could mention output format or units to be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers both parameters with descriptions. The description adds no additional meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it formats bytes to human-readable size. However, it does not differentiate from sibling tool 'bytes_to_human', which likely has similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'bytes_to_human'. No exclusion criteria or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_credit_cardBInspect
Format a credit card number with spaces.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Credit card number |
Output Schema
| Name | Required | Description |
|---|---|---|
| input | Yes | |
| masked | Yes | |
| card_type | Yes | |
| formatted | Yes | |
| last_four | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey all behavioral traits. It only states the formatting action but omits details like input sanitization (e.g., stripping non-digit characters), output format (grouping pattern), error handling for invalid inputs, or side effects. This is minimal for a safe, read-only tool but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the tool's purpose without redundant or extraneous information. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple formatting tool with one parameter and likely a straightforward output (formatted number), the description is adequate. However, it could be enhanced by noting the expected output format or behavior with non-digit inputs, making it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter described). The description adds no extra meaning beyond what the schema provides ('Credit card number'). Baseline 3 is appropriate as the schema already documents the parameter sufficiently.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Format a credit card number with spaces' clearly states the verb (format) and the resource (credit card number), specifying the action (adding spaces). It distinguishes from sibling tools like validate_credit_card or random_credit_card by focusing on formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., validate_credit_card for validation, format_phone for similar formatting). There are no prerequisites or exclusion criteria mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_currencyCInspect
Format an amount as currency.
| Name | Required | Description | Default |
|---|---|---|---|
| amount | Yes | Amount to format | |
| locale | No | Locale for formatting | en-US |
| currency | No | Currency code (USD, EUR, GBP, etc.) | USD |
Output Schema
| Name | Required | Description |
|---|---|---|
| amount | Yes | |
| symbol | Yes | |
| currency | Yes | |
| decimals | Yes | |
| formatted | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It merely states the purpose without disclosing behaviors such as rounding, handling of invalid inputs, or that it returns a string (though output schema exists).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. While efficient, it could be slightly more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with full schema and output schema, the description is minimally adequate. However, it lacks behavioral details that would help an agent handle edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('format an amount as currency'), distinguishing it from siblings like format_number and format_percentage. However, it could be more explicit about localization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives (e.g., format_number, format_percentage). The description does not provide context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_dateCInspect
Format a date string.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Date string (ISO format) | |
| format | No | Output format | %Y-%m-%d %H:%M:%S |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| format | No | |
| original | No | |
| formatted | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior but only states 'Format a date string.' It omits details such as input requirements (ISO format), format pattern syntax, and error handling. The agent receives minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (4 words) but under-specified. It lacks crucial details and does not earn its brevity by adding value beyond the tool name. A bit more information would improve it without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters and an output schema, the description is incomplete. It does not mention the return type (formatted string), strftime patterns, or handling of invalid inputs. Agents would need additional context to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters documented), so baseline is 3. The description adds no extra meaning beyond the schema fields; it does not clarify the strftime-style format or ISO date constraint.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Format a date string' clearly states the verb and resource but lacks specificity about the type of formatting or input format. It does not differentiate from sibling tools like parse_date or format_relative_time, which also handle dates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of when to choose format_date over parse_date, format_relative_time, or other date-related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_durationCInspect
Format seconds as duration.
| Name | Required | Description | Default |
|---|---|---|---|
| seconds | Yes | Duration in seconds | |
| verbose | No | Use verbose format (1 hour 2 minutes) |
Output Schema
| Name | Required | Description |
|---|---|---|
| seconds | Yes | |
| breakdown | Yes | |
| formatted | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states 'Format seconds as duration' without explaining the return format, the effect of the verbose parameter, or any other behavior. This is insufficient for an agent to understand the tool's operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence that is front-loaded and contains no unnecessary words. While concise, it could be improved by adding a brief example or additional context without bloating.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (true) and full parameter descriptions, the description is minimally adequate. However, it does not explain the output format or the impact of the verbose parameter, leaving some gaps in understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for both parameters (seconds and verbose). The description adds no extra meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: formatting seconds as duration. It uses a specific verb and resource, distinguishing it from other formatting tools like format_bytes or format_currency. However, it lacks detail on the output format, such as whether it returns a human-readable string or another format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like seconds_to_hms, which also converts seconds to a time format. The description does not mention context or exclusions, leaving the agent without clear decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_listCInspect
Format a list of items with proper grammar.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items | |
| conjunction | No | Conjunction to use (and, or) | and |
| oxford_comma | No | Use Oxford comma |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| items | Yes | |
| formatted | Yes | |
| conjunction | Yes | |
| oxford_comma | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations available. The description only restates basic functionality without disclosing behavioral details such as input format (comma-separated) or default Oxford comma. The schema provides these details, but the description adds no extra value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff. Could potentially include more detail but remains concise and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 3 parameters and an output schema, the description is adequate but lacks context on what 'proper grammar' means or the output format. It does not leverage the output schema presence to reduce burden.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description adds minimal semantic value beyond 'proper grammar', which loosely relates to conjunction and Oxford comma parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'format' and resource 'list of items', and specifies the goal 'with proper grammar'. It distinguishes itself from sibling tools like sort_items or capitalize by focusing on grammatical formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like join or list_to_sentence. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_numberCInspect
Format a number with locale-specific separators.
| Name | Required | Description | Default |
|---|---|---|---|
| locale | No | Locale (en-US, de-DE, fr-FR, etc.) | en-US |
| number | Yes | Number to format | |
| decimals | No | Decimal places |
Output Schema
| Name | Required | Description |
|---|---|---|
| locale | Yes | |
| number | Yes | |
| formatted | Yes | |
| decimal_separator | Yes | |
| thousand_separator | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits beyond basic formatting. It lacks information about error handling, default behavior for invalid locales, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no extra words. However, it is so concise that it omits potentially useful details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to explain return values. The tool is simple, but the description could note what happens with unsupported locales or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds the context of 'locale-specific separators', which reinforces the schema's locale parameter but does not add new constraints beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'format' and resource 'number', with the specific qualifier 'locale-specific separators'. This is distinct from sibling tools like format_currency or format_percentage, though it doesn't explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as format_currency or format_percentage. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_ordinalAInspect
Convert a number to its ordinal form (1st, 2nd, 3rd, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to convert to ordinal |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| suffix | Yes | |
| ordinal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must handle behavioral disclosure. It does not mention how edge cases (e.g., negative numbers, large numbers, zero) are handled, nor does it describe any constraints or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that clearly communicates the purpose. No unnecessary words, and the key information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description covers the core functionality. However, it omits mention of edge cases or language/locale specifics. Minor gaps but generally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds clarifying examples (1st, 2nd, 3rd, etc.) that explain the expected output, which adds value beyond the parameter description in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts a number to its ordinal form, with examples like 1st, 2nd, 3rd. It is specific about the verb (convert) and the resource (number), and distinguishes it from siblings such as format_number, number_to_words, or number_to_roman.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., format_number or number_to_words). It does not mention when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_percentageBInspect
Format a number as a percentage.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Value to format as percentage | |
| decimals | No | Decimal places | |
| multiply | No | Multiply by 100 (0.5 -> 50%) |
Output Schema
| Name | Required | Description |
|---|---|---|
| value | Yes | |
| decimals | Yes | |
| formatted | Yes | |
| percentage | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral traits such as the default multiplication by 100 (despite the 'multiply' parameter defaulting to true) or rounding/decimals behavior. With no annotations, the description fails to provide sufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with 6 words, extremely concise and front-loaded. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and that the schema plus output schema (present) provide good detail, the description is sufficiently complete. Minor gap: could mention the default output format (e.g., appends '%' sign).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all three parameters with descriptions, achieving 100% coverage. The tool description adds minimal value beyond what the schema already provides, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Format a number as a percentage' clearly states the action (format) and the resource (number) and the output type (percentage). It effectively distinguishes from sibling formatting tools like format_number and format_currency.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like format_number or format_currency. The description lacks any context about prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_phoneCInspect
Format a phone number according to country conventions.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Phone number to format | |
| country | No | Country code (US, UK, DE, FR, etc.) | US |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| input | Yes | |
| country | No | |
| formatted | No | |
| digits_only | No | |
| country_code | No | |
| international | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavioral traits like handling of invalid numbers or unsupported country codes. It adds little beyond the schema, which already defines parameters.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, very concise. While it could include more structure or examples, it is appropriately brief for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is minimally adequate. However, it could clarify expected input format or behavior with invalid inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description does not need to add parameter details. It offers no extra meaning beyond the schema, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool formats phone numbers by country, which distinguishes it from sibling tools like validate_phone or generate_phones. However, it does not explicitly differentiate from other formatting tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like validate_phone (validation) or random_phone (generation). It does not mention prerequisites, such as requiring a valid number.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_relative_timeCInspect
Format seconds as relative time (e.g., '2 hours ago', 'in 3 days').
| Name | Required | Description | Default |
|---|---|---|---|
| seconds | Yes | Seconds from now (positive = future, negative = past) |
Output Schema
| Name | Required | Description |
|---|---|---|
| unit | Yes | |
| value | Yes | |
| seconds | Yes | |
| formatted | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description alone must disclose behavior. It mentions the parameter semantics (positive=future, negative=past) but does not specify the range of relative units (e.g., seconds to years) or how edge cases are handled. The example only covers hours and days.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—one sentence with an example. Every word is useful, and the example helps clarify the output format. It is well-structured for quick reading.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (context signal), the description does not need to explain return values. However, for a tool with zero annotations, it lacks details on behavior like rounding, unit thresholds, or performance with large values. It is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already adequately describes the 'seconds' parameter. The description adds an output example but no new semantic meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts seconds to a relative time string with a concrete example ('2 hours ago', 'in 3 days'). The purpose is distinct from many siblings, though 'relative_time' is a similar sibling not explicitly distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'relative_time', 'format_duration', or 'format_date'. The description only implies usage for formatting seconds, not when it is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_ssnBInspect
Format a Social Security Number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | SSN to format |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| input | Yes | |
| masked | No | |
| formatted | No | |
| last_four | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits, but it only states the action without specifying what formatting entails (e.g., adding dashes, validating format). Missing details on expected input format and output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no redundancy. It is front-loaded and concise, though it could benefit from a bit more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (present but not shown) and a single parameter, the description provides minimal context. While it states the basic purpose, it does not cover expected input/output format or any edge cases, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% since the parameter 'number' has a description 'SSN to format', but the tool description adds no additional semantics beyond that. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Format' and the resource 'Social Security Number', which is specific and distinguishes it from sibling format tools like format_credit_card or format_phone.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any prerequisites or exclusions. The agent has no context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
format_truncateBInspect
Truncate text to a maximum length.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to truncate | |
| length | No | Maximum length | |
| suffix | No | Suffix to add when truncated | ... |
Output Schema
| Name | Required | Description |
|---|---|---|
| input | Yes | |
| output | Yes | |
| truncated | Yes | |
| output_length | No | |
| original_length | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral traits such as when the suffix is added, edge case handling (e.g., empty text), or whether truncation occurs at character or byte level. With no annotations, the description should provide these details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. It is concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple truncation tool with an output schema, the description is minimally adequate but lacks details about suffix behavior and edge cases. Given low complexity, a score of 3 is appropriate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (truncate) and resource (text) with a condition (maximum length). It is specific but does not differentiate from sibling tools like truncate or truncate_2.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There are sibling truncation tools, but the description provides no context for selection or exclusion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
fortune_cookieBInspect
Get a fortune cookie message.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| fortune | Yes | |
| lucky_numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description should disclose behavioral traits. It merely states the action without mentioning randomness, determinism, or any side effects. The brief description is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise with a single sentence that directly states the purpose. It is front-loaded and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and an existing output schema, the description is minimally adequate. However, it does not specify the format of the fortune message or any additional context, which could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema coverage is 100%. The description adds no parameter information, but baseline is 3, and with no parameters, 4 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns a fortune cookie message, which is a specific and understandable purpose. It distinguishes from siblings like dad_joke or random_trivia by its unique theme, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as random_trivia or dad_joke. The description lacks context for optimal usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
friendly_roastBInspect
Generate a friendly roast.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Name to roast | Friend |
Output Schema
| Name | Required | Description |
|---|---|---|
| name | Yes | |
| roast | Yes | |
| disclaimer | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It only states the action without disclosing any behavioral details such as how the roast is generated, whether it uses the provided name, or what the output format is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence with no wasted words. It is direct and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally sufficient. However, it lacks details about the roast style or the default behavior for missing name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter 'name' described as 'Name to roast'. The tool description does not add extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a friendly roast' clearly states the action (generate) and the resource (friendly roast). It is distinct from sibling tools like 'dad_joke' or 'magic_8_ball', though not specifying the style of roast.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or context for optimal use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
future_valueCInspect
Calculate future value of an investment.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual interest rate (percentage) | |
| years | Yes | Number of years | |
| present_value | Yes | Present value |
Output Schema
| Name | Required | Description |
|---|---|---|
| years | Yes | |
| total_gain | Yes | |
| future_value | Yes | |
| rate_percent | Yes | |
| present_value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral transparency. It only says 'calculate', omitting important details such as compounding frequency (implied annual), assumptions, or what happens with invalid inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise—a single sentence. It efficiently conveys the core purpose, though it could benefit from additional context without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks important context such as the compounding assumption (annual) and does not clarify how it differs from 'compound_interest'. Despite the output schema existing, the description is too minimal for a financial calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters already have descriptions. The tool description adds no additional meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool calculates future value of an investment, which is a specific verb+resource. However, it does not distinguish from sibling tools like 'compound_interest' or 'present_value', leaving ambiguity about the exact method (e.g., compounding frequency).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, when not to use it, or related tools like 'compound_interest'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gallons_uk_to_litersAInspect
Convert UK gallons to liters.
| Name | Required | Description | Default |
|---|---|---|---|
| gallons | Yes | Volume in UK gallons |
Output Schema
| Name | Required | Description |
|---|---|---|
| liters | Yes | |
| gallons_uk | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but the description accurately indicates a straightforward conversion without side effects. Adequate for a pure function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple unit conversion with one parameter and output schema present, the description is fully sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description already covers 'Volume in UK gallons' at 100%. Description adds no extra semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Convert' and resource 'UK gallons to liters', clearly distinguishing it from sibling tools like 'gallons_us_to_liters'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives, but the tool's purpose is self-evident given the naming and description. Simple conversion tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gallons_us_to_litersAInspect
Convert US gallons to liters.
| Name | Required | Description | Default |
|---|---|---|---|
| gallons | Yes | Volume in US gallons |
Output Schema
| Name | Required | Description |
|---|---|---|
| liters | Yes | |
| gallons_us | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose any behavioral details such as conversion factor, precision, handling of negative values, or output format. For a simple conversion, this is insufficient to inform the agent about potential edge cases or numeric behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, precise sentence that front-loads the core purpose. There is no wasted text, and it efficiently communicates the function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and existence of output schema, the description is passable but lacks details like the standard conversion factor (1 US gallon = 3.78541 liters) or any mention of rounding, which would make it more complete for an agent. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameter descriptions, so the tool description adds no additional meaning beyond what is in the schema. Baseline of 3 is appropriate as the description does not enrich parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and resource 'US gallons to liters', distinguishing it from the sibling tool 'gallons_uk_to_liters' which converts UK gallons. This specificity leaves no ambiguity about what unit is being converted.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for US gallons but provides no explicit guidance on when to use this tool versus alternatives like 'gallons_uk_to_liters'. While the sibling tool name hints at the distinction, the description itself does not direct the agent to the appropriate alternative for UK gallons.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcdBInspect
Calculate the greatest common divisor.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First number | |
| b | Yes | Second number |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | Yes | |
| b | Yes | |
| gcd | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description is minimal and does not disclose behavior regarding negative numbers, zero, large integers, or return value details. Even though an output schema exists (not shown), the description itself adds very little behavioral context beyond the basic calculation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence. It contains no unnecessary words and is directly front-loaded with the purpose. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (two integer parameters, standard mathematical operation), the description is minimally adequate. However, it lacks information on edge cases, return type (though output schema exists), and usage context. It could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are documented in the schema with titles and descriptions. The description does not add additional meaning beyond what the schema already provides. With 100% schema coverage, baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to calculate the greatest common divisor. It uses a specific verb and resource. However, it does not explicitly distinguish itself from sibling mathematical tools like lcm or other number theory functions, but given the standard nature of GCD, it is clear enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, edge cases, or comparison with similar tools (e.g., lcm). The description leaves the agent without context for choosing this tool among many math operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_acronymCInspect
Generate acronym from text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to create acronym from |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | Original input text |
| acronym | Yes | Generated acronym from first letters of each word |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits, but it only states the generic task without specifying how the acronym is formed (e.g., first letters, case handling, punctuation handling). This is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded with the key action, but it is too brief, omitting critical details that could have been included without much length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with an output schema, the description should explain what constitutes an acronym and the expected behavior. Instead, it is vague and leaves the agent guessing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the parameter 'text' has a clear description in the schema. The tool description adds no extra information beyond that, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and resource 'acronym from text', making the purpose immediately understandable. However, it does not differentiate from the sibling tool 'get_initials', which is closely related.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'get_initials', nor any conditions or prerequisites for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_addressesCInspect
Generate random placeholder addresses.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of addresses |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| addresses | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states it generates random placeholder addresses. It omits details about address format, country, determinism, or safety (e.g., no destructive actions). This is insufficient for understanding behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no extraneous words. It is efficient but lacks structural elements like front-loading key information; however, brevity is a strength here.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter) and the existence of an output schema (not shown), the description is minimally adequate. However, it could be improved by mentioning that it returns an array of address objects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (the 'count' parameter has a description: 'Number of addresses'). The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates random placeholder addresses. The verb 'Generate' and noun 'addresses' are specific, and the sibling 'random_address' suggests this tool can produce multiple addresses, though the description alone doesn't specify plurality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like 'random_address' or other generation tools. The description lacks context about use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_colorCInspect
Generate random color(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of colors | |
| format | No | Format: hex, rgb, hsl | hex |
Output Schema
| Name | Required | Description |
|---|---|---|
| color | No | |
| count | No | |
| colors | No | |
| format | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It merely states 'Generate random color(s).' without mentioning any side effects, deterministic behavior, or other traits. The schema provides parameter details, but the description adds no extra transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise. However, given the complexity and the number of sibling tools, slightly more structure (e.g., mentioning that it produces multiple colors) would improve it. Still, it is efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return values need not be explained. The description is adequate for a simple generation tool, but with many similar tools, it could provide more details on randomness or format defaults. It is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%—both parameters ('count' and 'format') are described in the schema. The description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly says 'Generate random color(s).' This indicates the verb and resource. However, it does not differentiate from siblings like 'random_color' or 'random_color_2', which likely have similar purposes. The lack of distinction prevents a higher score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many color-related sibling tools, such as 'random_color', 'blend_colors', 'complement_color', etc., the user is left without any context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_companiesCInspect
Generate random placeholder company names.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of company names |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| companies | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral info. It only states it generates names; no details on output format, randomness, or side effects. Very limited transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 5-word sentence, very concise. It is front-loaded with purpose, though it could be slightly more informative without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and one simple parameter, the description is minimally complete. However, it lacks usage guidelines and behavioral details, leaving gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for 'count'. The tool description adds no extra meaning beyond what the schema provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates random placeholder company names. It uses a specific verb 'generate' and resource, but does not explicitly differentiate from sibling 'random_company' which likely generates a single name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like 'random_company' or other random generators. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_datesCInspect
Generate random dates.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of dates | |
| format | No | Format: ISO, US, EU | ISO |
| end_year | No | End year | |
| start_year | No | Start year |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| dates | Yes | |
| format | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose that the tool can generate multiple dates (via 'count' parameter), accepts a date range through 'start_year' and 'end_year', or offers format choices. Randomness guarantees are absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), but it is too sparse to be helpful. It does not structure information effectively—no front-loading of key details beyond the basic action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters and no annotations, the description is incomplete. It fails to explain the output format (though output schema exists), default behavior, or constraints like the requirement that 'start_year' be less than 'end_year'. The agent cannot fully understand the tool's capabilities from the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. However, the description adds no additional meaning beyond what the schema already provides. It does not explain the interaction between 'start_year' and 'end_year' or the significance of the 'format' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate random dates.' clearly states the action (generate) and resource (dates), but does not differentiate from sibling tools like 'random_date' which likely does the same thing. The scope (single or multiple, date range) is not specified.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives such as 'random_date', 'format_date', or 'parse_date'. There is no mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_emailsCInspect
Generate random placeholder email addresses.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of emails | |
| domain | No | Email domain | example.com |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| domain | Yes | |
| emails | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It only says 'random placeholder' but does not detail that emails are not functional, how domains are used, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise single sentence, which is efficient but lacks context that could be added without significant bloat. Does not use front-loading effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple random generation tool, the description is minimally adequate. However, with many similar sibling tools and no output schema details, more context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for both parameters (count, domain) with descriptions. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Generate random placeholder email addresses' with specific verb and resource. However, it does not differentiate from sibling tool 'random_email', which likely generates a single random email.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'random_email' or other generators. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_gradientCInspect
Generate a gradient between two colors.
| Name | Required | Description | Default |
|---|---|---|---|
| steps | No | Number of steps in gradient | |
| color1 | Yes | Start hex color | |
| color2 | Yes | End hex color |
Output Schema
| Name | Required | Description |
|---|---|---|
| end | Yes | |
| start | Yes | |
| steps | Yes | |
| gradient | Yes | |
| css_gradient | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only states the basic operation. It does not disclose that the output is an array of hex colors, that interpolation is linear, or any side effects. The schema covers parameter descriptions but not behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. It is efficient but could include more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks context about what a gradient means (e.g., linear interpolation) and how it compares to similar tools. It is minimally adequate but leaves the agent guessing about output structure and use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and each parameter has a description (e.g., 'Start hex color', 'End hex color', 'Number of steps in gradient'). The tool description adds no further meaning beyond these schema declarations, so it meets the baseline but does not exceed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and the resource 'gradient between two colors'. It distinguishes from sibling tools like 'blend_colors' which yields a single color, and 'generate_shades'/'generate_tints' which modify a single color. However, it does not explicitly differentiate from all color-related siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not indicate when to use this tool versus alternatives like 'blend_colors' or 'generate_shades'. There are no prerequisites, exclusions, or context cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_hashCInspect
Generate hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash | |
| algorithm | No | Algorithm: md5, sha1, sha256, sha512 | sha256 |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | No | |
| text | No | |
| error | No | |
| algorithm | No | |
| supported | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. The description only states 'Generate hash of text' without detailing the output format (e.g., hex string), determinism, or any side effects. This is insufficient for an agent to understand the tool's behavior fully.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single sentence of five words. For a simple tool with two parameters and an output schema, this is appropriately sized. No unnecessary words, and the essential purpose is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema (not shown), the description should at least explain what the output represents (e.g., 'Returns the hash as a hex string'). The current description does not clarify the return format. For a tool that could be used in various contexts, this omission limits completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both 'text' and 'algorithm' parameters having descriptions. The description adds no additional meaning beyond what the schema already provides. According to the guidelines, when schema coverage is high, baseline is 3. No extra value is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate hash of text' clearly states the action (generate) and the resource (hash of text). It implies the tool produces a hash from input text. However, it does not differentiate from sibling tools like hash_md5, hash_sha256, etc., which are specific hash implementations. The name 'generate_hash' suggests a generic hashing function, which is consistent but not exclusive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the specific hash tools (hash_md5, hash_sha1, etc.). There are many sibling hash tools, and an agent would benefit from knowing that this tool is more flexible due to the algorithm parameter, but no such information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_hmacCInspect
Generate HMAC signature.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Secret key | |
| message | Yes | Message to sign | |
| algorithm | No | Hash algorithm: md5, sha1, sha256, sha512 | sha256 |
Output Schema
| Name | Required | Description |
|---|---|---|
| hmac | No | |
| error | No | |
| message | No | |
| algorithm | No | |
| supported | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations and description does not disclose any behavioral traits such as output format (hex?), security considerations, or whether it performs constant-time comparison. For a crypto tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence is concise but at the expense of completeness. It is not overly verbose, but lacks necessary detail for a crypto operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of the tool (cryptographic operation, multiple parameters, many similar siblings), the description is too minimal. It does not cover when to use, output format, or security notes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions like 'Secret key' and 'Message to sign'. The description adds no additional meaning beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Generate HMAC signature' which is clear but does not distinguish from sibling tools like hmac_sha256 that also generate HMAC signatures. The generic nature is implied by the algorithm parameter but not explicitly stated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this generic HMAC generator versus the algorithm-specific siblings (hmac_md5, hmac_sha256, etc.). The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_loremCInspect
Generate lorem ipsum text using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| paragraphs | No | Number of paragraphs | |
| sentences_per_paragraph | No | Sentences per paragraph |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| count | Yes | |
| paragraphs | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose whether the output is random or deterministic, despite using Faker which typically generates random data. No annotations are present, so the description carries the full burden, and it falls short.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the core purpose. It is front-loaded and free of unnecessary words, though it could benefit from slightly more detail without compromising conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and full parameter schema coverage, the description is minimally adequate. However, it lacks information about behavioral aspects (e.g., randomness), which leaves gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the input schema already describes both parameters ('Number of paragraphs', 'Sentences per paragraph'). The description adds no additional meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that it generates lorem ipsum text using Faker, indicating the verb and resource. However, it does not differentiate from sibling tools like lorem_words, lorem_sentences, or lorem_paragraphs, which have similar purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lorem_words or lorem_paragraphs. The description lacks context about appropriate use cases or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_memorableCInspect
Generate a memorable password based on a pattern.
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | No | Pattern: c=consonant, v=vowel, d=digit, s=symbol | cvccvc |
Output Schema
| Name | Required | Description |
|---|---|---|
| length | Yes | |
| pattern | Yes | |
| password | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as cryptographic security, error handling, or randomness source. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, one sentence, no wasted words. Could be considered underspecified but achieves brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity and presence of an output schema, the description still lacks sufficient context for tool selection (e.g., security or usage hints). Insufficient for decision-making.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'pattern' already described. The tool description adds 'memorable' but does not provide additional meaning beyond the schema's explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a memorable password based on a pattern. This distinguishes it from random password generators (e.g., generate_password) by specifying the pattern-based approach.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like generate_password or random_password. The description lacks explicit context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_namesCInspect
Generate random placeholder names.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of names | |
| include_last | No | Include last names |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| names | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description should disclose behavioral traits. It only states what the tool does, without mentioning authorization, side effects, rate limits, or return format. This is insufficient for an agent to understand the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence without wasted words, making it concise. However, it could be slightly more informative while still being brief.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the simplicity of the tool and the presence of an output schema, the description lacks important details about output format, the nature of placeholder names, and when to use this tool over similar siblings. This makes it incomplete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters ('Number of names', 'Include last names'). The tool description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and the resource 'random placeholder names', indicating the tool produces names for placeholder use. However, it does not distinguish from similar siblings like 'random_name' or 'generate_acronym', which may cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. With many sibling tools for name generation (e.g., random_name, generate_companies), explicit context is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_ngramsCInspect
Generate n-grams from text.
| Name | Required | Description | Default |
|---|---|---|---|
| n | No | N-gram size | |
| text | Yes | Text to generate n-grams from |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | N-gram size used |
| text | Yes | Original input text |
| count | Yes | Total number of n-grams |
| ngrams | Yes | List of generated n-grams |
| unique | Yes | Number of unique n-grams |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral information beyond the input schema. There is no mention of output format, edge cases (e.g., handling of punctuation or repeated words), or performance characteristics. Since annotations are absent, the description should have provided more transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it very concise and front-loaded. However, for a tool with two parameters and an output schema, it could be slightly expanded to include an example or usage hint without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally complete. However, it does not explain the concept of n-grams or how the tool handles edge cases, which would be helpful for an AI agent to invoke it correctly among many similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters ('text' and 'n'). The description does not add any additional meaning beyond the schema, baseline is 3 as per instructions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate n-grams from text' clearly states the action (generate) and the resource (n-grams). However, it does not distinguish this tool from siblings like 'generate_acronym' or 'word_count', which also generate text-based output.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs. alternatives. For example, it does not explain that n-grams are useful for language modeling or pattern detection, nor does it specify any prerequisites or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_passphraseCInspect
Generate a passphrase from random words.
| Name | Required | Description | Default |
|---|---|---|---|
| words | No | Number of words | |
| separator | No | Word separator | - |
| capitalize | No | Capitalize each word | |
| include_number | No | Include a random number |
Output Schema
| Name | Required | Description |
|---|---|---|
| length | Yes | |
| passphrase | Yes | |
| word_count | Yes | |
| entropy_bits | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic action without revealing details like word source, default behavior, or whether the passphrase is cryptographically secure. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, which is front-loaded and wastes no words. However, it may be too sparse for a tool with multiple parameters and siblings.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is minimally adequate. However, it lacks differentiation from similar tools (e.g., generate_memorable) and does not explain the word list or security aspects, leaving some contextual gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All four parameters have descriptions in the schema (100% coverage), so the description does not need to add much. It does not elaborate on parameter meanings beyond what the schema already provides, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: generating a passphrase from random words. This is specific and distinguishes it from other generators like generate_password (alphanumeric strings) and generate_pin (numeric digits). However, it could be stronger by explicitly contrasting with similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like generate_memorable or generate_password. There are no usage examples, prerequisites, or explicit exclusions, leaving the agent to infer appropriateness without support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_passwordCInspect
Generate secure password(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | How many passwords to generate | |
| length | No | Password length | |
| numbers | No | Include numbers | |
| symbols | No | Include symbols | |
| lowercase | No | Include lowercase letters | |
| uppercase | No | Include uppercase letters | |
| exclude_ambiguous | No | Exclude ambiguous characters (0O1lI) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| count | No | |
| error | No | |
| length | No | |
| password | No | |
| passwords | No | |
| entropy_bits | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden. It lacks details on randomness source, security guarantees, output format, or default character set, leaving behavior opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise but sacrifices informativeness. It is front-loaded but missing essential details, so it is not optimally balanced.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 7 parameters, no annotations, and many siblings, the description is insufficient. It lacks context on output format, password strength, and when to use this tool among alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers all 7 parameters with descriptions (100% coverage). The tool description adds no additional semantic value beyond what the schema provides, meeting baseline adequacy.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates secure passwords. However, it does not differentiate from sibling tools like generate_passphrase or generate_password_2, which could cause ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. With many password-related siblings, explicit usage instructions are needed.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_password_2BInspect
Generate a secure random password.
| Name | Required | Description | Default |
|---|---|---|---|
| digits | No | Include digits | |
| length | No | Password length | |
| special | No | Include special characters | |
| lowercase | No | Include lowercase letters | |
| uppercase | No | Include uppercase letters | |
| exclude_chars | No | Additional characters to exclude | |
| exclude_ambiguous | No | Exclude ambiguous chars (0O1lI) |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| length | No | |
| password | No | |
| charset_size | No | |
| entropy_bits | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It describes the output as 'secure random password' but doesn't detail the randomness source or any security guarantees. The description is not misleading but adds minimal behavioral context beyond the input schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no extraneous words. Every word earns its place, making it highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and rich input schema, the description is adequate for the tool's simple function. However, given the many similar siblings, it lacks differentiation and could benefit from mentioning when to prefer this variant.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so each parameter already has a description in the schema. The tool description itself adds no additional meaning beyond what the schema provides, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a secure random password, using a specific verb and resource. However, it does not differentiate from sibling tools like 'generate_password' or 'generate_passphrase', which could cause confusion for the agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like 'generate_password' or 'generate_token'. The description lacks any when-to-use or when-not-to-use criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_phonesCInspect
Generate random placeholder phone numbers.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of phone numbers | |
| format | No | Format: us, international | us |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| format | Yes | |
| phones | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only says 'random placeholder' without specifying if numbers are realistic, valid, or how formats differ. No mention of non-destructive nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence is concise but lacks structure. It is front-loaded but too brief to cover essential details, making it adequate but not excellent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, return values need not be explained. However, the description fails to address limitations, behavior, or differences from sibling tools, making it incomplete for informed selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. Description adds no extra meaning beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates random placeholder phone numbers, but it does not explicitly distinguish from sibling tool 'random_phone' which likely generates a single number. The plural 'phone numbers' hints at multiple generation, but lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'random_phone', 'format_phone', or 'validate_phone'. The agent receives no help in selecting the appropriate tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_pinCInspect
Generate a random PIN.
| Name | Required | Description | Default |
|---|---|---|---|
| length | No | PIN length |
Output Schema
| Name | Required | Description |
|---|---|---|
| pin | Yes | |
| length | Yes | |
| entropy_bits | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any behavioral traits. It does not mention that the PIN is numeric (digits only), the randomness quality, or that it generates a string. No annotations are present to compensate. The agent is left guessing about the output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
At one sentence, it is concise but overly sparse. While it wastes no words, it could provide more detail without sacrificing brevity. It is front-loaded but lacks completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and an output schema (presumably string), the description is minimally complete. However, it does not explain return values, which the output schema likely covers. Still, more context about typical PIN usage could help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full coverage for the single optional parameter 'length' (default 4, min 3, max 12). The description adds no additional meaning beyond what the schema already conveys. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a random PIN.' clearly states the action and resource. It distinguishes from sibling tools like generate_password or generate_uuid by specifying 'PIN', a numeric code typically used for authentication. However, it does not explicitly differentiate from similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For instance, a note like 'Use for numeric PINs, not alphanumeric passwords' would help. Without such context, an AI agent may not know when to choose this over generate_password or generate_token.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_sequenceCInspect
Generate a number sequence.
| Name | Required | Description | Default |
|---|---|---|---|
| end | No | End value | |
| step | No | Step value | |
| start | No | Start value |
Output Schema
| Name | Required | Description |
|---|---|---|
| end | Yes | |
| step | Yes | |
| start | Yes | |
| length | Yes | |
| sequence | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It only states 'generate a number sequence' without mentioning key behaviors like that it produces an arithmetic sequence from start to end with step, or what happens with defaults.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence but is underspecified for the tool's purpose and context. It sacrifices informativeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although the schema covers parameter details and output schema exists, the description fails to clarify core behavior (e.g., that it generates an arithmetic sequence). This leaves the agent with incomplete understanding of the tool's function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, providing basic descriptions for each parameter. The tool's description adds no additional meaning beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a number sequence' is vague and does not specify what type of sequence (arithmetic, geometric, etc.). With sibling tools like 'fibonacci' and 'collatz_sequence', the purpose is unclear and not differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, nor does it give any context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_shadesBInspect
Generate shades (darker variations) of a color.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of shades | |
| hex_color | Yes | Base hex color |
Output Schema
| Name | Required | Description |
|---|---|---|
| base | Yes | |
| tints | No | |
| shades | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as what determines the shade, whether it modifies the input, or any constraints on input format. The description is too brief to inform an agent about side effects or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It front-loads the purpose effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to explain return values. However, it lacks behavioral details like handling of invalid input or the algorithm used, which would be beneficial for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters. The description adds context ('darker variations') but does not add meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and the resource 'shades (darker variations) of a color'. It distinguishes from sibling tools like generate_tints (lighter variations) and lighten_color/darken_color by specifying that shades are darker.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as generate_tints or darken_color. It does not mention when not to use it or provide any decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_tintsBInspect
Generate tints (lighter variations) of a color.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of tints | |
| hex_color | Yes | Base hex color |
Output Schema
| Name | Required | Description |
|---|---|---|
| base | Yes | |
| tints | No | |
| shades | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description only states purpose without disclosing behavioral traits such as handling invalid hex colors, ordering of tints, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no extraneous information, well front-loaded. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite minimal description, the tool is simple with only 2 parameters fully described in schema and an output schema present. Combined with schema, coverage is adequate for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters ('Number of tints', 'Base hex color'). Description adds no additional meaning beyond schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool generates tints (lighter variations) of a color, with specific verb 'generate' and resource 'tints', distinguishing it from sibling 'generate_shades'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'generate_shades' or other color tools. Does not mention prerequisites or context for use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_tokenCInspect
Generate cryptographically secure token.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Format: hex, base64, urlsafe | hex |
| length | No | Token length in bytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| bytes | Yes | |
| token | Yes | |
| format | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description only says 'cryptographically secure', which implies safe random generation but lacks details on output format, default length, or any limitations. Falls short of fully describing behavior for a security-sensitive tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short description (5 words) conveys the core purpose without waste. However, it is too minimal and fails to provide necessary context, making it an under-specification rather than optimal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values are covered. However, the description lacks behavioral details and usage guidance that would make it complete for a security tool. Adequate for a simple utility but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already explains format and length. The description does not add additional meaning beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific verb ('generate') and resource ('cryptographically secure token'), clearly indicating the tool's purpose. It partially distinguishes from siblings like generate_password or generate_hash by emphasizing cryptographic security, but could be more explicit about differences from other token-generation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention prerequisites, restrictions, or scenarios where another tool might be more appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_uuidCInspect
Generate UUID(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of UUIDs to generate | |
| version | No | UUID version (1 or 4) |
Output Schema
| Name | Required | Description |
|---|---|---|
| uuid | No | |
| count | No | |
| uuids | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It does not mention that multiple UUIDs can be generated or that the version can be specified, both of which are revealed only through the schema. The description is too minimal to be transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) and front-loaded, but it is under-specified. It could include a brief note about common usage without adding much length, making the conciseness a trade-off with completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description should at least mention that it can generate one or more UUIDs and allow version selection. It does not, leaving the agent with incomplete context for effective invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage for its two parameters (count and version), so the baseline is 3. The description does not add any additional context or meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates UUIDs, but it does not differentiate from sibling tools like 'generate_uuids' (plural) or 'generate_uuid_v7', which have overlapping functionality. The verb and resource are clear, but the lack of distinction limits the score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Given the presence of multiple UUID-related siblings, this omission makes it harder for an agent to select the correct tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_uuidsBInspect
Generate random UUIDs.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of UUIDs |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| uuids | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is minimal. It does not disclose any behavioral traits such as randomness source, thread safety, or side effects. For a random generation tool, the lack of detail reduces transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words. It is concise and to the point, earning a perfect score for structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown), the description could be adequate if the output schema explains the return format. However, without seeing it, the description lacks details about what the tool returns (e.g., array of strings). It is minimally complete for a simple tool but could be more informative.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a single parameter 'count', described as 'Number of UUIDs'. The description 'Generate random UUIDs' adds no additional meaning beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate random UUIDs' clearly states the tool's verb and resource. However, it does not differentiate from sibling tools like 'generate_uuid', 'random_uuid', or 'generate_uuid_v7', which also generate UUIDs but may produce different versions or singular results. The purpose is clear but not unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. For example, it does not mention that it generates multiple UUIDs (via the count parameter) or that it produces version 4 UUIDs. Users are left to guess which tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_uuid_v7BInspect
Generate UUID v7 (time-ordered).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of UUIDs to generate |
Output Schema
| Name | Required | Description |
|---|---|---|
| uuid | No | |
| count | No | |
| uuids | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the output is time-ordered but does not disclose any behavioral traits like determinism, side effects, or performance characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. However, it is very brief and lacks structured information for a tool with a parameter, though it remains efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool, the description is incomplete. It has an output schema and partial parameter documentation, but it misses usage guidelines and behavioral context, leaving gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a description for the 'count' parameter. The description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates UUID v7, which is time-ordered. It uses a specific verb 'Generate' and resource 'UUID v7', distinguishing it from siblings like 'generate_uuid' (likely v4) or 'random_uuid'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'generate_uuid' or 'generate_uuids'. It does not mention context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
geohash_decodeBInspect
Decode geohash to coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
| geohash | Yes | Geohash string |
Output Schema
| Name | Required | Description |
|---|---|---|
| lat | Yes | |
| lon | Yes | |
| geohash | Yes | |
| lat_error | Yes | |
| lon_error | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic function, omitting any details about accuracy, input constraints, or potential side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words or redundancy. It is appropriately concise and can be understood quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one input, one output), the minimal description is nearly sufficient. The existence of an output schema likely covers the coordinate format, so the description adequately completes the context for a straightforward decoding operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'geohash' is described in the schema as 'Geohash string', and the tool description adds no further meaning beyond that. Since schema coverage is 100%, a score of 3 is appropriate as the description adds no extra semantic value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Decode') and the object ('geohash') and the result ('to coordinates'). It effectively distinguishes itself from its sibling 'geohash_encode' which performs the inverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when or when not to use this tool, nor does it mention alternatives or prerequisites. It simply states what the tool does without any contextual advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
geohash_encodeAInspect
Encode coordinates to geohash.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude | |
| lon | Yes | Longitude | |
| precision | No | Precision (1-12) |
Output Schema
| Name | Required | Description |
|---|---|---|
| lat | Yes | |
| lon | Yes | |
| geohash | Yes | |
| precision | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It identifies the core function (encoding to geohash) but does not address error handling, output format specifics, or constraints beyond schema. Since an output schema exists, the return format is partly covered, but behavioral traits like behavior on invalid coordinates are omitted. No contradiction with annotations as none are present.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately conveys the tool's purpose. Every word is necessary, and it is front-loaded with no extraneous information. This is optimal for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward encoding tool, the description, combined with the complete schema and output schema (context indicates its existence), provides adequate completeness. It could benefit from a brief note about precision trade-offs or typical usage scenarios, but it is sufficient for a basic understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema's property descriptions. It does not explain how precision affects the geohash or provide context for the coordinate range. Score remains at baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('encode') and the resource ('coordinates to geohash'). It is specific and unambiguous, effectively distinguishing it from the sibling tool 'geohash_decode' which performs the inverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as geohash_decode or other coordinate tools. The description does not mention use cases, prerequisites, or exclusion criteria, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
geometric_meanCInspect
Calculate geometric mean.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated positive numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| count | No | |
| error | No | |
| numbers | No | |
| geometric_mean | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides no behavioral context beyond the minimal calculation intent; expects positive numbers but relies on schema for that detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, but could be improved by adding a brief usage note without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and output schema exists, the description lacks context about when to use geometric mean over sibling functions, resulting in adequate but not complete information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter (numbers) is fully described in the input schema, so the description adds no extra meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates geometric mean, but does not differentiate it from sibling tools like calculate_mean or harmonic_mean.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use geometric mean versus other averages, no when-not or alternative suggestions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_credit_card_patternBInspect
Get regex pattern for credit card validation.
| Name | Required | Description | Default |
|---|---|---|---|
| card_type | No | Type: visa, mastercard, amex, discover, any | any |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must fully disclose behavior. It does not mention that the tool returns a regex pattern string, handles multiple card types, or behaves for invalid input. The minimal description leaves significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. It is efficient but could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the schema covers the parameter, and an output schema exists. The description is adequate but minimal; it could mention the return type (regex string) for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the parameter 'card_type' described adequately in the input schema. The description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get regex pattern for credit card validation' clearly states the verb (Get) and resource (regex pattern for credit card validation). It distinguishes from sibling tools like 'validate_credit_card' (checks validity) and 'format_credit_card' (formats cards).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining regex patterns, but lacks explicit guidance on when to use this tool versus alternatives like 'validate_credit_card' or 'random_credit_card'. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_date_patternBInspect
Get regex pattern for date validation.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Format: ISO, US, EU | ISO |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It only states the basic purpose, omitting details like output format, parameter effects (format changes pattern), error handling, or any side effects. This is insufficient for an agent to understand how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise: a single sentence that front-loads the action. No unnecessary words, meeting the ideal of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and the tool's simplicity, the description is adequate but lacking. It does not explain that the returned pattern varies by format, nor does it specify what the pattern includes (e.g., delimiters, flags). The completeness is sufficient for a trivial tool but could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the 'format' parameter. The tool description adds no additional meaning beyond the schema, so it meets the baseline. No enrichment from the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Describes the action 'get' and the resource 'regex pattern' for 'date validation', making the purpose clear. However, it does not differentiate from sibling pattern tools like get_time_pattern or get_phone_pattern, so it lacks explicit sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like validate_date or other pattern tools. No prerequisites, context, or when-not-to-use information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_divisorsAInspect
Get all divisors of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to find divisors for |
Output Schema
| Name | Required | Description |
|---|---|---|
| sum | Yes | |
| count | Yes | |
| number | Yes | |
| divisors | Yes | |
| is_perfect | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only states the basic operation without disclosing any behavioral traits (e.g., return format, performance, edge cases like number=1). The schema already provides constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single concise sentence that conveys the tool's purpose without any unnecessary words. It is well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is sufficient. It clearly states the input and outcome, though it could briefly note the return type for added clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing complete parameter documentation. The description adds no extra meaning beyond the schema's description 'Number to find divisors for', so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get all divisors of a number' uses a specific verb ('Get') and resource ('divisors'), clearly stating the tool's function. It effectively distinguishes from siblings like prime_factors or gcd by specifying 'all divisors'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when needing divisors) but provides no explicit guidance on when not to use it or alternatives. With many math siblings, clearer when-to-use would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_email_patternCInspect
Get regex pattern for email validation.
| Name | Required | Description | Default |
|---|---|---|---|
| strict | No | Use strict RFC 5322 pattern |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden but only states the basic purpose. No disclosure of behavior beyond that, such as what pattern types are returned or how strict affects output.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise but lacks front-loaded structure with key info. It is not verbose but also not particularly valuable beyond the title.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description is too sparse given the many siblings. It does not help the agent understand the tool's role or when to prefer it over similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage for the strict parameter ('Use strict RFC 5322 pattern'). The tool description adds no further meaning, so score at baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get regex pattern for email validation' with a specific verb and resource. It distinguishes from siblings like validate_email and other get_*_pattern tools, though could be more explicit about the distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as validate_email or other pattern tools. The description does not provide any context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_hex_color_patternBInspect
Get regex pattern for hex color validation.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full load for behavioral disclosure. It only states the purpose but does not mention any behavioral traits such as the output format, regex flavor, or that it is a safe read-only operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extra words, making it concise. However, it could benefit from being slightly more detailed, but it is not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the presence of an output schema (not shown), the description lacks context about the returned pattern, such as its format or usage. For a pattern getter among many siblings, more information would be helpful for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100% (no params). The description does not need to add parameter information; a baseline of 4 is appropriate as it is sufficient for this case.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get regex pattern for hex color validation' uses a specific verb ('Get') and resource ('regex pattern for hex color validation'), clearly distinguishing it from sibling tools like validate_hex or is_valid_hex, which actually validate a hex color.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like is_valid_hex, validate_hex, or other pattern getters. No explicit context or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_initialsBInspect
Get initials from a name.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Name to get initials from | |
| separator | No | Separator between initials |
Output Schema
| Name | Required | Description |
|---|---|---|
| name | Yes | Original input name |
| initials | Yes | Extracted initials, optionally joined by separator |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description does not disclose behavior beyond the basic function. It does not explain how it handles edge cases (e.g., middle names, non-alphabetic characters) or the effect of the separator parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no wasted words. It is front-loaded and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity of the tool and the presence of an output schema, the description is minimally adequate but lacks details on handling special cases or formatting rules.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description adds minimal extra meaning beyond the schema, merely stating the overall purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get initials from a name' clearly states the action and resource. It is specific enough to distinguish from many sibling tools, though it does not explicitly differentiate from similar tools like 'generate_acronym'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'generate_acronym' or 'abbreviate'. The description lacks context on appropriate usage scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_ipv4_patternAInspect
Get regex pattern for IPv4 address validation.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It only states 'Get regex pattern', disclosing no behavioral traits such as idempotency, safety, or side effects. The tool is assumed read-only, but this is implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at six words, effectively communicating the tool's purpose without wasted content. It is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking usage guidance, the tool is simple with no parameters and has an output schema. The description adequately covers the core functionality, though a brief note on the pattern format (e.g., regex string) would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100%. The description adds no parameter details, but with zero parameters, the baseline is 4. No further clarification is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a regex pattern for IPv4 validation. The verb 'get' and resource 'regex pattern for IPv4 address validation' are specific, and the purpose is unambiguous. It naturally distinguishes from sibling tools like get_ipv6_pattern or get_email_pattern.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., validate_ip or other pattern tools). The description lacks context for appropriate usage scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_ipv6_patternAInspect
Get regex pattern for IPv6 address validation.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the tool returns a regex pattern. It does not disclose any behavioral traits, such as whether the pattern is case-sensitive or follows a specific standard.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and contains no unnecessary words. It perfectly meets the criteria for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and an output schema exists, the description is minimally adequate. However, it does not explain what form the pattern takes (e.g., string) or any return format details, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the schema coverage is 100% and the description adds no further meaning. A baseline score of 4 is appropriate since no additional detail is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'regex pattern for IPv6 address validation', making it unambiguous. It effectively distinguishes itself from sibling tools like get_ipv4_pattern.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context such as when IPv6 validation is needed or comparisons to similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_json_pathBInspect
Extract a value from JSON using a path expression.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Path to extract (e.g., 'user.address.city' or 'items[0].name') | |
| json_string | Yes | JSON string |
Output Schema
| Name | Required | Description |
|---|---|---|
| path | No | |
| type | No | |
| error | No | |
| found | No | |
| valid | No | |
| value | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose error handling, behavior with invalid paths or malformed JSON, or any limitations. With no annotations, the description should provide more behavioral context beyond the core function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no redundant words. Front-loaded with verb and resource. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and the output schema likely provides return details, the description lacks usage guidance and error transparency, making it incomplete for an agent to confidently invoke in all scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with clear parameter descriptions, so the description adds minimal extra value. The term 'path expression' is already implied by the examples in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool extracts a value from JSON using a path expression, which is a specific verb+resource. It differentiates from sibling JSON tools like 'get_json_type' or 'json_minify' by focusing on extraction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., 'get_keys', 'get_values', 'json_query'). A new user would not know the best tool for different JSON operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_json_typeCInspect
Get the type of a JSON value.
| Name | Required | Description | Default |
|---|---|---|---|
| json_string | Yes | JSON string |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | No | |
| error | No | |
| valid | No | |
| python_type | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavior beyond the basic purpose. It does not mention error handling for invalid JSON, the list of detectable types (e.g., string, number, object), or whether parsing occurs. This is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no extraneous information. It is front-loaded and efficient, though it could provide slightly more detail without significant bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (true), the description does not need to explain return values. However, the description is minimal and does not clarify what 'type' means in this context, leaving some ambiguity for a tool that could be used in various JSON processing scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a single parameter 'json_string' described as 'JSON string'. The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the type of a JSON value' clearly states the action (get) and the resource (type of JSON value), distinguishing it from siblings like json_minify or json_diff. However, it could be more specific about what types are returned.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as is_valid_json or json_stats. There is no context about prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_keysBInspect
Get all keys from a JSON object.
| Name | Required | Description | Default |
|---|---|---|---|
| json_string | Yes | JSON object string |
Output Schema
| Name | Required | Description |
|---|---|---|
| keys | No | |
| type | No | |
| error | No | |
| valid | No | |
| key_count | No | |
| all_keys_nested | No | |
| total_nested_keys | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavioral traits. It does not specify behavior on invalid JSON, non-object input, or whether nested keys are included (only top-level keys implied). Minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at 6 words, but could afford an extra sentence clarifying return format or input constraints. Not verbose, but lacks necessary detail for a complete tool description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and an output schema exists (assumed to explain return values). However, given the lack of annotations and many sibling JSON tools, the description should ideally guide usage or mention edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage for the single parameter, so baseline is 3. Description repeats the schema's description ('JSON object string') without adding additional meaning or examples.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action ('Get all keys') and the target resource ('a JSON object'). Distinguishes from sibling JSON tools like get_json_path and get_json_type, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., get_json_path for specific keys, flatten_json for nested structures). No when-not-to-use or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_luminanceBInspect
Calculate relative luminance of a color.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| is_dark | Yes | |
| is_light | Yes | |
| luminance | Yes | |
| recommended_text | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations available, the description carries the full burden of disclosing behavior. It fails to mention that the calculation follows the sRGB relative luminance formula, is idempotent, or any other side effects. The description is too minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is appropriately sized for a simple utility function, though slightly more context could be added without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is mostly sufficient but lacks completeness in not mentioning the formula or typical use cases (e.g., contrast ratio calculations).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameter hex_color is already described. The description adds no new semantic details beyond what the schema provides, leaving it at the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Calculate') and the resource ('relative luminance of a color'), making the tool's purpose unambiguous. It effectively distinguishes from sibling color tools by specifying a distinct metric.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., contrast_ratio, hex_to_rgb). There is no mention of prerequisites or context where luminance is relevant.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_nowBInspect
Get current date and time.
| Name | Required | Description | Default |
|---|---|---|---|
| tz | No | Timezone (UTC, America/New_York, etc.) | UTC |
Output Schema
| Name | Required | Description |
|---|---|---|
| day | Yes | |
| utc | Yes | |
| hour | Yes | |
| year | Yes | |
| month | Yes | |
| minute | Yes | |
| second | Yes | |
| timestamp | Yes | |
| day_of_week | Yes | |
| day_of_year | Yes | |
| timestamp_ms | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fails to disclose behavioral traits: timezone handling, server time basis, output format, or whether the result is a string or object. The minimal description leaves significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no waste. However, it could be slightly expanded to include key details without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter, the description is adequate but lacks context about the return value (output schema exists but not referenced). Could mention that it returns a datetime or timestamp.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (the 'tz' parameter is fully described in the schema), so the description adds no additional meaning. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get current date and time' clearly states the action and resource, distinguishing it from siblings like 'current_time' (likely just time) and date formatting tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'current_time', 'convert_timestamp', or 'format_date'. No prerequisites or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_password_patternBInspect
Get regex pattern for password validation with custom requirements.
| Name | Required | Description | Default |
|---|---|---|---|
| min_length | No | Minimum length | |
| require_digit | No | Require digit | |
| require_special | No | Require special character | |
| require_lowercase | No | Require lowercase | |
| require_uppercase | No | Require uppercase |
Output Schema
| Name | Required | Description |
|---|---|---|
| pattern | Yes | |
| description | Yes | |
| requirements | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description only says 'get regex pattern' without disclosing return format, side effects, or whether it generates or retrieves a pattern. Lacks behavioral details beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, and to the point. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Minimal description does not cover return value details (output schema exists but not described), edge cases, or relation to password validation tools. Inadequate for a tool with 5 optional parameters and a complex domain.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions (min_length, require_digit, etc.). Description adds 'custom requirements' but no additional parameter semantics beyond schema. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Get regex pattern for password validation with custom requirements', specifying the verb, resource, and purpose. It distinguishes from sibling tools like analyze_password or generate_password.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives (e.g., analyze_password, validate_password_strength). Missing context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_phone_patternAInspect
Get regex pattern for phone number validation.
| Name | Required | Description | Default |
|---|---|---|---|
| country | No | Country: US, UK, international | US |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It accurately describes a read-only operation (getting a pattern) with no side effects. The transparency is sufficient for this simple tool, though more details about edge cases (e.g., invalid country) could be added.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It effectively communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is mostly complete. It doesn't mention the return format, but context signals indicate an output schema exists. For a pattern retrieval tool, this is adequate, though specifying the pattern format or behavior with invalid input would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one optional parameter 'country' with a description listing possible values (US, UK, international). Schema coverage is 100%, so baseline is 3. The description adds value beyond the schema but lacks detail on how to use the parameter effectively.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get regex pattern for phone number validation' clearly states the action (Get), resource (regex pattern), and purpose (phone number validation). It distinguishes itself from sibling tools like validate_phone, format_phone, and generate_phones by focusing on retrieving the pattern rather than applying it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives like validate_phone or format_phone. Usage is implied (you need the pattern), but no when-not or context clues are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_quarterCInspect
Get the quarter for a date.
| Name | Required | Description | Default |
|---|---|---|---|
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| quarter | No | |
| datetime | No | |
| quarter_end | No | |
| quarter_name | No | |
| quarter_start | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does not disclose edge cases, input validation behavior, or output format (e.g., returns 1-4 or 'Q1'). The word 'quarter' is ambiguous without definition. Minimal behavioral insight beyond the operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence with zero waste. However, its extreme brevity sacrifices detail needed for full understanding. It is concise but not optimally informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple function, the description is adequate but lacks explanation of output semantics and quarter definition. The presence of an output schema is noted but not described. Siblings are many, and more context could help differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the parameter. The description adds no extra meaning beyond what the schema provides ('Datetime in ISO format'). Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool extracts the quarter from a date, matching the name and resource. However, it does not explicitly differentiate from sibling date tools like 'day_of_year' or 'days_in_month', though the purpose is evident.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites or exclusions. The description simply states the function without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_slug_patternAInspect
Get regex pattern for URL slug validation.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states the function without any details about the pattern's characteristics (e.g., character set, length limits, Unicode support). This is insufficient for an agent to understand what the regex actually validates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise, front-loaded, and devoid of unnecessary words. Every token earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, has output schema), the description is minimally adequate. However, it could be more complete by explicitly stating that it returns a string regex pattern. The output schema likely covers that, but the description leaves room for ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100% (empty schema). Baseline for 0 parameters is 4. The description adds no parameter info, which is acceptable since there are none.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool returns a regex pattern for URL slug validation using the verb 'Get' and specific resource 'regex pattern for URL slug validation'. It distinguishes itself from sibling pattern getters (e.g., get_email_pattern, get_phone_pattern) by specifying 'slug'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when you need a regex pattern for slug validation), but does not explicitly state when to use this tool versus alternatives like is_valid_slug or other pattern getters. No when-not-to-use or exclusions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_time_patternBInspect
Get regex pattern for time validation.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Format: 24h, 12h | 24h |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must cover behavioral traits. It does not disclose what the regex pattern looks like, whether it supports both formats, or any limitations. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately concise for a simple tool, though it could be slightly more detailed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, an output schema likely exists to explain the return value, and the description combined with the schema provides sufficient context. However, it could mention that it returns a regex string.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'format', which already has a description. The tool description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'regex pattern for time validation', which distinguishes it from sibling pattern tools like 'get_date_pattern' or 'get_email_pattern'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as other pattern tools or time-related tools. The description does not mention any context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_url_patternBInspect
Get regex pattern for URL validation.
| Name | Required | Description | Default |
|---|---|---|---|
| require_protocol | No | Require http/https protocol |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description is minimal with no behavioral details beyond basic purpose; no annotations and no mention of return format or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and efficient, but could benefit from slightly more structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple tool with one optional param and output schema, but lacks detail on the pattern's specifics and behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema fully documents the single parameter 'require_protocol'; description adds no extra semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it retrieves a regex pattern for validating URLs, distinguishing it from other pattern tools like get_email_pattern or validation tools like validate_url.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives; implied by name but lacks context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_uuid_patternBInspect
Get regex pattern for UUID validation.
| Name | Required | Description | Default |
|---|---|---|---|
| version | No | Version: 1, 4, any | any |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | No | |
| format | No | |
| strict | No | |
| country | No | |
| pattern | Yes | |
| version | No | |
| examples | No | |
| card_type | No | |
| description | No | |
| case_insensitive | No | |
| require_protocol | No | |
| format_description | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states what the tool does without explaining behavioral traits. No annotations exist, so the description bears full responsibility. It does not mention that the tool is read-only, what format the returned regex follows, or any side effects. Minimal disclosure beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence that efficiently conveys the tool's purpose. Every word earns its place, and it is front-loaded with the key action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (covering return values), the description need not detail output. However, the tool has many siblings and a simple description may not fully prepare an agent. It is adequate but minimal, missing context like supported UUID versions or default behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for its single parameter (version), and the schema already documents its purpose. The description adds no extra meaning beyond the schema, which aligns with the baseline score of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get regex pattern for UUID validation' clearly states the action (Get), the resource (regex pattern), and the context (for UUID validation). It effectively distinguishes this tool from siblings like get_date_pattern or get_email_pattern by specifying UUID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling pattern tools (e.g., get_date_pattern, get_ipv4_pattern), the description lacks context for selection, such as noting that this tool is for UUID-specific validation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_valuesCInspect
Get all values from a JSON object.
| Name | Required | Description | Default |
|---|---|---|---|
| json_string | Yes | JSON object string |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | No | |
| count | No | |
| error | No | |
| valid | No | |
| values | No | |
| value_types | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It states 'get all values' but does not specify return structure (e.g., list, order), handling of nested objects, or error conditions for invalid input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words. It is concise but may be too brief; however, conciseness measures lack of waste, and this achieves that effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (1 param) and existing output schema, the description is still too sparse. It fails to address common edge cases (e.g., non-object input, nested values) and does not leverage context from siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters (json_string described as 'JSON object string'). The description adds marginal value by implying the parameter should be a JSON object and output is 'all values', but does not explain format or validation details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'get' and resource 'all values from a JSON object', indicating it extracts values. However, it does not distinguish from siblings like 'get_keys' (which gets keys) or 'flatten_json' (which flattens nested structures).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Despite many sibling tools that handle JSON or arrays, the description lacks any context about appropriate usage scenarios or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
grams_to_ouncesAInspect
Convert grams to ounces.
| Name | Required | Description | Default |
|---|---|---|---|
| grams | Yes | Weight in grams |
Output Schema
| Name | Required | Description |
|---|---|---|
| grams | Yes | |
| ounces | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It fails to disclose precision, rounding behavior, or return format. For a conversion tool, this leaves the agent guessing about exact results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (3 words, 1 sentence) with no wasted words. For a simple conversion, this is appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the existence of an output schema (not shown but implied), the description is nearly complete. It lacks behavioral details but covers the essential intent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (single parameter 'grams' described). The description adds no extra meaning beyond the schema, aligning with the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert grams to ounces' uses a specific verb and resource, clearly distinguishing it from siblings like 'ounces_to_grams' and other unit conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool vs alternatives. While the purpose is clear, it could benefit from mentioning that it handles one-way conversion, especially given the existence of 'ounces_to_grams'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
grayscale_colorAInspect
Convert color to grayscale.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color to convert to grayscale |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| grayscale | Yes | |
| luminance | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
As a pure conversion function, the description adequately states what it does, but does not mention any edge cases, valid input range, or return format. With no annotations, the description carries the full burden and offers minimal extra context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is clear and to the point, with no extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, no side effects, pure conversion), the description is complete enough. The presence of an output schema means return values need not be described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'hex_color' is fully described in the input schema (100% coverage). The description adds no additional semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Convert') and resource ('color to grayscale'), clearly distinguishing it from sibling tools like darken_color, lighten_color, and saturate_color.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as desaturate_color or analogous_colors. The description provides no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
group_by_lengthBInspect
Group items by their string length.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| grouped | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits, but it only states the core function, omitting details like how groups are structured, handling of empty strings, or whether ordering is preserved.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words, but it could include a bit more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, which likely documents return values, but the description does not mention output structure (e.g., map of lengths to arrays) or edge cases, leaving gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the parameter with 100% description, but the tool description adds no extra meaning beyond 'comma-separated items', which is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Group items') and the criterion ('by their string length'), making it specific and distinct from siblings like sort_items or chunk_array.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor are there any scenario-based recommendations or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
harmonic_meanCInspect
Calculate harmonic mean.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated positive numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| count | No | |
| error | No | |
| numbers | No | |
| harmonic_mean | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description should disclose behavioral traits. It only states the operation, with no mention of edge cases (e.g., handling of non-positive numbers), output format, or required permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two words) with no wasted text. However, it could benefit from a sentence or two to improve clarity without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of many sibling tools (e.g., geometric_mean, average), the description lacks context about when harmonic mean is appropriate. An output schema exists, but the description does not explain return values or typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with a clear parameter description ('Comma-separated positive numbers'). The tool description adds no additional meaning, but the schema already suffices, earning the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate harmonic mean' clearly states the verb and resource, specifying the exact type of mean. However, it does not differentiate from sibling tools like geometric_mean or average, though the name itself distinguishes it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of context, exclusions, or comparisons with other mean calculations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_adler32CInspect
Calculate Adler-32 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to calculate Adler-32 |
Output Schema
| Name | Required | Description |
|---|---|---|
| algorithm | Yes | |
| checksum_hex | Yes | |
| input_length | Yes | |
| checksum_decimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only says 'Calculate Adler-32 checksum.' It does not disclose that it returns a 32-bit integer, is deterministic, or any other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is very concise (one sentence) and front-loaded. It is appropriately sized for a simple tool, though not structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists (signal indicates true), the description does not need to explain return values. For a simple hash tool, the description is adequately complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, but the tool description adds no additional meaning beyond what is already in the schema. The parameter 'text' is self-explanatory from the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Calculate Adler-32 checksum' with a specific verb and resource. It differentiates from sibling hash functions mainly by name, but the description is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like hash_crc32 or hash_md5. The description does not provide context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_allAInspect
Generate hashes using multiple algorithms at once.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hashes | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It only says 'generate hashes using multiple algorithms at once' without disclosing which algorithms, output format, or any other behavioral details like input constraints or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that communicates the core functionality without any wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of many sibling hash tools and an output schema, the description is too minimal. It could specify the list of algorithms or output structure, but the output schema might compensate. Still, the description alone lacks completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter 'text' adequately described in the schema. The tool description adds no extra semantic meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and the resource 'hashes', and distinguishes from siblings by specifying 'using multiple algorithms at once', which sets it apart from single-algorithm hash tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for obtaining multiple hash algorithms simultaneously, but it does not explicitly state when to use this tool versus individual hash tools, or provide any alternative guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_blake2bCInspect
Generate BLAKE2b hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash | |
| digest_size | No | Digest size in bytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose key behaviors (e.g., one-way hash, deterministic, output format). It only states the operation, omitting whether it's cryptographic, side effects, or performance. Existence of output schema mitigates missing return details but not behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. However, it lacks structure (e.g., separated sections) and could include more context without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a hash function with an output schema and sibling tools, the description is minimal. It doesn't explain the output format (e.g., hex) or the significance of digest_size beyond schema. Missing details for an agent to fully understand usage without inspecting the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no extra meaning beyond the schema's field descriptions. Baseline of 3 is appropriate as the tool has two parameters and the description doesn't enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate') and the resource ('BLAKE2b hash of text'). It distinguishes from sibling hash tools by specifying the algorithm, but could be more precise by noting it's a cryptographic hash.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other hash algorithms (e.g., SHA-256, MD5). No mention of when not to use or alternatives, leaving the agent without selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_blake2sBInspect
Generate BLAKE2s hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash | |
| digest_size | No | Digest size in bytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose behavioral traits such as deterministic output, performance characteristics, or security properties. The customizable digest size is not highlighted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. However, it could be slightly more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so return value details are covered. Given the simplicity of the operation and schema coverage, the description is minimally complete but could benefit from mentioning the output format or typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters ('text' and 'digest_size'). The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the action ('Generate'), the algorithm ('BLAKE2s'), and the input ('text'). It clearly distinguishes from sibling hash tools like hash_md5 or hash_sha256 by naming the specific algorithm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use BLAKE2s over other hash algorithms (e.g., security, speed trade-offs). No alternatives or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_crc32CInspect
Calculate CRC32 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to calculate CRC32 |
Output Schema
| Name | Required | Description |
|---|---|---|
| algorithm | Yes | |
| checksum_hex | Yes | |
| input_length | Yes | |
| checksum_decimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It only states the basic function. It does not mention that the operation is read-only, deterministic, or what the output range is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (5 words) and front-loaded with the core purpose. However, it could be more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple checksum tool with an output schema, the description is minimally adequate but lacks details about output format or any nuances. It could be more helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the single parameter adequately. The description adds no extra meaning beyond 'Text to calculate CRC32'. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (calculate) and the specific resource (CRC32 checksum). However, it does not differentiate from the sibling tool 'crc32_checksum', which likely performs the identical function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives, such as other hash functions like md5 or sha256, or the sibling crc32_checksum. The description lacks any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_md5BInspect
Generate MD5 hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It fails to mention that MD5 is cryptographically broken, that the hash is deterministic, or the output format (hex string). This lack of transparency is significant for a cryptographic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, efficiently conveying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. However, it lacks any behavioral or security context that would be helpful for an AI agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'text' described as 'Text to hash'. The description adds no additional meaning beyond the schema, warranting the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate MD5 hash of text' clearly states the specific verb (generate) and resource (MD5 hash), and the name itself identifies the algorithm. It distinguishes itself from other hash siblings by specifying the exact hash function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like hash_sha256 or generate_hash. The description offers no context for selection among the many sibling hash tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_sha1BInspect
Generate SHA-1 hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states the operation without mentioning irreversibility, determinism, output format, or performance characteristics. This is insufficient for a hash function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at 6 words. It is front-loaded and to the point, though it could potentially include slightly more information without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool being simple with one parameter and an output schema, the description does not clarify the output format (e.g., hex string) or how it compares to sibling hash tools. This leaves ambiguity about the exact result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes the parameter as 'Text to hash'. The description adds no extra meaning beyond that, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate') and the specific resource ('SHA-1 hash of text'). It distinguishes this tool from siblings like hash_sha256, hash_md5, etc., by naming the exact algorithm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use SHA-1 versus other hashing algorithms, no caveats about security (SHA-1 is deprecated for cryptographic use), and no mention of alternatives among the many sibling hash tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_sha256BInspect
Generate SHA-256 hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose any behavioral traits such as determinism, performance, or side effects. It only states the basic operation without additional context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, no unnecessary words, and front-loaded with the essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple hashing tool with an output schema, the description is minimally adequate. However, given the large number of sibling hash tools, more context (e.g., when to use SHA-256) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'text' described as 'Text to hash'. The description adds no extra meaning beyond what the schema provides, so it meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Generate SHA-256 hash' and the resource 'text', distinguishing it from sibling hash functions like sha1 or sha512 by specifying the exact algorithm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use SHA-256 over other hash functions (e.g., SHA-1, MD5) or alternatives. The description does not mention any criteria for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_sha3_256BInspect
Generate SHA3-256 hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must fully disclose behavior. It only states the operation, missing details like output format (hex string), idempotency, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, no wasted words, concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple hash function with an output schema, but could be more helpful by explicitly noting the hex string output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'text', so the description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and resource 'SHA3-256 hash of text', distinguishing it from sibling hash functions like hash_sha256, hash_sha512, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. With many sibling hash tools, explicit selection criteria would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_sha3_512BInspect
Generate SHA3-512 hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states only that a hash is generated, omitting key details such as the output format (e.g., hex-encoded string), deterministic nature, or any side effects. The presence of an output schema is noted, but the description itself adds minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. Every word earns its place, making it highly efficient for a simple hash tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description is minimally complete. However, it fails to mention the return format (e.g., hex string) or edge cases, which would be valuable for an agent. It adequately conveys the core function but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage: one required string parameter 'text' with description 'Text to hash'. The tool description does not add additional meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate SHA3-512 hash of text' clearly states the action (generate) and the specific hash algorithm (SHA3-512), distinguishing it from other hash tools by algorithm name. However, it does not further differentiate from siblings like hash_sha3_256 or hash_sha512 beyond the name, relying on the tool name for full distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternative hash tools (e.g., hash_sha256, hash_md5) or other siblings like generate_hash or identify_hash. The description lacks any context for selection, exclusions, or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_sha384BInspect
Generate SHA-384 hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries the full burden. It states 'Generate SHA-384 hash' but does not disclose any behavioral traits such as determinism, performance characteristics, or potential side effects. The description is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of a single, front-loaded sentence with no extraneous words. It is as concise as possible while conveying the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no enums, output schema present), the description is adequate but lacks context on usage and behavioral details. For a hash function among many siblings, more guidance would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'text' has a schema description 'Text to hash' and coverage is 100%. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Generate' and the resource 'SHA-384 hash of text'. It is specific about the algorithm, distinguishing it from sibling hash tools like hash_sha256 or hash_sha1.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this hash function over alternatives (e.g., SHA-256 or SHA-512). The description does not mention use cases, security levels, or any selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hash_sha512BInspect
Generate SHA-512 hash of text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| algorithm | Yes | |
| digest_size | No | |
| hash_length | Yes | |
| input_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It only states the basic operation but does not mention that the output is deterministic, returns a hex string of fixed length (128 characters), or how it handles empty input. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It does not front-load key information like output format or behavioral guarantees. While not verbose, it could be more informative without adding length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool and the presence of an output schema (indicated), the description is adequate but minimal. It does not mention that the hash is hex-encoded or provide context for choosing this algorithm among many sibling hash tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage for the single parameter 'text', with a clear description 'Text to hash'. The description adds no additional meaning beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Generate) and the specific resource (SHA-512 hash of text). It distinguishes this tool from sibling hash tools by specifying the algorithm SHA-512, which is a specific and recognized hash function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use SHA-512 vs other hash algorithms or alternative tools like hash_sha256, hash_blake2b, etc. The description lacks context on when this tool is appropriate, such as for high-security hashing needs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
haversine_distanceCInspect
Calculate distance between two coordinates using Haversine formula.
| Name | Required | Description | Default |
|---|---|---|---|
| lat1 | Yes | Latitude of point 1 | |
| lat2 | Yes | Latitude of point 2 | |
| lon1 | Yes | Longitude of point 1 | |
| lon2 | Yes | Longitude of point 2 | |
| unit | No | Unit: km or mi | km |
Output Schema
| Name | Required | Description |
|---|---|---|
| unit | Yes | |
| point1 | Yes | |
| point2 | Yes | |
| distance | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only mentions the formula, but does not state return units, error handling, or validation beyond what the schema provides (e.g., range limits).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core purpose without excess words. However, it could benefit from slightly more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and many sibling tools, the description should provide more context about return format and when this tool is preferred. It is too minimal for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with descriptions for each parameter. The description adds no additional semantic value beyond the schema, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates distance between two coordinates using the Haversine formula. This is a specific verb and resource, but it does not distinguish from sibling tools like 'distance' or 'calculate_bearing', which may also compute distances.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'distance' or 'bounding_box'. There is no mention of constraints or use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
heart_rate_zonesCInspect
Calculate heart rate training zones.
| Name | Required | Description | Default |
|---|---|---|---|
| age | Yes | Age in years | |
| resting_hr | No | Resting heart rate (optional) |
Output Schema
| Name | Required | Description |
|---|---|---|
| age | Yes | |
| zones | Yes | |
| method | Yes | |
| max_heart_rate | Yes | |
| resting_heart_rate | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It merely states the calculation without mentioning that it is non-destructive, requires no side effects, or any other behavioral traits. The phrase 'calculate heart rate training zones' implies a read-only operation, but this is not explicit, and no further context is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core purpose. It is efficient with no wasted words. However, given the simplicity of the tool, more depth could be added without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (exists but not shown), which may clarify return values, but the description itself is too terse. It fails to mention common outputs like zone thresholds or percentages, leaving users uncertain about what the result contains. For a calculation tool with two parameters, more guidance is needed to ensure proper use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters (age and resting_hr), so the schema already documents their meaning. The tool description adds no additional semantics beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('calculate') and resource ('heart rate training zones'). It is specific and distinct from sibling tools like 'calculate_bmi' or 'calculate_bmr'. However, it does not elaborate on what heart rate training zones are, leaving some ambiguity for users unfamiliar with the concept.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor does it mention prerequisites or limitations. Users are left to infer usage from the parameter names alone. Sibling tools like 'calculate_bmr' and 'calculate_macros' share similar health contexts, but no differentiation is offered.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hello_worldBInspect
Hello World as a Service.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Name to greet | World |
Output Schema
| Name | Required | Description |
|---|---|---|
| message | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any behavioral traits beyond the obvious (producing a greeting). No annotations are provided to supplement. There is no mention of idempotency, side effects, or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence. It is front-loaded and to the point, but lacks depth. For a trivial tool this is acceptable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description provides adequate context for its basic purpose. Additional details about return format or edge cases are not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the single parameter. The description adds no additional meaning beyond the schema's description. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Hello World as a Service.' clearly states the tool produces a greeting. It is distinguishable from sibling tools which are specific utilities (e.g., math, string manipulation). However, it could be more specific about the output format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Among many siblings, there is no differentiation or context for when a simple greeting is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hexadecimal_to_decimalBInspect
Convert hexadecimal to decimal.
| Name | Required | Description | Default |
|---|---|---|---|
| hexadecimal | Yes | Hexadecimal number string |
Output Schema
| Name | Required | Description |
|---|---|---|
| decimal | Yes | |
| hexadecimal | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits, such as output format, error handling, or assumptions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise but overly minimal; it could include more useful details like output format without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity and presence of an output schema, the description lacks additional context about the conversion process or assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the description adds no extra meaning beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'hexadecimal to decimal', distinguishing it from sibling tools like 'decimal_to_hexadecimal'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no prerequisites or exclusions mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hex_decodeBInspect
Decode hexadecimal to text.
| Name | Required | Description | Default |
|---|---|---|---|
| encoded | Yes | Hex string to decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| decoded | No | |
| encoded | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like input format handling (e.g., case sensitivity, spaces) and encoding assumptions, but it does not. This leaves important edge cases unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no waste, but it could be slightly expanded to include key details without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description is largely adequate but misses some contextual details about input validation and output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool description adds no extra meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Decode hexadecimal to text.' uses a specific verb and resource, clearly distinguishing from siblings like hex_encode and base64_decode. It succinctly states the core function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., base64_decode, binary_decode) or when not to use it. The description lacks contextual direction for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hex_encodeBInspect
Encode text to hexadecimal.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hex encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| encoded | Yes | |
| original | Yes | |
| encoded_upper | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states 'encode' but lacks details on character encoding (e.g., UTF-8), hex case, prefix, reversibility, or whether whitespace is preserved. Minimal behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no waste, but slightly under-specified. Could include output format or input constraints without losing conciseness. Acceptable but not optimally informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity and presence of an output schema, the description is minimally adequate. However, among many encoding siblings, more context (e.g., 'Outputs lowercase hex string without prefix') would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description 'Text to hex encode'. The tool description adds no extra meaning beyond the schema, which is adequate but not enhanced. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Encode text to hexadecimal' uses a specific verb and resource, clearly stating the operation and output format. It distinguishes from sibling tools like 'hex_decode' (inverse) and other encoding tools (e.g., 'base64_encode'). No tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'ascii_encode' or 'base64_encode'. There are no exclusions, prerequisites, or context hints. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hex_to_cmykAInspect
Convert hex color to CMYK.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color (e.g., #FF5733 or FF5733) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| cmyk | Yes | |
| cmyk_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose error handling, case sensitivity, or prefix handling (though the parameter description in schema does this). The basic behavior is conversion, which is transparent enough for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words. It is concise and front-loaded with the essential action and target.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool, the description is adequate. It states the core function, and the output schema (though not visible) likely defines the return format. It does not detail intermediate steps or edge cases, but the simplicity of the tool mitigates this.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage for the single parameter, with an example provided. The tool description adds no additional parameter information beyond what the schema already provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb 'Convert' and resource 'hex color to CMYK'. It is unambiguous and easily distinguishable from sibling color conversion tools like hex_to_rgb or hex_to_hsl.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives is provided. The context is clear due to the distinct output format (CMYK), but there is no mention of prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hex_to_hslBInspect
Convert hex color to HSL.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color (e.g., #FF5733 or FF5733) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| hsl | Yes | |
| hsl_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It does not mention behavioral traits like expected input format (though schema helps), return value format, or any side effects. The description is too minimal for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words, perfectly front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite being a simple conversion, the description lacks information about the output format (e.g., HSL object) and any edge cases. With no output schema in the description, and many sibling tools, the description is insufficiently complete for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'hex_color', which is already well-documented in the schema. The description adds no additional meaning beyond what the schema provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert hex color to HSL.' clearly states the verb (convert), resource (hex color), and target (HSL), making the purpose unmistakable. It distinguishes from sibling tools like hex_to_rgb and rgb_to_hsl.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. However, the conversion is straightforward and context is clear enough from the description and input schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hex_to_hsvBInspect
Convert hex color to HSV.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color (e.g., #FF5733 or FF5733) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| hsv | Yes | |
| hsv_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description fails to disclose behavioral traits such as validation, error handling, or output structure. It only repeats the conversion intent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, perfectly concise and front-loaded. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema and simple input, the description is minimally sufficient. However, it lacks any usage context that could help select among many sibling color tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes the parameter 'hex_color' with examples. The tool description adds no extra meaning, so baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert hex color to HSV' clearly states the verb (convert), resource (hex color), and target format (HSV). It distinguishes from sibling color converters like hex_to_hsl, hex_to_rgb, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like hex_to_hsl or hex_to_rgb. The description lacks context on prerequisites or output interpretation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hex_to_rgbAInspect
Convert hex color to RGB.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color (e.g., #FF5733 or FF5733) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| rgb | Yes | |
| rgb_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must convey behavior. It accurately describes a simple conversion without hidden side effects. Doesn't mention error handling but is transparent for a pure function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (not shown), the description doesn't need to detail return values. For a simple tool, the description is adequate, but could briefly mention expected output format for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The tool description adds no additional meaning beyond the parameter description, which already explains the hex format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool converts hex color to RGB, using a specific verb and resource. It distinguishes from sibling tools like hex_to_hsl, hex_to_cmyk, etc., which target different color models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. However, the purpose is clear, and implied usage for RGB conversion is understandable given sibling tools have distinct outputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hmac_md5AInspect
Generate HMAC-MD5.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Secret key | |
| message | Yes | Message to authenticate |
Output Schema
| Name | Required | Description |
|---|---|---|
| algorithm | Yes | |
| signature | Yes | |
| message_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits but adds nothing beyond the tool name. Important details like input encoding, output format, or security considerations are omitted, which is concerning for a cryptographic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the verb and resource. No redundant information; every word is essential.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema exists and parameters are simple, the description lacks context about when to choose HMAC-MD5 over siblings, input encoding expectations, or output format. For a crypto tool, this is somewhat lacking but not critically incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear parameter descriptions ('Secret key', 'Message to authenticate'). The tool description adds no additional meaning beyond what the schema provides, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate HMAC-MD5', specifying the exact operation and algorithm. This distinguishes it from sibling tools like hash_md5 or hmac_sha256.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives. The description is minimal and does not mention context or exclusions, leaving the agent to infer usage solely from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hmac_sha256BInspect
Generate HMAC-SHA256.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Secret key | |
| message | Yes | Message to authenticate |
Output Schema
| Name | Required | Description |
|---|---|---|
| algorithm | Yes | |
| signature | Yes | |
| message_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits like determinism, error handling, or output format. It only states the generic purpose, missing details that would help the agent understand side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that efficiently conveys the tool's purpose. It avoids unnecessary words, making it easy to parse, though it could be expanded slightly without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of a cryptographic function, the description combined with a fully described input schema and an output schema provides adequate completeness. However, it lacks any additional context about security or algorithm nuances that could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides full descriptions for both parameters (key and message). The description adds no additional meaning beyond what the schema offers, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool generates HMAC-SHA256, a specific cryptographic function. It distinguishes itself from siblings like generate_hmac, hmac_md5, and hmac_sha512 by specifying the exact algorithm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus HMAC with other algorithms or plain hashing. Does not mention any prerequisites or context for use, leaving the agent without decision-making support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hmac_sha512BInspect
Generate HMAC-SHA512.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Secret key | |
| message | Yes | Message to authenticate |
Output Schema
| Name | Required | Description |
|---|---|---|
| algorithm | Yes | |
| signature | Yes | |
| message_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states the operation without describing what the tool does beyond the bare minimum (e.g., no mention of input validation, error handling, or output format).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with only one sentence, no wasted words. However, it may be too terse, sacrificing completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and two simple parameters, the description provides minimal context. For a cryptographic tool, additional details about usage context and behavior would be beneficial, but the schema partially compensates.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both key and message have descriptions). The description adds no extra meaning beyond the schema, achieving the baseline score. No additional parameter context is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate HMAC-SHA512' clearly states the verb (Generate) and the specific resource (HMAC-SHA512), making the tool's purpose immediately obvious. It differentiates from sibling HMAC and hash tools by naming the algorithm.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use HMAC-SHA512 vs other cryptographic tools (e.g., hmac_sha256, hmac_md5). No alternatives or when-not-to-use scenarios are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hours_to_minutesAInspect
Convert hours to minutes.
| Name | Required | Description | Default |
|---|---|---|---|
| hours | Yes | Time in hours |
Output Schema
| Name | Required | Description |
|---|---|---|
| hours | Yes | |
| minutes | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description only states the conversion action. It does not disclose behavior for edge cases (e.g., negative hours, very large numbers). However, for a simple mathematical operation, the default assumption of no side effects is reasonable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, no wasted words, front-loaded with essential information. Perfectly concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's extreme simplicity and the presence of an output schema (not shown but indicated), the description is nearly complete. Missing details like return type are likely covered by schema. Minor gap: no mention of input constraints or rounding behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema describes the 'hours' parameter as 'Time in hours' with 100% coverage. The description adds no extra meaning beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert hours to minutes' clearly states the verb and resource. It is unambiguous but does not differentiate from sibling conversion tools like 'minutes_to_seconds' which also follow the 'Convert X to Y' pattern.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. However, due to the straightforward nature of the conversion and unique pairing of units, the implication is clear. The description could briefly mention that it is for single hour-to-minute conversions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hsl_to_hexCInspect
Convert HSL to hex color.
| Name | Required | Description | Default |
|---|---|---|---|
| h | Yes | Hue (0-360) | |
| l | Yes | Lightness (0-100) | |
| s | Yes | Saturation (0-100) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| hsl | Yes | |
| rgb | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the conversion operation, omitting details such as handling of out-of-range values, rounding behavior, or output format. This is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at 5 words, front-loading the core purpose. Every word contributes, though it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. However, it lacks completeness in terms of usage context and edge cases, and the sibling list suggests a need for differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add extra meaning beyond the schema. While the schema already documents ranges, the description could clarify conversion specifics like whether hue is interpreted as degrees, but it does not. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Convert HSL to hex color' with a clear verb and resource. However, it does not differentiate from sibling color conversion tools like rgb_to_hex, hsv_to_hex, etc., which slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over its siblings. In a context with many similar color conversion tools, the description lacks any contextual advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hsv_to_hexBInspect
Convert HSV to hex color.
| Name | Required | Description | Default |
|---|---|---|---|
| h | Yes | Hue (0-360) | |
| s | Yes | Saturation (0-100) | |
| v | Yes | Value (0-100) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| hsv | Yes | |
| rgb | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should disclose behaviors like rounding, error handling, or output format. It only states 'convert' with no further details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that effectively communicates the tool's purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with well-documented parameters and an output schema, so the minimal description is acceptable. However, it could mention that output is a hex string.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents all parameters with descriptions and ranges. The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Convert) and the transformation (HSV to hex color). It distinguishes from siblings like hex_to_hsv and hsl_to_hex through the specific color space.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not indicate when to use this tool over alternatives, such as using hsl_to_hex for HSL input or hex_to_hsv for the reverse conversion.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
html_decodeAInspect
HTML decode text (unescape special characters).
| Name | Required | Description | Default |
|---|---|---|---|
| encoded | Yes | HTML encoded string to decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| decoded | Yes | |
| encoded | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It states it decodes HTML entities, which is the core behavior, but does not mention limitations, edge cases (e.g., unsupported entities), or side effects. This is minimally adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no extraneous words. It front-loads the purpose and adds a clarifying parenthetical, making it highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema (implied), so the description provides basic completeness. However, it lacks any contextual details about usage, such as examples or common scenarios, making it only adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'encoded', which already has a clear description. The tool description does not add additional meaning beyond restating the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('HTML decode') and the resource ('text'), with a parenthetical explanation ('unescape special characters') that makes the purpose unambiguous. Among siblings like 'html_encode', it is easily distinguishable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., 'html_encode', 'url_decode'). The description does not indicate appropriate contexts or excluded use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
html_encodeBInspect
HTML encode text (escape special characters).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to HTML encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| encoded | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must fully disclose behavior. It states 'escape special characters' but does not specify which characters are escaped (e.g., <, >, &, ", '), whether double encoding occurs, or any side effects. This is minimal for a transformation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, concise and front-loaded. It contains no unnecessary words, but it could be slightly more informative. Still, it is well-structured for its simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no enums, output schema present), the description is adequate but not thorough. It does not explain the return format (encoded string) or edge cases, but the output schema likely covers that. It feels minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with one parameter 'text' described as 'Text to HTML encode'. The tool description adds 'escape special characters' which is redundant with the schema. Baseline 3 is appropriate as the schema already provides adequate semantic meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'HTML encode text (escape special characters).' It uses a specific verb ('HTML encode') and a clear resource ('text'), and it distinguishes this tool from siblings like 'html_decode' and other encoding tools (e.g., url_encode, base64_encode) by specifying HTML encoding and escaping special characters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks any guidance on when to use this tool versus alternatives. It does not mention prerequisites, when not to use, or which alternative tool might be more appropriate. For example, it does not contrast with html_decode or url_encode.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
http_method_infoBInspect
Get information about an HTTP method.
| Name | Required | Description | Default |
|---|---|---|---|
| method | Yes | HTTP method |
Output Schema
| Name | Required | Description |
|---|---|---|
| safe | No | |
| error | No | |
| method | Yes | |
| has_body | No | |
| cacheable | No | |
| idempotent | No | |
| description | No | |
| known_methods | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It fails to disclose any behavioral traits such as whether the tool is read-only, what 'information' includes, or any side effects. This is inadequate for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded. Every word earns its place with no wasted space.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description need not explain return values. However, it lacks context about the output's nature or examples. For a simple tool with one parameter, it is minimally adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the single parameter. The description adds no additional meaning beyond 'HTTP method', which is already in the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states the tool gets information about an HTTP method, which is clear and specific. However, it does not explicitly differentiate from siblings like status_code_info or port_info, though the resource type distinguishes it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description implies use when needing HTTP method info but provides no exclusions or context for selecting it over similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
hypotenuseAInspect
Calculate the hypotenuse of a right triangle.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | Length of side a | |
| b | Yes | Length of side b |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | Yes | |
| b | Yes | |
| hypotenuse | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description fails to disclose behavioral traits such as acceptance of non-positive numbers, edge cases (e.g., zero or negative lengths), or output format. For a simple tool, more transparency is expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, two parameters, full schema coverage, and assumed output schema, the description is largely complete. It lacks explicit mention of unit assumptions or constraints but adequately conveys purpose for a standard mathematical function.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters ('Length of side a' and 'Length of side b'), so baseline is 3. The description adds no additional meaning beyond the schema, meeting the minimum but not exceeding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate the hypotenuse of a right triangle' clearly states the verb (calculate) and resource (hypotenuse of a right triangle), distinguishing it from sibling tools like add or square_root by naming a specific geometric calculation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage via the tool name, but lacks explicit guidance on when to use versus alternatives like Pythagoras theorem or when inputs are invalid (e.g., non-positive lengths). No exclusions or prerequisites are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ideal_weightCInspect
Calculate ideal body weight using various formulas.
| Name | Required | Description | Default |
|---|---|---|---|
| sex | Yes | Sex: male or female | |
| height_cm | Yes | Height in centimeters |
Output Schema
| Name | Required | Description |
|---|---|---|
| sex | Yes | |
| height_cm | Yes | |
| ideal_weight_kg | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only says 'using various formulas' without explaining which formulas, how they are selected, or any side effects or requirements. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it sacrifices necessary detail. It is concise but under-informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description fails to mention how the result is presented or which formulas are used. Important context about formula selection and result interpretation is missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers both parameters with descriptions, achieving 100% coverage. The description adds no extra meaning beyond implying that the calculation depends on height and sex. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates ideal body weight, which is specific. However, it does not differentiate from sibling tools like calculate_bmi or estimate_body_fat, and 'various formulas' is vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as calculate_bmi or calculate_bmr. There are no prerequisites or examples of appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
identify_hashBInspect
Identify the possible algorithm of a hash based on its format.
| Name | Required | Description | Default |
|---|---|---|---|
| hash_string | Yes | Hash string to identify |
Output Schema
| Name | Required | Description |
|---|---|---|
| hash | Yes | |
| is_hex | Yes | |
| length | Yes | |
| possible_algorithms | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral details such as whether it returns a single best guess or multiple algorithms, if it provides confidence scores, or if it can return 'unknown'. The current statement is too vague about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the core functionality without extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description lacks details on what the output contains (e.g., list of possible algorithms, confidence levels). It does not cover edge cases or limitations, leaving the user uncertain about the tool's response.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter hash_string, and its description explains what to provide. The tool description adds no additional semantic value beyond the schema, so baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: identifying the possible algorithm of a hash based on its format. It uses a specific verb (identify) and resource (hash algorithm), effectively distinguishing it from sibling tools that generate or verify hashes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like verify_hash or compare_hashes. It fails to mention prerequisites or contexts where identification might be uncertain.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
inches_to_centimetersAInspect
Convert inches to centimeters.
| Name | Required | Description | Default |
|---|---|---|---|
| inches | Yes | Length in inches |
Output Schema
| Name | Required | Description |
|---|---|---|
| inches | Yes | |
| centimeters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the core behavior (conversion) but omits details like precision or edge cases. However, for a straightforward mathematical conversion, this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is appropriately sized for a simple conversion tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has only one required parameter, no nested objects, and an output schema exists (not shown but referenced). The description is complete enough for an AI agent to understand and correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema; the parameter 'inches' is already described as 'Length in inches' in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Convert') and the resource ('inches to centimeters'), making it unambiguous. The tool's purpose is distinct from sibling conversion tools like 'centimeters_to_inches' or 'feet_to_meters'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage is for converting inches to centimeters. No explicit alternatives or when-not-to-use instructions are given, but for a simple conversion, the context is clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
in_rangeCInspect
Check if a value is within a range.
| Name | Required | Description | Default |
|---|---|---|---|
| value | Yes | Value to check | |
| max_val | Yes | Maximum value | |
| min_val | Yes | Minimum value |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| min | Yes | |
| value | Yes | |
| in_range | Yes | |
| distance_from_max | Yes | |
| distance_from_min | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It fails to specify whether the range check is inclusive (value >= min && value <= max) or exclusive (value > min && value < max). No edge cases are mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff. However, it could be longer to include necessary behavioral details, so not a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple range check with an output schema (presumably boolean), the description is adequate but lacks specification on inclusivity and edge cases, which are important for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with basic descriptions, but the tool description adds no additional meaning beyond what is already in the schema (e.g., 'Value to check'). It does not clarify inclusivity for min and max.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check if a value is within a range'), which is a specific verb+resource. However, sibling tools like 'is_between' likely perform the same check, so it lacks differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'is_between' or 'clamp'. The description does not mention context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
integer_to_ipBInspect
Convert integer to IP address.
| Name | Required | Description | Default |
|---|---|---|---|
| integer | Yes | Integer to convert to IP | |
| version | No | IP version (4 or 6) |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | No | |
| error | No | |
| integer | No | |
| version | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states the basic function but does not disclose that the tool supports both IPv4 and IPv6 via the 'version' parameter, nor does it mention any range constraints or error conditions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core purpose. However, it could be slightly improved by mentioning the version parameter to avoid ambiguity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (implied) and full parameter coverage in the schema, the description is adequate for simple use. However, it lacks details about the version parameter's impact, making it only minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides descriptions for both parameters, achieving 100% schema description coverage. The description adds no additional meaning beyond what the schema already conveys, meeting the baseline for coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Convert' and clearly identifies the resource as 'integer to IP address'. It distinguishes this tool from its sibling 'ip_to_integer' by emphasizing the direction of conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when needing to convert an integer to an IP address) but provides no explicit guidance on when not to use it or mention of alternatives like 'ip_to_integer' for the reverse operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
inverse_caseCInspect
Inverse the case of each character (same as swap).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the operation without detailing behavior for non-alphabetic characters, return type, or any side effects. The minimal information is insufficient for complete transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise, consisting of a single sentence. It avoids unnecessary words, but the structure could be improved by separating the alias or adding more context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (1 param, no output schema, no annotations), the description is somewhat lacking. It does not confirm the return type, handle edge cases, or explain the redundancy with 'swap_case'. Completeness is low.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter 'text' with a description, and the tool description adds no further meaning. Since schema coverage is 100%, baseline is 3. No additional detail is provided about encoding or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool inverts the case of each character, and it provides an alias ('same as swap') which helps relate it to sibling tools. However, it does not distinguish itself from the identical sibling 'swap_case', causing potential confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like 'swap_case', 'to_upper_case', or 'to_lower_case'. The description only notes it is the same as swap, which does not help an agent choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invert_colorCInspect
Invert a color.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color to invert |
Output Schema
| Name | Required | Description |
|---|---|---|
| inverted | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden for behavioral disclosure. It fails to explain what 'invert' means (e.g., RGB complement, hue inversion) or any side effects, leaving significant ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise and efficient, using only one sentence. While it lacks depth, it earns points for brevity and front-loading the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and an output schema that likely documents return values, the description still omits crucial information about the inversion method and output format. It is insufficient for an agent to use correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool description adds no new meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Invert a color' clearly states the action (invert) and resource (color). However, it does not differentiate from sibling tools like 'complement_color' or 'grayscale_color', which might perform similar operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or context that would help an agent choose this tool over related ones.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ip_infoBInspect
Get detailed information about an IP address.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | Yes | |
| error | No | |
| valid | No | |
| version | No | |
| exploded | No | |
| is_global | No | |
| compressed | No | |
| is_private | No | |
| packed_hex | No | |
| is_loopback | No | |
| is_reserved | No | |
| is_multicast | No | |
| is_link_local | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to mention rate limits, authentication requirements, data sources, or response structure. Only states the basic action without transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and to the point. It could be slightly more informative but maintains efficiency without unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, output schema exists), the description is minimally adequate. However, it lacks specifics on what 'detailed information' includes and does not leverage the output schema's presence to reduce explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the 'ip' parameter described as 'IP address to analyze'. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets detailed information about an IP address, but it does not differentiate from sibling tools like ip_info_2 or network_info. The verb 'get' and resource 'IP address' are specific, but the scope is vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving IP details but provides no explicit guidance on when to use this vs alternatives like ip_info_2 or cidr_info. No context on prerequisites or limitations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ip_info_2CInspect
Get basic information about an IP address.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to get info for |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | No | |
| code | No | |
| error | No | |
| version | No | |
| is_global | No | |
| is_private | No | |
| is_loopback | No | |
| is_reserved | No | |
| is_multicast | No | |
| is_link_local | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only states 'Get basic information', implying a read operation, but does not disclose rate limits, authentication needs, or what exactly is returned beyond the output schema existence.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with no wasted words. Front-loaded and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite low complexity and presence of output schema, the description is incomplete. It fails to outline what 'basic information' includes, leaving the agent to guess or assume the output structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter 'ip' already includes a description. The description adds no additional meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'basic information about an IP address', but does not differentiate from the sibling tool 'ip_info', which likely provides similar functionality. The scope of 'basic information' is vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'ip_info', 'validate_ip', or other IP-related tools. No when-not-to-use or contextual hints provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ip_in_networkCInspect
Check if an IP address is within a network.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to check | |
| network | Yes | Network in CIDR notation |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | No | |
| error | No | |
| network | No | |
| is_in_network | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits beyond the basic operation. There is no mention of idempotency, error handling, or any side effects. The tool is a check, so it is likely read-only, but that is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one concise sentence that directly states the tool's purpose. There is no unnecessary information. However, it could be slightly improved with an example or more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple boolean check tool with an output schema (likely returning true/false), the description is minimally adequate. It does not explain the return value or address edge cases like invalid IP formats, but given the tool's simplicity, it is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both parameters have descriptions). The tool's description adds minimal value beyond the schema: it rephrases the overall function but does not clarify parameter formats or constraints. For example, the network parameter is described in the schema as 'Network in CIDR notation,' which is sufficient.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Check if an IP address is within a network.' It uses a specific verb and resource, and the purpose is easily understood. However, it does not explicitly differentiate from sibling tools like ip_in_range or validate_ip, which have similar purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, scenarios, or exclusions. Users must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ip_in_rangeAInspect
Check if an IP address is within a CIDR range.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to check | |
| cidr | Yes | CIDR range |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | No | |
| cidr | No | |
| code | No | |
| error | No | |
| in_range | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavior. It only states the basic function, omitting details such as return type, error handling, or validation behavior. The output schema may compensate, but the description itself adds insufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence with no wasted words. It is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description provides minimal context. It does not mention the return value or any edge cases, but the presence of an output schema partially compensates. Still, it feels incomplete for a tool without annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add any meaning beyond the schema definitions for ip and cidr, so no extra value is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if an IP address is within a CIDR range, using a specific verb and resource. This distinguishes it from sibling tools like ip_in_network and cidr_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives no explicit guidance on when to use this tool versus alternatives like ip_in_network. For a simple tool, the implicit context may suffice, but it lacks explicit usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ip_to_binaryBInspect
Convert IP address to binary representation.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | Yes | |
| error | No | |
| binary | No | |
| total_bits | No | |
| binary_compact | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided; the description only states the basic transformation. It does not disclose input validation, error handling, or output format (e.g., dot-separated octets).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no superfluous words, appropriate for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward conversion tool with an output schema (not shown), the description is minimally adequate but lacks details on input format or potential edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter (ip) having a description. The tool description adds no extra meaning beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert IP address to binary representation' clearly states the verb (Convert) and resource (IP address to binary), distinguishing it from related siblings like ip_to_integer or binary_to_decimal.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives (e.g., ip_to_integer, decimal_to_binary). No context for when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ip_to_integerBInspect
Convert IP address to integer.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | Yes | |
| hex | No | |
| error | No | |
| valid | No | |
| integer | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits like input format (IPv4/IPv6), error handling, or output range. This could lead to misuse if the tool only accepts IPv4 addresses, for example.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that directly states the tool's purpose with no unnecessary words. It is efficient but could be slightly more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, likely integer output), the description is minimally adequate. However, it does not specify input format (e.g., dotted decimal vs. binary) or output range, which could cause ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage with a single parameter 'ip' described as 'IP address to convert'. The description adds no additional semantic meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert IP address to integer' uses a specific verb ('Convert') and clearly identifies the resource and transformation. It distinguishes itself from siblings like 'integer_to_ip' (reverse) and 'ip_to_binary' (different output format).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'ip_to_binary' or 'cidr_info'. The description lacks context about preferred scenarios or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ipv4_to_ipv6BInspect
Convert IPv4 address to IPv6 mapped address.
| Name | Required | Description | Default |
|---|---|---|---|
| ipv4 | Yes | IPv4 address to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| ipv4 | Yes | |
| error | No | |
| ipv6_6to4 | No | |
| ipv6_mapped | No | |
| ipv6_mapped_exploded | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the conversion behavior but lacks details on edge cases (e.g., invalid IPv4 addresses, special addresses like 0.0.0.0 or broadcast). With no annotations, the description should provide more context about the conversion process and error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. It front-loads the key information: action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to explain return values. It states the output format (IPv6 mapped address) sufficiently for a simple conversion tool. However, it could mention expected input format or validation, but overall it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 100% with a clear parameter description. The tool description does not add additional meaning beyond what the schema already provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (Convert) and the resource (IPv4 address to IPv6 mapped address). It distinguishes the output as a mapped IPv6 address, which is a specific format. However, it does not differentiate from the sibling tool 'ipv4_to_ipv6_2', which might have similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'ipv4_to_ipv6_2' or 'ipv6_to_ipv4'. There is no mention of prerequisites, valid input ranges, or error conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ipv4_to_ipv6_2BInspect
Convert IPv4 address to IPv6 mapped format.
| Name | Required | Description | Default |
|---|---|---|---|
| ipv4 | Yes | IPv4 address |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| ipv4 | No | |
| error | No | |
| ipv6_mapped | No | |
| ipv6_compatible | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description states a pure conversion but lacks details on constraints, side effects, or behavior beyond the conversion. For a simple operation, it's minimal but not informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with no extra fluff. Every word is meaningful and directly relevant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema, so return values are covered. However, given the existence of a sibling tool with a similar name, the description lacks completeness in differentiating its scope or special case.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with description 'IPv4 address' for the only parameter. Description adds no additional meaning beyond what schema already provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description has specific verb 'convert' and resource 'IPv4 address' to 'IPv6 mapped format'. However, it does not differentiate from sibling 'ipv4_to_ipv6', which likely serves a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs the sibling 'ipv4_to_ipv6' or any other alternatives. Agent must infer usage without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ipv6_to_ipv4BInspect
Extract IPv4 address from IPv6 mapped address.
| Name | Required | Description | Default |
|---|---|---|---|
| ipv6 | Yes | IPv6 mapped address to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| ipv4 | No | |
| ipv6 | Yes | |
| type | No | |
| error | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden. It only states the purpose without disclosing behavior for invalid inputs, edge cases, or any side effects. The operation is simple, but still lacks transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that efficiently conveys the purpose. It is concise without being overly terse, and it is front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with one parameter and an output schema (as signaled by context), the description provides sufficient information to understand the tool's purpose and usage. It is complete enough for typical use, though it could mention input validation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter is already documented in the schema. The description adds no additional meaning beyond what the schema provides, earning a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Extract') and clearly identifies the resource ('IPv4 address from IPv6 mapped address'). It distinguishes this tool from sibling network conversion tools like ipv4_to_ipv6 and ipv4_to_ipv6_2 by specifying the direction of conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives or when not to use it. For example, there is no mention that this is for IPv6 mapped addresses only, or comparison to similar tools like ipv4_to_ipv6.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_armstrong_numberAInspect
Check if a number is an Armstrong number (narcissistic number).
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| num_digits | Yes | |
| is_armstrong | Yes | |
| sum_of_powers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not state return type or behavior beyond the check. While the output schema likely handles this, the description could explicitly say it returns a boolean.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no fluff. Efficient and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of output schema, the description is nearly complete. Could be improved by explicitly noting the return type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic parameter description. The tool description adds no additional meaning beyond the schema's 'Number to check'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses specific verb 'Check' and target resource 'number is an Armstrong number'. Unambiguous and distinguishes from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Lacks context for selection among many math-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_betweenCInspect
Check if a number is between two bounds.
| Name | Required | Description | Default |
|---|---|---|---|
| lower | Yes | Lower bound | |
| upper | Yes | Upper bound | |
| number | Yes | Number to check | |
| inclusive | No | Include bounds in range |
Output Schema
| Name | Required | Description |
|---|---|---|
| lower | Yes | |
| upper | Yes | |
| number | Yes | |
| inclusive | Yes | |
| is_between | Yes | |
| distance_to_lower | Yes | |
| distance_to_upper | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose that the check is inclusive by default (as per schema), does not mention return type (boolean), or handle edge cases like NaN. Behavior is underspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single short sentence. It is not wordy, but it provides minimal information. Could be slightly more informative without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of 4 parameters and an output schema (presumably boolean), the description is minimal. It fails to explain the inclusive parameter or return value. Completeness is low.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%. The description adds no additional meaning beyond what the schema already provides for parameters. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if a number is between two bounds, using a specific verb and resource. It's clear but doesn't explicitly distinguish from the sibling tool 'in_range' which may be similar.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'in_range' or 'clamp'. No mention of typical use cases or edge cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_common_passwordAInspect
Check if password is in common password list.
| Name | Required | Description | Default |
|---|---|---|---|
| password | Yes | Password to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| is_common | Yes | |
| recommendation | Yes | |
| common_patterns | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden. It truthfully describes the behavior as a check but does not disclose that it is read-only, nor does it mention any rate limits or response format. The output schema handles return type, so the description is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 7 words, conveying the core purpose without any wasted words. It is optimally concise for its simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, trivial function) and presence of an output schema, the description is complete enough. It could mention that the check is against a predefined list, but not strictly necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the parameter 'password' already described as 'Password to check'. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if a password is in a common password list, using specific verb 'check' and resource 'common password list'. It distinguishes itself from sibling tools like 'analyze_password' and 'generate_password' by its specific function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'analyze_password' or 'password_entropy'. The description implies usage but offers no exclusions or context for the agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_divisibleBInspect
Check if a number is divisible by another number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check | |
| divisor | Yes | The divisor |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| number | No | |
| divisor | No | |
| remainder | No | |
| is_divisible | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should fully disclose behavior. It does not mention the return type (likely boolean), edge cases (division by zero, negative numbers), or that it uses exact integer division. This leaves ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. However, it lacks structural elements like bullet points or explicit details on return value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description is minimally adequate but fails to explicitly state the return type or behavior for edge cases. It does not fully compensate for missing annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no extra meaning beyond the parameter names. Baseline 3 is appropriate as the description does not enhance understanding of the parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Check') and resource ('number is divisible by another number'), which clearly communicates the tool's function and distinguishes it from siblings like 'is_even', 'is_odd', or 'modulo'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., is_even for divisibility by 2, modulo for remainder). The description lacks context about preferred scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_emptyBInspect
Check if text is empty or whitespace only.
| Name | Required | Description | Default |
|---|---|---|---|
| text | No | The text to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| is_blank | Yes | |
| is_empty | Yes | |
| is_whitespace_only | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It does not specify behavior for null or undefined input, whether whitespace is trimmed, or the return type. The description is minimal and lacks important edge-case details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous words. It is perfectly concise and efficiently communicates the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple utility with one optional parameter and an output schema available, the description is adequate. However, it lacks context on edge cases (e.g., null input, handling of non-string types) which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter description 'The text to check'. The tool description adds no additional meaning beyond the parameter's purpose, so baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: checking if text is empty or whitespace-only. The verb 'Check' and resource 'text' are specific, and it distinguishes itself from sibling tools like 'contains' or 'starts_with'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, limitations, or comparisons to other string-checking tools among the siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_evenCInspect
Check if a number is even.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| is_odd | Yes | |
| number | Yes | |
| is_even | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral details beyond the basic check, such as return type, error handling, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence, but it is overly minimal and could include more contextual information without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, clear purpose), the description is adequate but lacks any enrich information. The presence of an output schema reduces the need for return value details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no additional meaning beyond the schema's parameter description. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if a number is even' clearly states the action and resource, using a specific verb. It distinguishes from siblings like 'is_odd' by the parity check, though not explicitly.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'is_odd' or 'is_prime'. The description lacks context for choosing this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_fibonacciBInspect
Check if a number is a Fibonacci number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| is_fibonacci | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description should reveal behavioral details like return type or edge cases, but it only states the basic function. An output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. However, it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool (single integer input, likely boolean output) and existence of an output schema, the description is adequate but minimal. It could mention the return type for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter described as 'The number to check'. The description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if a number is a Fibonacci number' clearly specifies the action (check) and the resource (a number for Fibonacci property), which is distinct from sibling tools like 'fibonacci' that generate sequences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as 'fibonacci' or other number-checking tools (e.g., 'is_prime'). The description provides no context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_integerAInspect
Check if a number is an integer.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| is_integer | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description does not elaborate on behavior beyond the check. However, the tool is inherently a read-only property check, so the lack of additional behavioral disclosure is not critical.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. No unnecessary words, though it could optionally include a brief note about return format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an existing output schema, the description is sufficient to convey the core functionality. It covers what the tool does without needing elaboration.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter described as 'The number to check'. The description does not add extra meaning, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if a number is an integer' uses a specific verb ('Check') and resource ('if a number is an integer'), clearly distinguishing it from sibling tools like is_even or is_prime.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. While the purpose is clear, the description does not provide any context or exclusions, which is acceptable but minimal for a simple tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_leap_yearBInspect
Check if a year is a leap year.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Year to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| year | Yes | |
| days_in_year | Yes | |
| is_leap_year | Yes | |
| days_in_february | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full burden for behavioral disclosure. It only states the purpose but fails to mention that the tool is non-destructive, that it uses Gregorian calendar rules, or that it returns a boolean. The output schema is present, so return value details are covered, but other behavioral traits are absent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is extremely concise: one sentence with no filler. It is front-loaded with the essential action, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter, output schema present, no nested objects), the description is largely complete. It clearly states the primary function, and the output schema covers return value details. Some context about leap year rules could improve it, but it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the single parameter 'year' with a description. The tool's description adds no additional meaning beyond what the schema provides, justifying a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool checks if a year is a leap year. However, it does not distinguish itself from the sibling tool 'is_leap_year_2', which likely performs a similar check.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines provided. The description does not mention when to use this tool versus alternatives like 'is_leap_year_2', nor are there any prerequisites or context given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_leap_year_2BInspect
Check if a year is a leap year.
| Name | Required | Description | Default |
|---|---|---|---|
| year | Yes | Year to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| year | Yes | |
| days_in_year | Yes | |
| is_leap_year | Yes | |
| days_in_february | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states basic behavior but does not mention edge cases (e.g., year 0, negative years), error handling, or output format. The presence of an output schema partially compensates.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, and concise without wasted words. However, it could be more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple boolean check tool, the description covers the main task. But given sibling 'is_leap_year' exists, more context on differences or output would improve completeness. Output schema exists but not referenced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description 'Year to check'. Description adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the purpose: checking if a year is a leap year. Verb 'Check' and resource 'year' are specific. However, there is a sibling 'is_leap_year' with an identical description, so no differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'is_leap_year'. Sibling tools exist but no context or exclusions are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_negativeAInspect
Check if a number is negative.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| is_zero | Yes | |
| is_negative | Yes | |
| is_positive | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is minimal. It does not mention the return type (boolean) or any side effects, though the output schema exists. For a simple check, this is adequate but could be more informative.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one short sentence that fully conveys the tool's purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity—one required parameter, no nested objects, and an output schema—the description minimally covers what is needed. It states the core function, though adding mention of the return type would make it completely self-contained.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage with parameter description 'The number to check'. The tool description adds no additional meaning beyond what the schema already provides, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if a number is negative' clearly states a specific verb and resource, and it distinguishes the tool from similar sibling tools like 'is_positive' and 'is_zero'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as 'is_positive' or 'is_zero'. The simplicity makes usage implicit, but clarity on alternatives would improve.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_oddBInspect
Check if a number is odd.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| is_odd | Yes | |
| number | Yes | |
| is_even | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fails to disclose any behavioral traits (e.g., return type, error handling for non-integers). The one-line description is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, though it could benefit from slightly more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature and presence of an output schema, the description is minimally adequate but lacks context with sibling tools and fails to guide the agent on usage boundaries.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter `number` described as 'The number to check'. The description adds no additional meaning beyond the schema, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if a number is odd.' uses a specific verb and resource, clearly distinguishing the tool from siblings like `is_even`, `is_prime`, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like `is_even` or other parity checks, leaving the agent with no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_palindromeBInspect
Check if text is a palindrome.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to check | |
| ignore_case | No | Ignore case | |
| ignore_spaces | No | Ignore spaces |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| is_palindrome | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description does not mention that it returns a boolean or that parameters like ignore_case and ignore_spaces affect behavior. Minimal disclosure beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple boolean-returning tool with output schema, the description is adequate but minimal. It does not mention the effect of the optional parameters, which are crucial for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptive parameter names and defaults. The description adds no extra meaning, but the schema already documents the parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if text is a palindrome. It distinguishes from siblings like is_palindrome_number, but does not clarify scope like handling of empty strings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this vs alternative string utilities like reverse_string or compare. An agent would need to infer from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_palindrome_numberBInspect
Check if a number is a palindrome.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| reversed | Yes | |
| is_palindrome | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose behavior such as handling of negative numbers, zero, or leading zeros (e.g., 010 considered palindrome?). Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise. Could be slightly more detailed without losing conciseness, but acceptable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with one parameter and output schema present. Description is minimal but sufficient for the task. No major gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (1 param described). Description adds no extra meaning beyond 'Number to check' from schema. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states what the tool does: 'Check if a number is a palindrome.' Verb+resource+condition are specific. Differentiates from sibling 'is_palindrome' (likely for strings).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. There are siblings like 'is_palindrome' for strings, but no mention of when to choose number vs string version.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_perfect_numberAInspect
Check if a number is a perfect number (sum of proper divisors equals the number).
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | Yes | |
| number | Yes | |
| is_perfect | Yes | |
| divisor_sum | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It states the core logic (sum of proper divisors) but does not mention any edge cases, performance constraints, or what happens with the result. The schema already defines the input range, so the description adds minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of a single, efficient sentence that includes a parenthetical definition. No unnecessary words, perfectly front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema (not shown but assumed adequate). The description covers the core logic. It could optionally mention the return type, but given the output schema exists, it is not required. Slightly incomplete for an agent unfamiliar with perfect numbers, but sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage for 'number'. The description restates the purpose but does not add new semantic details (e.g., format, special values). Baseline 3 applies as the schema already documents the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if a number is perfect, with a parenthetical definition. It uses a specific verb ('Check') and resource ('a number'), and distinguishes from related number tools like is_prime or is_armstrong_number.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. While the purpose is self-evident for a simple check, siblings like is_perfect_square or is_power_of exist, and no context for optimal usage is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_perfect_squareAInspect
Check if a number is a perfect square.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| square_root | No | |
| is_perfect_square | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It does not mention return type or edge cases, but the output schema (present) covers return. Minimal disclosure beyond the basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. Front-loads the purpose effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple boolean check with one parameter and an output schema, the description is sufficient. It could mention that the result is a boolean, but it's implied.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes the parameter. The description adds no extra meaning beyond 'The number to check', which is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Check' and the specific property 'perfect square' for a number. It distinguishes from sibling tools like 'is_even', 'is_prime', etc., which check other properties.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or alternatives. Given the simplicity, the purpose implies usage, but no exclusions or comparisons are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_positiveBInspect
Check if a number is positive.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| is_zero | Yes | |
| is_negative | Yes | |
| is_positive | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It does not mention the return type (presumably boolean), edge cases like zero (which is not positive), or any side effects. The description is too sparse for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is appropriately sized for a simple tool and front-loads the purpose effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is minimally adequate. However, it lacks an explicit definition of 'positive' (greater than zero, zero excluded) and does not mention the output type, which could cause ambiguity. With an output schema present (but not shown), the description need not explain return values, but additional context would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the schema already describes the parameter as 'The number to check'. The description adds no new information beyond the schema, so baseline score 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool checks if a number is positive. It uses the specific verb 'check' and resource 'number', and it implicitly distinguishes from sibling tools like 'is_negative' and 'is_zero' by focusing on positivity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'is_negative' or 'is_zero'. The description does not mention any prerequisites, exclusions, or typical use cases, leaving the agent to infer context from sibling names alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_power_ofBInspect
Check if a number is a power of another number.
| Name | Required | Description | Default |
|---|---|---|---|
| base | Yes | Base to check against | |
| number | Yes | Number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| base | Yes | |
| number | Yes | |
| exponent | No | |
| is_power | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must explain behavior. It does not explicitly state that the tool returns a boolean, nor does it mention edge cases (e.g., number=1 is a power of any base≥2). The description is too brief to fully disclose behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no extraneous words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Although an output schema exists, the description lacks usage guidance and behavioral details. For a simple boolean check tool, it is adequate but not comprehensive, especially given the large number of siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description adds no additional meaning beyond what the schema already provides, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Check' followed by a clear statement: 'if a number is a power of another number'. This precisely conveys the tool's function and distinguishes it from siblings like 'is_divisible' or 'is_perfect_square'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives such as 'nearest_power', 'nth_root', or other mathematical checks. The agent is left to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_primeBInspect
Check if a number is prime.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| is_prime | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden of behavioral disclosure. It does not mention edge cases (0, 1, negative numbers) or performance implications, leaving significant gaps for an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It is front-loaded and efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but indicated), the description need not detail return values. For a simple integer prime check, the description is sufficiently complete, though it could mention what it returns (boolean).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'number' described as 'The number to check'. The tool description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if a number is prime' is a specific verb+resource combination that clearly states the tool's function. It distinguishes itself from sibling tools like is_even, is_odd, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools include many number property checks (e.g., is_even, is_perfect_square), but the description gives no context for selecting this one.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_private_ipAInspect
Check if an IP address is private (RFC 1918 for IPv4).
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | Yes | |
| error | No | |
| is_private | No | |
| matching_range | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It states the check follows RFC 1918 but does not specify the return value (likely boolean) or any side effects. For example, it doesn't say 'Returns true if the IP is private, false otherwise'. This omission makes the behavior less transparent than it could be.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly conveys the tool's purpose. Every word is necessary and there is no redundant information. It is front-loaded with the key action and scope.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple boolean check tool with one parameter and likely a straightforward output schema, the description is almost complete. It clearly states the scope (RFC 1918, IPv4). However, it lacks explicit mention of the return format (true/false). The presence of an output schema partially compensates, but a direct statement would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters (one required 'ip' with description 'IP address to check'). The tool description adds no additional meaning beyond what the schema already provides. According to the guidelines, when schema_description_coverage is high, baseline is 3, which is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Check if an IP address is private (RFC 1918 for IPv4)'. It uses a specific verb ('Check') and identifies the resource ('IP address') with a well-defined scope ('private', 'RFC 1918', 'IPv4'). This distinguishes it from similar siblings like 'is_valid_ip' or 'private_ip_ranges'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there is no mention of when not to use it or which sibling tools might be more appropriate for other scenarios (e.g., checking validity or getting private ranges). The usage context is implied but not spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_subsetCInspect
Check if array1 is a subset of array2.
| Name | Required | Description | Default |
|---|---|---|---|
| array1 | Yes | Potential subset | |
| array2 | Yes | Potential superset |
Output Schema
| Name | Required | Description |
|---|---|---|
| array1 | Yes | |
| array2 | Yes | |
| is_equal | Yes | |
| is_subset | Yes | |
| is_superset | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description lacks behavioral details such as how it handles duplicates, order, or case sensitivity. The tool's behavior beyond the basic check is opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence without fluff. However, it could be expanded to include necessary context without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description does not specify the return type (likely boolean) or the precise definition of subset (e.g., treating arrays as sets). Given the existence of an output schema, the description should at least hint at the output. Incomplete for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter having a description, but those descriptions are minimal ('Potential subset', 'Potential superset'). The tool description reinforces the relationship, adding slight value over the schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if array1 is a subset of array2' clearly states a specific verb and resource, and it distinguishes itself from sibling array tools like array_union or array_difference.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as array_intersection or contains. No when-not-to-use or exclusion criteria are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_triangularAInspect
Check if a number is a triangular number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| position | No | |
| is_triangular | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is minimal and provides no behavioral details beyond the basic check. With no annotations, it carries the full burden, but it does not disclose edge cases (e.g., 0 is triangular) or return type, though the schema implies integer input and output schema likely covers the result.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. It is front-loaded and efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description is nearly complete. It lacks explicit mention of return type or edge cases, but for a simple boolean check, it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description does not add meaning beyond the input schema. The schema already describes the 'number' parameter with a description, and the tool description restates what the parameter is without additional semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: checking if a number is triangular. It uses a specific verb ('check') and resource ('triangular number'), distinguishing it from sibling tools like 'is_fibonacci' or 'is_perfect_square'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description is clear but lacks context for when binary classification tools are appropriate, though the tool's simplicity makes it intuitive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_valid_coordinatesCInspect
Check if coordinates are valid.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude to validate | |
| lon | Yes | Longitude to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| lat | Yes | |
| lon | Yes | |
| is_valid | Yes | |
| is_valid_lat | Yes | |
| is_valid_lon | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only says 'Check if coordinates are valid' without explaining what constitutes valid coordinates (e.g., lat range -90 to 90, lon range -180 to 180) or any side effects. For a validation tool, this is insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise—a single sentence. It is front-loaded and to the point. For a simple validation tool, this level of conciseness is acceptable, though a bit more detail would not hurt.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has an output schema and high parameter coverage, the description is minimally adequate. However, it lacks explanation of validity criteria (e.g., coordinate ranges) which is important for correct usage. It feels incomplete for a validation tool with no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%—both parameters have descriptions ('Latitude to validate', 'Longitude to validate'). The tool description adds no additional meaning beyond what the schema already provides. Baseline is 3, and no extra value is added.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if coordinates are valid' clearly states the tool's purpose: validating coordinates. The verb 'Check' and resource 'coordinates' are specific. While the name already implies this, the description adds clarity. However, it does not explicitly differentiate from sibling validation tools like 'validate_email', but the unique resource 'coordinates' makes it distinct enough.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. The description does not indicate prerequisites, scope, or when not to use it. Given the extensive list of sibling tools (many validation-type tools), the agent would benefit from knowing that this is specifically for lat/lon coordinates or that other tools handle different validations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_valid_hexBInspect
Check if a string is a valid hex color.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Color string to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| input | Yes | |
| expanded | No | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as case sensitivity, handling of the '#' prefix, or accepted color formats. This is insufficient for a validation tool without annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no redundant information. It is well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and has an output schema, the description does not explain what the output represents (e.g., boolean) or handle edge cases (e.g., empty strings, long strings). It is adequate but lacks completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 100% for the single parameter, and the description ('valid hex color') aligns with the schema's 'Color string to validate'. However, it does not add extra meaning or clarify expected formats beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Check' and specifies the resource 'string' and condition 'valid hex color', making it clear what the tool does. However, it does not distinguish itself from the sibling tool 'validate_hex', which likely performs a similar validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'validate_hex' or other validation tools. There is no mention of prerequisites, limitations, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_valid_slugBInspect
Check if a string is a valid URL slug.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Slug to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| slug | Yes | |
| issues | No | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must convey behavior. It does not specify what 'valid' means, return type, or error handling (e.g., returns boolean vs throws on invalid).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite output schema existence, the description lacks details on validation criteria or output behavior. With only one parameter and no nested objects, more context is warranted for a validation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter 'slug' has a schema description 'Slug to validate' (100% coverage), and the tool description adds no extra meaning beyond confirming it's a URL slug check. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action 'Check' and the resource 'if a string is a valid URL slug'. Distinguishes from siblings like 'slugify' and 'deslugify' by indicating validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied that this tool is for verifying slug validity, but no explicit guidance on when to use alternatives like 'validate_pattern' or what constitutes invalid input.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_valid_urlCInspect
Validate if a string is a valid URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to validate | |
| require_protocol | No | Require http/https |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| issues | No | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility. It only states the basic validation function without disclosing what validation criteria are used, error behavior, or return format (though output schema may cover returns).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence. It is concise but could be improved by adding a brief note on output or usage without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and existence of output schema, the description is minimally adequate. However, it lacks differentiation from sibling `validate_url` and does not clarify validation behavior, which could hinder correct selection by an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter descriptions in the schema already explain `url` and `require_protocol`. The tool description adds no additional parameter semantics beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it validates URLs, but it does not differentiate from the sibling `validate_url` tool, making it less clear which to use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like `validate_url`. The description only states functionality without usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_weekendCInspect
Check if a date is a weekend.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Date (YYYY-MM-DD) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| date | No | |
| error | No | |
| day_name | No | |
| is_weekday | No | |
| is_weekend | No | |
| day_of_week | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavior beyond the name. It omits details like return type (boolean), error handling for invalid dates, and that it considers Saturday/Sunday as weekend.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise single sentence, front-loaded with the core action. Could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of output schema, the description is somewhat complete but misses explicit mention of return value and edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, so the description adds no extra meaning. The parameter 'date' is already well-defined. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if a date is a weekend, using a specific verb and resource. It distinguishes well from sibling date tools like is_leap_year or date_diff.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, such as day_of_year or date_to_timestamp. Lacks context about timezone or format assumptions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
is_zeroAInspect
Check if a number is zero.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| is_zero | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It transparently states the tool checks if a number is zero, which is a simple read-only operation. No side effects or permissions are needed, and the description is accurate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with zero superfluous words. It is front-loaded and efficiently conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, boolean check) and the existence of an output schema, the description is complete. It covers the essential behavior without needing additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the parameter description 'The number to check' is already clear. The tool description adds no extra meaning beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if a number is zero' uses a specific verb and resource, clearly distinguishing it from sibling tools like is_even, is_odd, etc. It is precise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Among many similar boolean checkers, the description does not mention when to prefer is_zero or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
joinBInspect
Join items with a delimiter.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items to join | |
| delimiter | No | Delimiter to join with | , |
Output Schema
| Name | Required | Description |
|---|---|---|
| items | Yes | |
| joined | Yes | |
| delimiter | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It states the core operation but omits details like that 'items' is a comma-separated string (delegated to schema), or what happens with edge cases (e.g., empty items, delimiter handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is highly concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with two parameters and an output schema, the description is adequate but lacks context about expected input format (comma-separated items) and output. The schema fills some gaps, but more behavioral context would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description repeats the schema's purpose without adding new meaning, but it aligns with the parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Join items with a delimiter' clearly states the action (join) and resource (items) with a delimiter. It distinguishes from siblings like 'split' or 'array_zip' by focusing on concatenation, though it doesn't explicitly differentiate from similar concatenation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'repeat' or 'array_union'. The description provides no context about preconditions or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
join_pathBInspect
Join path parts safely.
| Name | Required | Description | Default |
|---|---|---|---|
| parts | Yes | Path parts separated by comma | |
| separator | No | Path separator | / |
Output Schema
| Name | Required | Description |
|---|---|---|
| parts | Yes | |
| joined | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behaviour. 'Safely' suggests extra handling (e.g., deduplicating separators), but it's vague. It does not state what happens with invalid inputs, trailing slashes, or whether it normalizes paths.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no filler. Every word contributes to the purpose and safety hint. Ideal conciseness for a simple utility tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, an output schema exists, and the tool is simple, the description covers the core function. However, it lacks details on edge cases, error handling, and return format, making it minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with descriptions. The tool description adds no new information beyond the schema. Baseline 3 is appropriate as the description does not compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Join path parts safely' uses a specific verb and resource, clearly indicating it concatenates path components. It hints at safety (e.g., handling separators), distinguishing it from siblings like `build_url` or `slugify`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like `build_url`, `normalize_url`, or `slugify`. The description implies path joining but doesn't exclude other use cases or provide context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
json_diffBInspect
Compare two JSON objects and find differences.
| Name | Required | Description | Default |
|---|---|---|---|
| json1 | Yes | First JSON string | |
| json2 | Yes | Second JSON string |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | No | |
| identical | No | |
| differences | No | |
| change_count | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure, but it does not. It fails to describe what 'differences' means (e.g., structural, value, ordering), the output format, or any side effects. The tool's exact behavior remains opaque.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It efficiently communicates the core purpose without any fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (two string parameters, output schema exists), the description is minimally adequate. However, it lacks explanation of the difference detection algorithm, output structure, or edge cases, which leaves some gaps for an agent to infer correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions ('First JSON string', 'Second JSON string'), which add little beyond parameter names. The tool description does not provide additional meaning or usage details for the parameters, so it meets the baseline but adds no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'compare' and the resource 'two JSON objects' with the goal to 'find differences'. It effectively distinguishes from sibling tools like json_minify or json_prettify which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. For example, it does not mention that both inputs must be valid JSON strings or how to handle malformed inputs.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
json_minifyAInspect
Minify JSON (remove whitespace).
| Name | Required | Description | Default |
|---|---|---|---|
| json_str | Yes | JSON to minify |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| savings | No | |
| minified | No | |
| minified_length | No | |
| original_length | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states the basic behavior (remove whitespace) but does not disclose error handling, input validation, or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, front-loaded. Could be slightly improved by including a complete sentence, but effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with output schema and clear input, description is sufficient. No missing critical information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline applies. Description adds no extra meaning beyond the schema's 'JSON to minify'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb (minify), resource (JSON), and effect (remove whitespace). It distinguishes from sibling tools like json_prettify by specifying the opposite operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternative guidance. Usage is implied but not contrasted with siblings like json_prettify or json_minify.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
json_prettifyAInspect
Prettify JSON (format with indentation).
| Name | Required | Description | Default |
|---|---|---|---|
| indent | No | Indentation spaces | |
| json_str | Yes | JSON to prettify |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| prettified | No | |
| original_length | No | |
| prettified_length | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description minimally states the core behavior (format with indentation) but lacks details on error handling, return value type, or validation. It is adequate for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very concise single sentence. Could be slightly improved by including the return type or default indent, but it is efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is mostly complete. Output schema exists, so return details are covered. No critical missing info for a basic formatting tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no significant meaning beyond the schema. The mention of indentation aligns with the indent parameter but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action (prettify) and resource (JSON) with the detail about indentation. It distinguishes from sibling tools like json_minify or json_diff by focusing on formatting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., json_minify, json_diff). No when-not or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
json_statsBInspect
Get statistics about a JSON structure.
| Name | Required | Description | Default |
|---|---|---|---|
| json_string | Yes | JSON string to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| nulls | No | |
| valid | No | |
| arrays | No | |
| numbers | No | |
| objects | No | |
| strings | No | |
| booleans | No | |
| max_depth | No | |
| size_bytes | No | |
| total_keys | No | |
| total_values | No | |
| size_minified | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source for behavioral information. It only states that it gets statistics, without disclosing what statistics (e.g., depth, key count, types), whether it's read-only, or any side effects. This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence, efficient and front-loaded. It could be slightly expanded without becoming verbose, but it is not overly long. Score 4 for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (analyzing JSON structure), the description is too minimal. It does not specify what statistics are computed, which is essential for an agent to determine if this tool meets the need. The presence of an output schema does not compensate for the lack of high-level description of the statistics provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema's parameter description 'JSON string to analyze'. It does not clarify format constraints or expected size.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get statistics about a JSON structure' clearly specifies the verb (Get) and resource (statistics about a JSON structure), distinguishing it from sibling tools like json_diff, json_minify, etc. that perform different operations on JSON.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not state when not to use it or mention other tools for specific JSON analysis tasks, leaving the agent to infer usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
json_to_query_stringBInspect
Convert a JSON object to URL query string.
| Name | Required | Description | Default |
|---|---|---|---|
| json_string | Yes | JSON object to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | No | |
| query_string | No | |
| full_url_example | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but fails to disclose behavioral details such as URL encoding, key ordering, handling of nested objects, or error behavior. For a conversion tool, more transparency is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no extraneous words. Every part earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description is adequate but lacks details on edge cases (e.g., invalid JSON, empty objects) and encoding behavior. It meets minimum needs but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The parameter description 'JSON object to convert' adds little beyond the schema's own description, providing only a slight clarification.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb and resource: 'Convert a JSON object to URL query string.' It distinguishes from siblings like 'query_string_to_json' (reverse operation) and 'add_query_param' (modifying an existing query string).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Siblings like 'query_string_to_json', 'add_query_param', and 'remove_query_param' exist, so explicit usage context would be beneficial.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
jwt_decodeBInspect
Decode JWT token (without signature verification).
| Name | Required | Description | Default |
|---|---|---|---|
| token | Yes | JWT token to decode (without verification) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| header | No | |
| payload | No | |
| warning | No | |
| signature | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It discloses the lack of signature verification but fails to mention what happens with invalid tokens, output format, error handling, or other behaviors beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no superfluous information, achieving maximum conciseness while conveying the core purpose and a key differentiator.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite being a simple tool with one parameter, the description lacks information about the return value format and error scenarios. However, an output schema exists which may cover return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the parameter description already states 'without verification'. The tool description adds no additional meaning to the parameter beyond what the schema provides, so baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool decodes a JWT token and explicitly notes it does so without signature verification, distinguishing it from potential verification tools. The verb 'decode' and resource 'JWT token' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. While the description implies it's for decoding without verification, there is no mention of when verification is needed or alternative tools to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kebab_caseBInspect
Convert text to kebab-case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| kebab_case | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic conversion, omitting details like handling of special characters, edge cases, or output format. For a simple tool, more transparency is expected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently communicates the tool's purpose without extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (1 param, output schema exists), the description is minimally complete. However, it fails to specify kebab-case rules (e.g., lowercase with hyphens), which a fuller description might include. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'text', and the description adds no additional meaning beyond the schema's 'The text to convert'. Following guidelines, baseline 3 is appropriate as the schema already documents the parameter sufficiently.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'text to kebab-case', making the tool's purpose immediately obvious. It also distinguishes from sibling tools like camel_case, snake_case, etc., which target different case formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as snake_case or camel_case. There is no mention of prerequisites, when-to-use, or when-not-to-use, leaving the agent to infer usage from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kelvin_to_celsiusBInspect
Convert Kelvin to Celsius.
| Name | Required | Description | Default |
|---|---|---|---|
| kelvin | Yes | Temperature in Kelvin |
Output Schema
| Name | Required | Description |
|---|---|---|
| kelvin | Yes | |
| celsius | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No behavioral details beyond the conversion. Lacks information about precision, output format, or any constraints. Since annotations are absent, the description fails to disclose important behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence that immediately conveys the tool's purpose. No unnecessary information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple conversion tool. Output schema exists, so not required. However, no mention of edge cases or precision. Meets minimum completeness for its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter is well-documented in schema (100% coverage). Description adds no extra semantic meaning beyond the schema. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the conversion from Kelvin to Celsius, distinguishing it from other temperature conversion tools like celsius_to_fahrenheit or fahrenheit_to_celsius. The verb 'Convert' is specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance provided. It does not differentiate from other temperature conversion tools, nor does it state context for when this conversion is appropriate. User must infer from the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kilobytes_to_megabytesAInspect
Convert kilobytes to megabytes.
| Name | Required | Description | Default |
|---|---|---|---|
| kilobytes | Yes | Size in kilobytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| kilobytes | Yes | |
| megabytes | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose the conversion factor (e.g., 1 MB = 1024 KB or 1000 KB), which is a critical behavioral detail. No annotations exist to fill this gap. The basic operation is clear, but precision assumptions are hidden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly states the tool's purpose, with no unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple, the description lacks specification of the conversion factor (binary vs decimal) and does not mention the output schema. For a conversion tool, these details are important for correct usage, making it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no additional meaning beyond 'Size in kilobytes'. The parameter semantics are fully captured in the schema, so the description offers no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Convert' and indicates both input unit (kilobytes) and output unit (megabytes), clearly stating the tool's function. It is unambiguous and distinct from other conversion tools in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'bytes_to_human' or other conversion tools. No prerequisites or context for when to apply this conversion, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kilograms_to_poundsBInspect
Convert kilograms to pounds.
| Name | Required | Description | Default |
|---|---|---|---|
| kilograms | Yes | Weight in kilograms |
Output Schema
| Name | Required | Description |
|---|---|---|
| pounds | Yes | |
| kilograms | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description lacks any behavioral details such as rounding behavior, handling of negative numbers, or edge cases. The output schema exists but is not referenced.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no unnecessary words. Perfectly concise for a simple conversion tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no nested objects) and existence of an output schema, the description is mostly complete. Could mention that output is in pounds, but output schema likely covers it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter described as 'Weight in kilograms'. The description adds no additional meaning beyond the schema. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the conversion from kilograms to pounds. It is specific and uses a verb+resource format. However, it does not differentiate from sibling conversion tools, though the direction is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like pounds_to_kilograms. No mention of prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kilometers_to_milesBInspect
Convert kilometers to miles.
| Name | Required | Description | Default |
|---|---|---|---|
| kilometers | Yes | Length in kilometers |
Output Schema
| Name | Required | Description |
|---|---|---|
| miles | Yes | |
| kilometers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the full burden. It only states the conversion without disclosing any behavioral traits like rounding, precision, or return format. Even though an output schema exists, the description adds no behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is appropriately concise for a simple conversion tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward conversion with a single parameter and existing output schema, the description is minimally adequate. However, it could be improved by mentioning the expected return value or potential edge cases to be truly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully describes the single parameter (kilometers) with 100% coverage. The description adds no additional semantic information beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (convert) and resource (kilometers to miles). However, it does not differentiate from the sibling tool miles_to_kilometers, which performs the reverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus the reverse sibling (miles_to_kilometers) or any other conversion tool. No context about appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
knots_to_kphAInspect
Convert knots to kilometers per hour.
| Name | Required | Description | Default |
|---|---|---|---|
| knots | Yes | Speed in knots |
Output Schema
| Name | Required | Description |
|---|---|---|
| kph | Yes | |
| knots | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description is the sole source. It conveys a simple conversion operation without disclosing any potential edge cases or behavior beyond the basic transformation, which is acceptable for such a straightforward tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that efficiently communicates the tool's purpose with no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description provides sufficient context. The presence of an output schema means return values are documented elsewhere.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a description for the parameter ('Speed in knots'). The tool description does not add any additional semantic meaning beyond what the schema offers, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Convert') and the specific resource ('knots to kilometers per hour'), distinguishing it from sibling conversion tools like 'kilometers_to_miles' or 'celsius_to_fahrenheit'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of when not to use it or any context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kph_to_mphAInspect
Convert kilometers per hour to miles per hour.
| Name | Required | Description | Default |
|---|---|---|---|
| kph | Yes | Speed in kilometers per hour |
Output Schema
| Name | Required | Description |
|---|---|---|
| kph | Yes | |
| mph | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations were provided, so the description carries the full burden. It does not disclose any behavioral traits such as precision, rounding, or side effects, beyond the basic conversion function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no waste, perfectly concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity conversion tool with an output schema, the description is generally complete. It adequately explains the tool's function, though it could mention output format or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add significant meaning beyond the schema's parameter description. It clarifies the conversion context but offers no additional parameter insights.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts kilometers per hour to miles per hour, using specific verb and resources, distinguishing it from other conversion tools like mph_to_kph.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks explicit when-to-use or when-not-to-use guidance, but for a simple unit conversion the context is implied. No alternatives are mentioned, but the tool's purpose is self-explanatory.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lcmBInspect
Calculate the least common multiple.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First number | |
| b | Yes | Second number |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | Yes | |
| b | Yes | |
| lcm | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure, but it only states the basic operation. It does not address edge cases (e.g., negative numbers, zero), return type, or potential limitations, which is a significant gap for a mathematical tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-integer function with an existing output schema, the description is adequate but minimal. It lacks guidance on usage and behavior, which reduces completeness. The agent would benefit from notes on valid input ranges or typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions ('First number' and 'Second number'). The description adds context by naming the operation but does not enhance parameter semantics beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the least common multiple, which is a specific mathematical operation. The tool name 'lcm' combined with the description makes the purpose unambiguous and distinguishes it from siblings like 'gcd'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like 'gcd' or other arithmetic functions. The description does not mention context or prerequisites, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
leetspeak_passwordAInspect
Convert a password to leetspeak (for demonstration, not security).
| Name | Required | Description | Default |
|---|---|---|---|
| level | No | Leetspeak intensity (1-3) | |
| password | Yes | Password to convert to leetspeak |
Output Schema
| Name | Required | Description |
|---|---|---|
| note | Yes | |
| level | Yes | |
| original | Yes | |
| leetspeak | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, and the description only says 'for demonstration, not security'. It does not disclose behavioral traits such as how leetspeak conversion works (e.g., which characters are substituted), whether the output is reversible, or any side effects. The minimal disclosure is insufficient for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that communicates the core function without unnecessary words. It is front-loaded and every part is relevant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description is adequate for a demonstration tool. It conveys the primary purpose and the non-security context, though it could be improved by providing a simple example or noting the default behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so both parameters are already explained in the schema. The description does not add any extra meaning beyond what the schema provides, such as clarifying what 'level' means for intensity. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'password to leetspeak', specifying the tool's function. It also distinguishes itself from sibling tools like analyze_password or generate_password by adding '(for demonstration, not security)'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool is for demonstration purposes only and not for security, but it does not explicitly guide when to use this tool versus alternatives like generate_password or analyze_password. No direct when-not or alternative tool references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
levenshtein_distanceBInspect
Calculate Levenshtein (edit) distance between two strings.
| Name | Required | Description | Default |
|---|---|---|---|
| text1 | Yes | First string | |
| text2 | Yes | Second string |
Output Schema
| Name | Required | Description |
|---|---|---|
| text1 | Yes | First input string |
| text2 | Yes | Second input string |
| distance | Yes | Levenshtein edit distance (number of single-character edits) |
| similarity | Yes | Normalized similarity (0-1, where 1 = identical) |
| similarity_percent | Yes | Similarity as a percentage (0-100) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the function, omitting behavioral details like time complexity (O(n*m)), case sensitivity, or whether whitespace is considered. The tool is non-destructive, but this is not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently communicates the tool's purpose with no superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculation tool with two string parameters and an output schema (as indicated by context signals), the description is adequate. It does not need to explain return values since an output schema exists, and the functionality is straightforward.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with each parameter having a basic description ('First string', 'Second string'). The tool description adds no additional meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates the Levenshtein (edit) distance between two strings, using a specific verb and resource. It is distinct from sibling tools like 'text_similarity' by specifying the exact algorithm, but does not explicitly differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., other string comparison tools like 'text_similarity' or 'hamming_distance'). There are no usage exclusions or context hints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lighten_colorAInspect
Lighten a color by a percentage.
| Name | Required | Description | Default |
|---|---|---|---|
| amount | No | Amount to lighten (0-100) | |
| hex_color | Yes | Hex color to lighten |
Output Schema
| Name | Required | Description |
|---|---|---|
| amount | Yes | |
| darkened | No | |
| original | Yes | |
| lightened | No | |
| saturated | No | |
| desaturated | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must stand alone. It clearly states the tool lightens a color, which is a simple transformation. However, it doesn't detail how the percentage is applied or any other behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise—one sentence that conveys the core purpose. It is front-loaded and efficient, though it could be slightly more informative without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. It doesn't explain the return value, but the output schema likely covers that. It lacks additional context like edge cases or percentage interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the input schema already documents both parameters (hex_color and amount). The description adds no additional meaning beyond what the schema provides, so it meets the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Lighten') and the resource ('a color'), specifying the operation as 'by a percentage', which distinguishes it from siblings like darken_color or saturate_color.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool or when not to. The description implies it should be used to lighten colors, but lacks context on prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_localesAInspect
List available locales for Faker-powered endpoints.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| locales | Yes | |
| description | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states the basic function without disclosing behavioral traits like immutability, return format, or side effects. The description carries the full burden but fails to add critical context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that states the core functionality without unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters) and the presence of an output schema, the description adequately covers the intended use. It lacks nuance about the locale list's purpose, but overall it is sufficient for a basic listing operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema coverage is 100% trivially. The description need not add parameter information, meeting the baseline expectation for a parameter-less tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb+resource: 'List available locales' specifies the action and object. 'for Faker-powered endpoints' provides context, distinguishing it from other listing tools among siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or alternatives are provided. Usage is implied by the tool's purpose, but there is no guidance on when not to use it or compare with similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_timezonesAInspect
List all available timezone abbreviations.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| timezones | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It indicates a read operation (listing), but lacks details such as whether the result includes only abbreviations or also full names, if sorting applies, or if the list is dynamic. The existence of an output schema partially compensates but the description itself is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly states the tool's purpose with no unnecessary words. It is appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and an output schema exists, the description is somewhat minimal. It does not elaborate on the format or scope of the timezone abbreviations. While adequate for a simple list, it could be more informative to help an agent differentiate from other timezone tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema description coverage is 100% by default. The baseline is 4. The description does not need to add parameter semantics since none exist.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all available timezone abbreviations, using a specific verb 'List' and resource 'timezone abbreviations'. This distinguishes it from sibling tools like convert_timezone or timezone_offset which perform different operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention scenarios where listing timezone abbreviations is appropriate or when another tool like convert_timezone should be used. No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
liters_to_gallons_ukAInspect
Convert liters to UK gallons. Because a UK gallon isn't a US gallon.
| Name | Required | Description | Default |
|---|---|---|---|
| liters | Yes | Volume in liters |
Output Schema
| Name | Required | Description |
|---|---|---|
| liters | Yes | |
| gallons_uk | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It accurately describes the conversion operation, which is a safe, read-only calculation. However, it does not explicitly state it is read-only or mention any potential side effects, though none are expected for a conversion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceptionally concise: two short sentences. The first sentence states the core purpose, and the second adds necessary context. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description is complete. It covers the conversion purpose, distinguishes from similar tools, and is sufficient for an AI agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds value by clarifying that the conversion is to UK gallons, providing context beyond the schema's description of the 'liters' parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the verb 'Convert' and the resource 'liters to UK gallons', making the purpose clear. It also distinguishes from the sibling tool 'liters_to_gallons_us' by noting the difference between UK and US gallons.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (for UK gallons) by stating 'Because a UK gallon isn't a US gallon', but it does not explicitly provide when-to-use or when-not-to-use guidance. No alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
liters_to_gallons_usBInspect
Convert liters to US gallons.
| Name | Required | Description | Default |
|---|---|---|---|
| liters | Yes | Volume in liters |
Output Schema
| Name | Required | Description |
|---|---|---|
| liters | Yes | |
| gallons_us | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only states the conversion purpose with no additional behavioral details (e.g., rounding, precision, handling of edge cases).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, efficient. Could include more context without harming conciseness, but current form is not wasteful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema, return values need not be described. The description is adequate for a simple conversion, but lacks usage guidelines and behavioral transparency, reducing completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with the parameter already well-described. The description adds no extra meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the specific conversion verb and resource clearly: 'Convert liters to US gallons.' It distinguishes from siblings like `liters_to_gallons_uk` and `gallons_us_to_liters`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Sibling tools exist for UK gallons and reverse conversion, but the description offers no context or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
loan_paymentCInspect
Calculate monthly loan payment.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual interest rate (percentage) | |
| months | Yes | Loan term in months | |
| principal | Yes | Loan amount |
Output Schema
| Name | Required | Description |
|---|---|---|
| principal | Yes | |
| total_paid | Yes | |
| term_months | Yes | |
| total_interest | Yes | |
| monthly_payment | Yes | |
| annual_rate_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior, but it only states 'calculate monthly loan payment'. It fails to describe the formula (e.g., fixed-rate amortization), whether it includes fees, or what the output contains (e.g., just payment amount or schedule). This is insufficient for a financial calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no fluff, which aids readability. However, it could be slightly more informative about the calculation context without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (content unknown) and 100% parameter coverage, the description is minimally adequate. However, it lacks details about the calculation model (e.g., standard amortization formula) and does not address the tool's scope relative to similar siblings, leaving room for improvement.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and each parameter has a clear description in the schema (e.g., 'Annual interest rate (percentage)', 'Loan term in months'). The tool description adds no additional meaning beyond what the schema already provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and the resource 'monthly loan payment'. It is specific enough to convey the tool's purpose, though it does not explicitly differentiate from the sibling 'mortgage_calculator' which may have a broader scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'mortgage_calculator', 'compound_interest', or 'simple_interest'. There is no mention of prerequisites, limitations, or recommended use cases, leaving the agent to infer usage without context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
logAInspect
Calculate logarithm. Natural log if no base specified.
| Name | Required | Description | Default |
|---|---|---|---|
| base | No | Base (default: natural log) | |
| number | Yes | Number (must be positive) |
Output Schema
| Name | Required | Description |
|---|---|---|
| base | Yes | |
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only repeats the basic function and default base. It does not mention error handling, precision, domain restrictions (beyond schema), or any side effects. For a simple tool, this is minimal but not misleading.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that is front-loaded with the main action. No unnecessary words or fluff. Every word adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical function with full schema coverage and an output schema, the description is adequately complete. It specifies the core behavior and default mode. No additional context is essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds value by clarifying default behavior when base is null. This goes beyond the schema which only states 'Base (default: natural log)' but the description reinforces it. The number parameter is already described in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates logarithms and specifies default behavior (natural log). It uses a specific verb ('Calculate') and resource ('logarithm'), making its purpose immediately understandable. It distinguishes itself from siblings like log10 and log2 by being the general log function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like log10 or log2. The name implies general logarithm, but the description does not mention sibling tools or conditions for selection. Users must infer from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
log10BInspect
Calculate base-10 logarithm.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number (must be positive) |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only states the operation, without disclosing edge cases, error behavior, or return value format. The schema provides domain info (positive numbers), but the description adds no extra behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very brief (3 words) and front-loaded. It is appropriately sized for a simple mathematical tool, though it could add a word about the return value without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (one parameter, simple function) and presence of an output schema, the description is adequate. However, it could be more explicit about returning the logarithm value, and it does not mention error conditions for non-positive inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameter is already well-documented. The description does not add further meaning beyond what the schema provides (e.g., 'Number (must be positive)'). Baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Calculate base-10 logarithm', clearly identifying the verb and resource. It distinguishes itself from sibling tools like 'log' (natural log) and 'log2' by specifying the base.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for base-10 logarithm calculations but provides no explicit guidance on when to choose this tool over alternatives like log or log2. No exclusions or context are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
log2BInspect
Calculate base-2 logarithm.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number (must be positive) |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits beyond the basic function. The schema already indicates the parameter must be positive (exclusiveMinimum 0), so the description adds no additional transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one short sentence with no unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical function with a single parameter and an output schema, the description is nearly complete. However, the lack of behavioral transparency (e.g., error handling) slightly reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has full coverage (100%) for the single parameter, including its description. The tool description adds no new information beyond what the schema provides, so it meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the function: calculating base-2 logarithm. However, it does not distinguish it from sibling tools like 'log' (likely natural log) or 'log10', which could be confusing for an AI agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'log' or 'log10'. The agent must infer usage without explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lorem_bytesAInspect
Generate lorem ipsum of approximately specified byte size.
| Name | Required | Description | Default |
|---|---|---|---|
| size | No | Approximate size in bytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| actual_bytes | Yes | |
| requested_bytes | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full behavioral burden. It notes that the size is 'approximately' specified, hinting at imprecision, but does not explain how approximation works, performance characteristics, or that output is Latin-like text. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, directly states purpose. Perfectly concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter) and presence of an output schema, the description is largely adequate. It could mention that output is a string of lorem ipsum text, but the output schema likely covers that. Slight gap in explaining the 'approximately' behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (parameter 'size' with description). The tool description essentially restates the schema's 'approximate size in bytes' without adding new meaning. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate lorem ipsum of approximately specified byte size' uses a specific verb ('generate') and resource ('lorem ipsum') with a key attribute (byte size). It clearly distinguishes from sibling tools like 'lorem_words' or 'lorem_paragraphs' which focus on word or paragraph counts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as 'lorem_words', 'lorem_paragraphs', or 'generate_lorem'. The description does not specify scenarios or constraints like 'use when you need a specific byte size'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lorem_htmlAInspect
Generate lorem ipsum as HTML.
| Name | Required | Description | Default |
|---|---|---|---|
| paragraphs | No | Number of paragraphs | |
| include_headings | No | Include h2 headings |
Output Schema
| Name | Required | Description |
|---|---|---|
| html | Yes | |
| paragraphs | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description is minimal. It does not disclose behavioral traits such as the structure of the HTML (e.g., containing <p> tags, heading tags, or styling). The schema provides parameter defaults, but the description adds no behavioral context beyond the output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and contains no wasted words. It efficiently conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lorem generator with an output schema (not shown but implied), the description is largely sufficient. However, it could mention that HTML tags are included, but this is implied by 'as HTML'. The presence of many sibling lorem tools might require more distinction, but the format distinction suffices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add extra meaning beyond what the schema already provides for the two parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates lorem ipsum text in HTML format, using a specific verb ('Generate') and resource ('lorem ipsum as HTML'). This distinguishes it from siblings like lorem_markdown and lorem_bytes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like lorem_markdown or lorem_paragraphs. The description implies usage for HTML output but lacks exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lorem_markdownBInspect
Generate lorem ipsum as Markdown.
| Name | Required | Description | Default |
|---|---|---|---|
| paragraphs | No | Number of paragraphs | |
| include_list | No | Include a bullet list | |
| include_headings | No | Include headings |
Output Schema
| Name | Required | Description |
|---|---|---|
| markdown | Yes | |
| paragraphs | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states the output format, but omits that this is a read-only, stateless generation with no side effects, rate limits, or authorization requirements. The description is insufficient for a tool with no other metadata.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that directly conveys the tool's purpose without extraneous information. It is efficiently front-loaded with the key action and result.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown but indicated) and the tool's simplicity, the description is nearly complete. It explains what is generated (lorem ipsum) and in what format (Markdown). However, it could briefly note that this is for placeholder text generation, which is implicit but helpful for clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the parameters ('paragraphs', 'include_list', 'include_headings') are well-documented in the schema. The description adds no additional meaning beyond 'Generate lorem ipsum as Markdown', which is sufficient given the schema handles parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate') and the resource ('lorem ipsum') with a specific output format ('as Markdown'). This distinguishes it from siblings like lorem_bytes, lorem_html, lorem_paragraphs, etc., which produce different formats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus other lorem generation siblings (e.g., lorem_html, lorem_paragraphs). Without context signals, the agent cannot determine scenarios where Markdown output is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lorem_paragraphsBInspect
Generate lorem ipsum paragraphs.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of paragraphs | |
| start_with_lorem | No | Start with standard Lorem ipsum |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| count | Yes | |
| paragraphs | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should disclose behavioral traits like output format and configurability. It only states 'Generate lorem ipsum paragraphs' with no mention of the parameters (count, start_with_lorem) or that output is plain text. Lacks detail on what the tool actually produces.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence. It is front-loaded and waste-free, but it sacrifices detail for brevity. Slightly above average due to efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (many sibling lorem tools) and the presence of an output schema, the description is too minimal. It doesn't explain that it generates plain text paragraphs or how it differs from other lorem generators. Incomplete for proper tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters ('Number of paragraphs', 'Start with standard Lorem ipsum'). The description adds no additional meaning beyond what the schema provides, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Generate' and resource 'lorem ipsum paragraphs', which distinguishes it from sibling tools like lorem_words, lorem_sentences, lorem_html, etc. The purpose is unambiguous and specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., lorem_words, lorem_html). No when-not-to-use or prerequisites mentioned. The agent must infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lorem_sentencesCInspect
Generate lorem ipsum sentences.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of sentences | |
| start_with_lorem | No | Start with standard Lorem ipsum sentence |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| count | Yes | |
| sentences | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states 'Generate' without clarifying whether it is a read-only generation, what side effects exist, or any constraints beyond the schema. The description is too minimal to be transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence) with no wasted words, but it sacrifices informativeness. It is appropriately sized for a trivial tool but lacks depth.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the many sibling lorem tools and an output schema, the description fails to specify that this generates a random string of lorem ipsum sentences, or to hint at the output format. It is insufficient context for an agent to choose this tool among alternatives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema; 'count' and 'start_with_lorem' are already documented with descriptions in the input schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate lorem ipsum sentences' essentially restates the tool name 'lorem_sentences' without providing additional context or differentiation from siblings like lorem_paragraphs or lorem_words. It lacks specific verb-resource distinction beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the many lorem siblings (e.g., for sentence-level output vs. words or paragraphs). No context, prerequisites, or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lorem_wordsCInspect
Generate lorem ipsum words.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of words |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | Words joined as a single string |
| count | Yes | Number of words requested |
| words | Yes | List of generated lorem ipsum words |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the basic action without disclosing traits like randomness, determinism, or any side effects. The parameter 'count' implies generation of a specified number of words, but the description does not confirm this behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, consisting of a single sentence that immediately states the purpose. It is efficient with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of multiple sibling lorem tools and the presence of an output schema (not shown), the description is too brief. It fails to specify the output format or any distinguishing features, leaving the agent without sufficient context to confidently select this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (the only parameter 'count' is described in the schema as 'Number of words'). The description adds no additional meaning beyond the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and resource 'lorem ipsum words', which conveys the basic purpose. However, it does not differentiate from the sibling tool 'lorem_words_2', nor does it specify any unique characteristics such as output format or dictionary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus its sibling 'lorem_words_2' or other lorem generators. There is no mention of constraints, alternatives, or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lorem_words_2CInspect
Generate lorem ipsum words.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of words | |
| start_with_lorem | No | Start with 'Lorem ipsum' |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| count | Yes | |
| words | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It only states it generates words, with no mention of randomness, reproducibility, or side effects. This is insufficient for an agent to understand behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded. It is efficient, though it could benefit from slightly more detail about differentiation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input schema and presence of an output schema, the description is minimally adequate. However, the presence of nearly identical siblings makes it incomplete for proper tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters have descriptions). The tool description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate lorem ipsum words' clearly states the action (generate) and resource (lorem ipsum words). However, it does not distinguish itself from siblings like 'lorem_words' or 'generate_lorem', which likely have identical functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many similar siblings (e.g., lorem_words, generate_lorem, lorem_paragraphs), the agent has no way to choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
lowercaseBInspect
Convert text to lowercase.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to lowercase |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| lowercase | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states the obvious transformation and does not mention handling of non-alphabetic characters, locale support, or edge cases like empty strings.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise and front-loaded. However, it is too minimal to be fully informative; additional context about usage or behavior would improve completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple transformation tool with one parameter and an output schema, the description is minimally adequate. However, given the large number of sibling case-conversion tools, more detail would help the agent differentiate and use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond what the schema's parameter description ('The text to lowercase') already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: converting text to lowercase. It uses a specific verb ('Convert') and resource ('text'), and the result ('lowercase') is unambiguous. This also distinguishes it from sibling tools like 'uppercase' or 'swap_case'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool over similar siblings (e.g., 'to_lower_case', 'convert_all_cases'), nor does it mention any prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
magic_8_ballCInspect
Ask the Magic 8-Ball.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your yes/no question |
Output Schema
| Name | Required | Description |
|---|---|---|
| answer | Yes | |
| question | Yes | |
| sentiment | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose key behavioral traits such as returning a random answer, being non-deterministic, or that it is for entertainment only. No annotations are provided to compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at 4 words, but it lacks necessary behavioral context. It is front-loaded but too brief to be fully informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and presence of an output schema, the description is incomplete. It does not mention the response format, randomness, or typical usage context, leaving the agent without full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description 'Your yes/no question'. The description adds no additional meaning beyond the schema, meeting the baseline for full coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Ask the Magic 8-Ball' clearly indicates a yes/no question answering tool, leveraging cultural knowledge of a Magic 8-Ball toy. It distinguishes itself from siblings like 'yes_no' and 'flip_coin' by name, though it does not explicitly state the random nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use or alternatives provided. The description lacks context such as 'Use for fun yes/no questions' or comparisons with similar tools like 'yes_no' or 'flip_coin'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mask_textCInspect
Mask text, keeping only start/end characters visible.
| Name | Required | Description | Default |
|---|---|---|---|
| end | No | Characters to keep at end | |
| text | Yes | Text to mask | |
| start | No | Characters to keep at start | |
| mask_char | No | Masking character | * |
Output Schema
| Name | Required | Description |
|---|---|---|
| masked | Yes | Masked text with only start/end characters visible |
| original_length | Yes | Length of the original text |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description is minimal. It does not explain what masking character is used (default '*'), how start and end interact, or handle edge cases like short text.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, concise and front-loaded. Every word adds value, though more detail could be added without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and a simple tool, the description is somewhat complete but lacks specifics on masking character and edge cases. Not fully informative for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. The description adds some context by confirming start/end behavior, but does not elaborate beyond what schema already describes.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: masking text while keeping start and end characters visible. It uses a specific verb and resource, and distinguishes from sibling tools like 'replace' or 'truncate'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Does not mention when not to use or provide context for sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
maximumCInspect
Find the maximum value.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior but only states the basic function. It does not mention that the input is a comma-separated list, what happens with empty or malformed input, or the return format. Key behavioral details are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise but lacks structure; it is a single sentence without front-loading key details. While efficient, it sacrifices clarity and completeness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description is too sparse. It fails to clarify that the tool operates on a list of numbers, and it does not address potential usage context or distinguish from similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, which is already described as 'Comma-separated numbers.' The description adds no additional meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Find the maximum value,' which clearly indicates the tool's purpose of identifying the largest number. However, it does not specify that the input is a comma-separated string of numbers, and it fails to differentiate from sibling tools like 'max_value' or 'min_value'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks information about prerequisites, edge cases, or when not to use it, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
max_valueBInspect
Find maximum value.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | No | |
| code | No | |
| error | No | |
| index | No | |
| numbers | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states 'Find maximum value', which implies a read-only computation, but it does not disclose any behavioral traits such as side effects, input validation behavior, error handling, or output structure. Despite having an output schema (not shown), the description adds no behavioral context beyond what the schema implies.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at three words, front-loading the key action. It contains no unnecessary content. However, it borders on tautology (restating the name) and could include a hint about the input format to be more self-contained.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description covers the essential purpose. It does not address edge cases (e.g., empty input, non-numeric strings) but for a straightforward max calculator this is acceptable. Overall, it is mostly complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: the parameter 'numbers' already describes itself as 'Comma-separated numbers'. The tool description adds no additional meaning beyond this, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Find maximum value' clearly states the tool's purpose: to compute the maximum from a set of numbers. It uses a specific verb and resource. However, it does not differentiate from the sibling tool 'maximum', which likely has a similar purpose, so clarity is somewhat diminished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool over alternatives like 'maximum' or 'min_value'. There is no mention of prerequisites, context, or when not to use it, leaving the agent without guidance for choosing among related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
md5_checksumCInspect
Generate MD5 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| md5 | Yes | |
| text | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavior. It only says 'Generate' without mentioning output format, determinism, or any side effects, failing to add value beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only 3 words, which is under-specified for a tool with many siblings. It sacrifices informativeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite an output schema existing, the description does not mention what is returned or how the output is structured, leaving the agent with minimal actionable information.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'text' described as 'Text to hash'. The description adds nothing extra, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate MD5 checksum' clearly states the verb and resource, but does not distinguish from a sibling tool like 'hash_md5' that likely performs the same function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance provided on when to use MD5 vs other hash tools (e.g., SHA-1, SHA-256) or security considerations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
megabytes_to_gigabytesBInspect
Convert megabytes to gigabytes.
| Name | Required | Description | Default |
|---|---|---|---|
| megabytes | Yes | Size in megabytes |
Output Schema
| Name | Required | Description |
|---|---|---|
| gigabytes | Yes | |
| megabytes | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose whether the conversion uses binary (1 GB = 1024 MB) or decimal (1 GB = 1000 MB) interpretation, nor does it mention precision or output type. With no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that conveys the entire purpose without any redundant or unnecessary words. It is optimally concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple unit conversion tool with an output schema present, the description is minimally adequate but fails to specify the conversion factor or return format, which could be incomplete for precise use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with 'Size in megabytes' for the parameter. The tool description merely restates the conversion, adding no new meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert megabytes to gigabytes' is a specific verb+resource combination that clearly states the tool's function. It distinguishes itself from siblings like 'kilobytes_to_megabytes' by focusing on the direct conversion from MB to GB.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'bytes_to_human' or other unit converters. It lacks any mention of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
merge_jsonCInspect
Merge two JSON objects.
| Name | Required | Description | Default |
|---|---|---|---|
| deep | No | Deep merge nested objects | |
| json1 | Yes | Base JSON object | |
| json2 | Yes | JSON object to merge |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | No | |
| merged | No | |
| deep_merge | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. It does not disclose merge behavior (e.g., override strategy, handling of duplicate keys), whether it mutates inputs, or any side effects. The 'deep' parameter is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (5 words) but at the expense of providing critical usage details. Conciseness should not sacrifice essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks context on merge semantics, parameter behavior, and differentiation from siblings. The tool is simple but incomplete for effective agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with each parameter having a brief description. The tool description adds no additional meaning beyond what the schema provides, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Merge two JSON objects' which identifies the verb and resource, but it is vague. It does not distinguish from sibling tools like json_diff or json_minify. The 'deep' parameter behavior is not mentioned in description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Given many JSON-related sibling tools, this omission makes it harder for an agent to select the correct tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
metaphoneBInspect
Generate Metaphone phonetic encoding.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Word to encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | Input word (uppercased) |
| metaphone | Yes | Metaphone phonetic encoding |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any behavioral traits beyond the basic function. It omits details such as whether it's one-way, language support, or return format. With no annotations, the description carries full burden but is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no unnecessary words. However, it could be slightly more informative without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description is barely adequate. It lacks context about Metaphone's properties or how it compares to similar tools, leaving gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'text', which has a description. The description adds minimal value beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: generating Metaphone phonetic encoding. It specifies the resource (Metaphone encoding) and the action (generate), making it distinct from sibling tools like soundex.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives like soundex. The description lacks context for selecting this tool among many phonetic encoding options.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
meters_per_second_to_mphAInspect
Convert meters per second to miles per hour.
| Name | Required | Description | Default |
|---|---|---|---|
| mps | Yes | Speed in meters per second |
Output Schema
| Name | Required | Description |
|---|---|---|
| mph | Yes | |
| meters_per_second | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits, but it only restates the conversion purpose. There is no mention of output precision, edge cases (e.g., negative values), or any additional behavior beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-formed sentence with no unnecessary words. It is front-loaded and efficiently conveys the tool's function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For this simple unit conversion tool with one parameter and an output schema, the description sufficiently explains what the tool does. No additional context is required.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides 100% coverage for the single parameter 'mps' with a clear description. The tool description does not add any further meaning, aligning with the baseline score of 3 for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the conversion from meters per second to miles per hour. It uses a specific verb 'convert' and names both units, making it distinct from sibling conversion tools like 'kph_to_mph' or 'meters_to_feet'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. While the name implies a specific conversion, there is no explicit context about use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
meters_to_feetAInspect
Convert meters to feet.
| Name | Required | Description | Default |
|---|---|---|---|
| meters | Yes | Length in meters |
Output Schema
| Name | Required | Description |
|---|---|---|
| feet | Yes | |
| meters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It clearly states the conversion operation, which is a simple mathematical transformation. For such a tool, no additional behavioral traits (e.g., side effects, precision) need disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is appropriately front-loaded and easily scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, straightforward conversion) and the presence of an output schema (not shown but indicated by context), the description is fully complete. No additional information is necessary for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter described as 'Length in meters'). The description adds value by specifying the target unit (feet), providing context beyond the schema. This extra information justifies a score above the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert meters to feet' uses a specific verb and resource, clearly indicating the conversion direction. It distinguishes itself from its sibling tool 'feet_to_meters' which performs the reverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for converting meters to feet but provides no explicit guidance on when to use this tool versus alternatives (e.g., other length conversions). No exclusions or prerequisites are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
miles_to_kilometersCInspect
Convert miles to kilometers.
| Name | Required | Description | Default |
|---|---|---|---|
| miles | Yes | Length in miles |
Output Schema
| Name | Required | Description |
|---|---|---|
| miles | Yes | |
| kilometers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry the full burden. It does not mention whether the conversion follows the exact standard (1 mile = 1.60934 km), precision, rounding behavior, or edge cases (e.g., negative values). This lack of detail could lead to misuse.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at one sentence, which is appropriate for a simple conversion. However, it slightly under-specifies by not including any precision or usage context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is mostly adequate. Output schema exists to explain return values. However, missing behavioral details as noted under transparency reduce completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter already described as 'Length in miles'. The tool description adds no new semantic information beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action (convert) and resource (miles to kilometers). It is specific and unambiguous. However, it does not differentiate from sibling unit conversion tools, though the name itself serves as differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other unit converters. Given the large number of sibling tools, some context (e.g., 'Use this when you need to convert length from miles to kilometers') would help an AI agent decide appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
milliliters_to_cupsAInspect
Convert milliliters to US cups.
| Name | Required | Description | Default |
|---|---|---|---|
| milliliters | Yes | Volume in milliliters |
Output Schema
| Name | Required | Description |
|---|---|---|
| cups_us | Yes | |
| milliliters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It correctly implies a stateless, non-destructive read/convert operation. For a pure mathematical conversion, this is sufficient. However, it does not explicitly state that no side effects or authentication are required.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, precise sentence with no extraneous words. It is optimally concise for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one input, straightforward conversion), the description is complete. The presence of an output schema further reduces the need for return value explanation. More detail (e.g., rounding behavior) would be beneficial but is not critical for correct use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the single 'milliliters' parameter is described as 'Volume in milliliters'). The description adds no additional meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert milliliters to US cups' clearly states the verb (convert) and the specific resources (milliliters, US cups). It is unambiguous and effectively distinguishes from sibling tools like cups_to_milliliters or other unit converters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool (when converting milliliters to cups) but provides no explicit guidance on when not to use it or alternatives. For a simple unit conversion, the purpose largely dictates usage, but explicit mention of the reverse conversion tool (cups_to_milliliters) would improve guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
milliliters_to_fluid_ouncesAInspect
Convert milliliters to US fluid ounces.
| Name | Required | Description | Default |
|---|---|---|---|
| milliliters | Yes | Volume in milliliters |
Output Schema
| Name | Required | Description |
|---|---|---|
| milliliters | Yes | |
| fluid_ounces_us | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description honestly conveys a pure conversion without side effects. No annotations are provided, so the description carries the full burden. It doesn't discuss precision or edge cases, but for a simple conversion, this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, short sentence that conveys the entire purpose with no wasted words. Perfectly concise for the task.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description covers the essential operation. The presence of an output schema (indicated by context) compensates for the lack of return value details. Lacks mention of rounding or unit system, but adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'milliliters' is described in the schema as 'Volume in milliliters', and the description adds no additional meaning. With 100% schema coverage, the baseline score is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Convert') and the specific resource ('milliliters to US fluid ounces'). It uses a specific verb and resource, distinguishing it from other conversion tools like 'cups_to_milliliters' or 'liters_to_gallons_us'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The description is purely functional, but the tool name and context of sibling conversion tools imply its usage. Lacks alternative recommendations or usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
minify_jsonCInspect
Minify (compress) a JSON string.
| Name | Required | Description | Default |
|---|---|---|---|
| json_string | Yes | JSON string to minify |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | No | |
| minified | No | |
| bytes_saved | No | |
| minified_length | No | |
| original_length | No | |
| savings_percent | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only states the basic operation but does not disclose behavior such as whether it validates JSON, handles invalid input, or produces any side effects. With no annotations, the description carries the full burden and fails to provide sufficient behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), which is positive, but it lacks structure such as separating purpose from usage details. It is concise but underspecified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description still falls short by not providing error handling information or differentiation from a similarly named sibling tool. The description is minimal and incomplete for an agent to use correctly without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers the single parameter with 100% coverage. The description adds no extra meaning beyond what the schema provides, meeting the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action (minify/compress) and target (JSON string), making the purpose immediately understandable. However, it does not differentiate from the sibling tool 'json_minify' which likely performs the same function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'json_minify' or 'prettify_json'. The description lacks context about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
minimumCInspect
Find the minimum value.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| min | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavior such as handling of empty inputs, non-numeric values, or error cases. It only states the basic action without additional context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is very concise. However, it lacks structure or additional details that could improve clarity, such as the type of input or output.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, single operation) and the existence of an output schema, the description is minimally adequate. However, it could benefit from mentioning the return value or behavior with edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the 'numbers' parameter as 'Comma-separated numbers' with 100% coverage. The description adds no extra meaning beyond what the schema provides, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Find the minimum value.' which provides a specific verb and resource. While it distinguishes from the sibling 'maximum' by implication, it does not explicitly differentiate from 'min_value' or other similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool over alternatives like 'maximum' or 'min_value'. There is no mention of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
minutes_to_secondsAInspect
Convert minutes to seconds.
| Name | Required | Description | Default |
|---|---|---|---|
| minutes | Yes | Time in minutes |
Output Schema
| Name | Required | Description |
|---|---|---|
| minutes | Yes | |
| seconds | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It only states the conversion without disclosing behavioral traits such as handling of negative numbers, rounding, or output type. This is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no extraneous information. It is appropriately front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally complete. However, it lacks context on edge cases or result format, which could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the parameter with a description ('Time in minutes'). The description adds no further semantic value beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert minutes to seconds' clearly specifies the verb (Convert) and resource (minutes to seconds), distinguishing it from sibling tools like hours_to_minutes or seconds_to_hms.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the tool name and description, but there is no explicit guidance on when to use this vs. alternatives. For a simple conversion, this is acceptable but not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
min_valueCInspect
Find minimum value.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| min | No | |
| code | No | |
| error | No | |
| index | No | |
| numbers | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must carry full burden. It fails to disclose handling of non-numeric input, empty strings, or error conditions. The input format (comma-separated string) is only in the schema, not in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at 4 words, front-loaded, and no redundant text. However, it sacrifices informativeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits key context such as expected input format, behavior on invalid input, and relationship to sibling tools. For a simple tool, more completeness is expected.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'numbers' is fully described in the schema as 'Comma-separated numbers'. The description adds no additional meaning beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Find minimum value' clearly states the action and resource. It is specific but does not differentiate from the sibling 'minimum' tool, though the name 'min_value' hints at its role.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'minimum' or 'max_value'. No mention of prerequisites, edge cases, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
moduloAInspect
Calculate a modulo b (remainder of a divided by b).
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | Dividend | |
| b | Yes | Divisor |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | No | |
| b | No | |
| code | No | |
| error | No | |
| result | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose important behavioral traits such as the handling of division by zero (b=0) or error conditions. For a mathematical operation, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that immediately communicates the tool's purpose. No wasted words, front-loaded with the operation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical tool with a high-coverage input schema and an output schema, the description is nearly complete. However, it lacks mention of a critical edge case (b=0), which would be expected for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions 'Dividend' and 'Divisor'. The overall description adds context by explaining the operation, which reinforces the role of the parameters. This adds value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate a modulo b (remainder of a divided by b)' clearly states the operation with a specific verb and resource. It distinguishes itself from sibling math tools like 'add' or 'divide' by explicitly naming the modulo operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for remainder calculation but does not explicitly specify when to use this tool versus alternatives like 'divide' or 'integer division'. No guidance on prerequisites or exclusions is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
morse_decodeBInspect
Decode Morse code to text.
| Name | Required | Description | Default |
|---|---|---|---|
| morse | Yes | Morse code to decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| morse | No | |
| decoded | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry full behavioral disclosure, but it gives no details on supported characters, case sensitivity, invalid input handling, or output format. This is a significant gap for a decoding tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter decoding tool with an existing output schema, the description is minimally adequate but does not explain the return value or behavior, missing opportunities for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the sole parameter with 100% coverage. The description provides no additional semantic meaning beyond 'morse' and 'decode'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Decode Morse code to text' uses a specific verb (Decode) and resource (Morse code), clearly distinguishing it from its sibling 'morse_encode'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'morse_encode' or other encoding/decoding tools. Lacks prerequisites or contextual cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
morse_encodeBInspect
Encode text to Morse code.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to encode to Morse code |
Output Schema
| Name | Required | Description |
|---|---|---|
| morse | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavior. It does not specify supported characters, spacing conventions, or error handling for invalid input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), but it is under-specified. It could be expanded to include important details without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one simple parameter and an output schema. The description is minimally complete but could be improved by explaining the output format (e.g., dots and dashes with spaces).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the parameter 'text' described as 'Text to encode to Morse code'. The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Encode text to Morse code' clearly states the action (encode) and the resource (text to Morse code). It is specific and distinguishes from the sibling tool 'morse_decode'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'morse_decode'. No edge cases or prerequisites are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mortgage_calculatorCInspect
Calculate mortgage details.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual interest rate (percentage) | |
| years | No | Loan term in years | |
| home_price | Yes | Home price | |
| down_payment | No | Down payment |
Output Schema
| Name | Required | Description |
|---|---|---|
| home_price | Yes | |
| term_years | Yes | |
| total_paid | Yes | |
| loan_amount | Yes | |
| down_payment | Yes | |
| total_interest | Yes | |
| monthly_payment | Yes | |
| annual_rate_percent | Yes | |
| down_payment_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It fails to disclose any behavioral traits such as what is returned (e.g., monthly payment, total interest), assumptions (e.g., fixed rate, amortization), or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (one sentence), but it lacks substantive information. It is not front-loaded with key details; it is merely a generic statement that could apply to many tools.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given four parameters, no annotations, and an output schema (not described), the description is completely inadequate. It does not help an agent understand what the tool returns or when to use it compared to related tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so parameters are documented. However, the description adds no additional meaning beyond the generic phrase, missing the chance to explain parameter relationships or usage (e.g., effect of down_payment on loan amount).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate mortgage details' uses a verb and resource, but it is vague and does not specify what exactly is calculated (e.g., monthly payment, total cost, amortization). It does not distinguish from sibling tools like loan_payment or compound_interest.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. No context about prerequisites or scenarios provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mph_to_kphAInspect
Convert miles per hour to kilometers per hour.
| Name | Required | Description | Default |
|---|---|---|---|
| mph | Yes | Speed in miles per hour |
Output Schema
| Name | Required | Description |
|---|---|---|
| kph | Yes | |
| mph | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations to contradict or supplement. Description accurately describes the conversion, but lacks details about edge cases or precision.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence that fully conveys the tool's purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool, the description is complete. Output schema exists, so no need to describe return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter well-described. The description adds no additional semantic meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the function: converting miles per hour to kilometers per hour, using a specific verb-resource pair. It distinguishes from sibling tools like kph_to_mph or knots_to_kph.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicit usage: the description indicates when to use it (when needing to convert mph to kph), but no explicit guidance on when not to use it or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
multiplyBInspect
Multiply two or more numbers together.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers to multiply |
Output Schema
| Name | Required | Description |
|---|---|---|
| numbers | Yes | |
| product | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral aspects such as error handling for malformed input, precision limits, or performance characteristics. The description simply states the function without depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. It is front-loaded and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple arithmetic tool with an output schema, the description covers the basic operation. However, it lacks context on edge cases (e.g., empty input, non-numeric strings) and does not mention return format or precision.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: the 'numbers' parameter is described as 'Comma-separated numbers to multiply' in the schema. The tool description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'multiply' and the resource 'numbers', and specifies it works for two or more numbers, which distinguishes it from sibling tools like 'add' or 'subtract'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., add, calculate_product). No context for prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
name_to_hexBInspect
Convert a CSS color name to hex.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | CSS color name |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | No | |
| name | Yes | |
| found | Yes | |
| available_colors | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It fails to mention case sensitivity, support for non-standard names, or error handling when the name is not recognized. The minimal description leaves the agent uninformed about critical behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence that efficiently conveys the tool's purpose. It is front-loaded with the action and contains no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate but lacks important details like supported CSS color names or behavior for invalid inputs. It could be more complete with a note about specification compliance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'name', which is described as 'CSS color name'. The description adds no additional meaning beyond the schema, so it meets the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: convert a CSS color name to hex. The verb 'Convert' and the resource 'CSS color name' are specific, and the tool is distinct from sibling color conversion tools like hex_to_rgb or rgb_to_hex.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, limitations, or when not to use it. With siblings like hex_to_rgb and name to hex, the agent has no basis for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nearest_powerBInspect
Find the nearest power of a base to a number.
| Name | Required | Description | Default |
|---|---|---|---|
| base | No | Base | |
| number | Yes | Number to find nearest power for |
Output Schema
| Name | Required | Description |
|---|---|---|
| base | No | |
| error | No | |
| number | No | |
| exponent | No | |
| lower_power | No | |
| upper_power | No | |
| nearest_power | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear the full burden. It does not explain what 'nearest' means (e.g., absolute difference, floor/ceiling), nor does it address edge cases or return value structure. The output schema exists but the description adds no behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence—concise but perhaps too brief. It front-loads the core purpose but omits useful details without becoming overly long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with full schema coverage and an output schema, the description is minimal. It lacks explanation of the algorithm, return value format, or edge cases, leaving the agent with incomplete context for proper invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters having descriptions in the schema. The description adds no additional meaning beyond what the schema already provides, meeting the baseline but not exceeding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool finds the nearest power of a base to a number, which distinguishes it from sibling tools like 'power' (which likely computes exact power) and other mathematical functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs alternatives, such as 'power' for exact exponentiation or 'log' for logarithmic calculations. No mention of context or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
netmask_to_cidrAInspect
Convert subnet mask to CIDR prefix length.
| Name | Required | Description | Default |
|---|---|---|---|
| netmask | Yes | Netmask (e.g., 255.255.255.0) |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| netmask | Yes | |
| cidr_prefix | No | |
| cidr_notation | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description only states the conversion. It does not disclose behavior for invalid input, return format, or edge cases. However, as a pure conversion, it is acceptable but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no wasted words. Perfectly concise for this simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, return values are not needed. The tool is simple and the description adequately covers its purpose. Could mention handling of invalid netmasks, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with description and example. The description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert subnet mask to CIDR prefix length' clearly specifies the action (convert) and the resource (subnet mask to CIDR). It distinguishes from sibling tools like cidr_to_netmask (reverse) and cidr_info (provides info).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use vs alternatives. Given the simplicity, it is implied that if you have a netmask and need a CIDR, use this tool, but no exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
network_infoCInspect
Get information about a network.
| Name | Required | Description | Default |
|---|---|---|---|
| network | Yes | Network in CIDR notation (e.g., 192.168.1.0/24) |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | No | |
| netmask | No | |
| network | Yes | |
| version | No | |
| hostmask | No | |
| last_host | No | |
| first_host | No | |
| is_private | No | |
| num_addresses | No | |
| prefix_length | No | |
| network_address | No | |
| broadcast_address | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It only says 'get information,' implying a read-only operation, but does not describe side effects, required permissions, or the nature of the returned data.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but too brief to be informative. It does not benefit from being front-loaded with key details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is an output schema (not shown), but the description does not mention what information is returned. For a tool with many siblings, more detail is needed to ensure the agent selects it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter is well-described in the schema with an example. The description adds no additional meaning beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description says 'Get information about a network,' which is vague and does not specify what kind of information. It fails to distinguish from sibling tools like cidr_info or ip_info that also retrieve network-related data.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives. There are many network-related sibling tools, and the description does not clarify the tool's specific purpose or usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
normalize_urlCInspect
Normalize a URL to a canonical form.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to normalize | |
| sort_params | No | Sort query parameters | |
| lowercase_host | No | Lowercase hostname | |
| remove_default_port | No | Remove default port (80/443) | |
| remove_trailing_slash | No | Remove trailing slash from path |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| normalized | Yes | |
| changes_made | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behaviors such as modifications to case, port, trailing slash, or parameter sorting. The schema parameters imply these but the description itself lacks transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded and efficient. However, it could be slightly more verbose to add context without losing clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters and an output schema, the description is too brief. It does not explain what 'canonical form' means or how the parameters affect it, leaving the agent with incomplete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the parameter titles and descriptions already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool normalizes a URL to a canonical form, which is a specific verb-resource pair. It distinguishes from siblings like parse_url and build_url, though 'canonical form' is somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like is_valid_url, extract_domain, or add_query_param. The description does not provide any context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
normalize_whitespaceCInspect
Normalize whitespace (multiple spaces to single).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to normalize |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| normalized | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description lacks details on handling tabs, newlines, or leading/trailing whitespace. Does not disclose whether only spaces are affected or all whitespace.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single phrase with no extra words. Front-loaded with purpose, though could benefit from slight expansion without losing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given output schema exists but not provided, description is minimally adequate. For a simple string operation with many siblings, more context on behavior would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of parameters with description. Tool description adds clarification that normalization targets multiple spaces, but does not specify format or constraints beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it normalizes whitespace by converting multiple spaces to single. Distinguishes from sibling tools like remove_whitespace which remove all spaces.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like trim or remove_whitespace. Does not specify prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nth_cubeBInspect
Get the nth cube number.
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | Which cube number |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | |
| cube | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden of behavioral disclosure. It does not mention edge cases (e.g., behavior for n near limits), return type, or any error handling. The minimal description adds no extra behavioral context beyond the input schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is front-loaded and easy to parse. However, it could include a brief note on the output to improve completeness without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter math tool, the description is functional but sparse. With an output schema present, the description does not need to detail return values, but a mention of the integer result or range would enhance completeness. It meets minimal adequacy.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the description adds no additional meaning beyond 'Which cube number' already present in the schema. Baseline of 3 is appropriate as the description does not enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the nth cube number' is specific and unambiguous. The verb 'Get' and resource 'cube number' clearly state the tool's action and result. Among siblings like 'cube', 'nth_square', 'nth_prime', it distinctly identifies its mathematical operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'cube' (which likely returns the cube of a given number) or other nth-series tools. There are no exclusions or context hints to aid tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nth_primeAInspect
Get the nth prime number.
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | Which prime number (1=2, 2=3, etc.) |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | |
| prime | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the basic operation. It does not disclose return type, performance, or side effects, though the tool is a pure math function. The schema covers constraints (n range).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One efficient sentence front-loads the purpose. No wasted words, but could include additional helpful context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (single parameter with full schema description and an output schema), the description provides enough context for selection and basic use, though it omits explicit mention of the return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (parameter 'n' has a description explaining it represents which prime number). The tool description adds no extra parameter information, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description 'Get the nth prime number' uses a specific verb ('get') and resource ('nth prime number'), clearly distinguishing it from sibling tools like 'is_prime' or 'primes_in_range'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description lacks context for selecting this tool over related ones like 'nth_root' or 'primes_in_range'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nth_rootBInspect
Calculate the nth root of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | Root degree | |
| number | Yes | Number to find root of |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | No | |
| code | No | |
| error | No | |
| number | No | |
| result | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully convey behavioral traits. It only states the basic operation, failing to disclose how edge cases (negative numbers, root degree restrictions, accuracy) are handled. The agent gains no insight into potential pitfalls or returned value ranges.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently conveys the core purpose. It is appropriately brief for a simple mathematical function, though it sacrifices some helpful detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity, high schema coverage, and the presence of an output schema, the description is mostly complete for the basic operation. However, it omits usage context and edge-case behavior, which are partly compensated by the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no extra meaning beyond the schema parameter descriptions ('Root degree', 'Number to find root of'). Baseline score of 3 is appropriate as the description does not enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and the resource 'nth root', distinguishing it from sibling tools like square_root or cube_root which handle specific roots. The name and description together precisely indicate this tool computes the nth root for any given degree.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it does not mention that square_root or cube_root are optimized for specific cases, nor does it specify prerequisites or limitations. The description lacks explicit when/when-not instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nth_squareBInspect
Get the nth square number.
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | Which square number |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | |
| square | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose any behavioral traits beyond the basic operation. Since no annotations are provided, the description carries the full burden but only states the function's purpose. For a simple mathematical computation, this is minimally adequate but lacks details such as idempotency or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one short sentence. It contains no unnecessary words or information, effectively communicating the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one integer parameter, pure computation, output schema exists), the description is mostly complete. It could benefit from clarifying that the result is the square of the given index, but it is sufficient for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a description for the single parameter 'n' ('Which square number'). The description adds no additional meaning beyond what the schema provides. With 100% schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get the nth square number' clearly identifies the verb and resource. It distinguishes itself from siblings like 'square' (which likely computes square of a given number) by specifying 'nth', implying it takes an index and returns the square of that index. However, it does not explicitly differentiate from other nth-series tools like `nth_cube` or `nth_prime`.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'square' or 'nth_cube'. There is no mention of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nth_triangularAInspect
Get the nth triangular number.
| Name | Required | Description | Default |
|---|---|---|---|
| n | Yes | Which triangular number |
Output Schema
| Name | Required | Description |
|---|---|---|
| n | Yes | |
| formula | Yes | |
| triangular | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It only repeats the name without adding behavioral context like formula, error handling, or return type.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no superfluous words, perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical tool with one parameter and an output schema present, the description is adequate. However, it could benefit from mentioning the formula or range implications.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter description already states 'Which triangular number'. The tool description adds minimal extra meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb "Get" and the resource "the nth triangular number", which is specific and distinct from sibling tools like is_triangular, nth_cube, nth_square, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit guidance on when to use this tool versus alternatives, but the context is clear and the tool's purpose is straightforward.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
nullAInspect
Returns null. For when you need a null.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description explicitly states the tool returns null, with no hidden side effects or behaviors. Since there are no annotations, the description fully discloses the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two short sentences that front-load the core action ('Returns null'). Every word is necessary and no information is missing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the trivial nature of the tool (no parameters, simple output), the description is complete. The existence of an output schema (not shown) further reduces the need for additional detail.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With no parameters and 100% schema description coverage, the description adds no additional meaning beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns null, using specific verb and resource. It distinguishes itself from siblings like 'true_endpoint' and 'false_endpoint' by its unique return value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'For when you need a null' provides clear context for when to use the tool. However, it does not explicitly mention alternatives or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
number_to_romanBInspect
Convert a number to Roman numerals.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to convert (1-3999) |
Output Schema
| Name | Required | Description |
|---|---|---|
| roman | Yes | |
| number | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description adds no behavioral context beyond the input schema (e.g., no mention of validation, error handling, or standard Roman numeral conventions). The schema already defines range 1-3999.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no wasted words. Perfectly concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion with one parameter and an output schema, the description is adequate. Could optionally mention the output format but is still fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a parameter description 'Number to convert (1-3999)'. The tool description adds no extra meaning; baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert a number to Roman numerals.' clearly states the verb (convert) and resource (number to Roman numerals). It distinguishes itself from siblings like 'roman_to_number' and 'number_to_words'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., roman_to_number, number_to_words). The description does not mention criteria for selection or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
number_to_wordsBInspect
Convert a number to words.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| words | Yes | |
| number | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides no behavioral details beyond the input schema. It does not disclose how negative numbers, zero, or large numbers are handled, nor the language or formatting style of the output. With no annotations, the description should compensate, but it does not.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. Direct and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (one parameter, simple operation), the description is minimally adequate but lacks behavioral context like output format or handling of edge cases. Since an output schema exists, return values need not be explained, but usage context is still missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (parameter 'number' described in schema). The description adds little meaning beyond the schema, but baseline for high coverage is 3. It does not add extra context about the parameter's behavior, such as range implications.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert a number to words.' clearly states the specific action (convert) and resource (number to words). It distinguishes from sibling tools like 'number_to_roman' or 'decimal_to_binary' by specifying the output format is words.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives such as 'number_to_roman' or other number converters. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ounces_to_gramsCInspect
Convert ounces to grams.
| Name | Required | Description | Default |
|---|---|---|---|
| ounces | Yes | Weight in ounces |
Output Schema
| Name | Required | Description |
|---|---|---|
| grams | Yes | |
| ounces | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose any behavioral traits such as conversion precision, output format, or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it lacks important details that could be included without much additional length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the existence of an output schema, the description is minimally adequate. However, it could be improved by specifying the conversion factor or that it uses standard ounces.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes the 'ounces' parameter as 'Weight in ounces' with 100% coverage. The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the conversion from ounces to grams, which is a specific verb and resource. However, it does not provide any differentiation from sibling tools like 'grams_to_ounces' or other unit converters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers no guidance on when to use this tool versus alternatives. It simply states the conversion without context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
padBInspect
Pad text to a specified length.
| Name | Required | Description | Default |
|---|---|---|---|
| char | No | Padding character | |
| side | No | Side to pad (left, right, both) | right |
| text | Yes | The text to pad | |
| length | Yes | Target length |
Output Schema
| Name | Required | Description |
|---|---|---|
| length | Yes | |
| padded | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It fails to mention edge cases, default padding character, side default, or behavior when text exceeds target length.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short but lacks necessary details, making it under-specified rather than concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description omits behavioral details critical for a tool with 4 parameters and no annotations. It is incomplete for safe and effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents parameters. The description adds only a general phrase about padding to a specified length, not adding meaningful detail beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool pads text to a specified length. It specifies the verb 'pad' and the resource 'text', and it distinguishes from siblings like trim or truncate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide explicit guidance on when to use this tool vs alternatives like truncate or other padding functions. Usage is implied but not clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
parse_dateCInspect
Parse a date string.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Date string to parse | |
| format | No | Input format | %Y-%m-%d |
Output Schema
| Name | Required | Description |
|---|---|---|
| iso | No | |
| code | No | |
| error | No | |
| format | No | |
| parsed | No | |
| original | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose error handling, timezone assumptions, supported date formats, or whether parsing is lenient or strict. 'Parse a date string' is insufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it is under-specified. It is not earning its place as it could be expanded to include key details without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the presence of an output schema, the description is too brief for a date parsing tool that likely involves timezones, invalid inputs, and multiple formats. It lacks completeness given the complexity implied by sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with both parameters documented. The description adds no additional meaning beyond what the schema already provides, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Parse a date string' clearly states the verb and resource, but it is vague and does not differentiate from sibling tools like format_date, validate_date, or date_diff, which also involve date strings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as format_date (for output formatting) or validate_date (for checking validity). The description provides no context for when to choose parse_date.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
parse_urlBInspect
Parse a URL into its components.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to parse |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| is_secure | Yes | |
| components | Yes | |
| query_params | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavior. It only states the function but doesn't specify what 'components' means, any side effects, or return structure. The existence of an output schema is noted but not leveraged in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise with one short sentence. It is front-loaded but may be too sparse for a tool with no annotations or additional guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, output schema present), the description is still lacking in usage context and behavioral details. It does not fully compensate for the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the parameter 'url' described as 'URL to parse'. The description adds no additional meaning beyond the schema, so baseline is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (parse), resource (URL), and result (its components). It distinguishes the tool from siblings like 'parse_url_2' and 'build_url' by being specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'parse_url_2' or 'normalize_url'. The description lacks context about prerequisites or typical scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
parse_url_2CInspect
Parse a URL into its components.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to parse |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | No | |
| code | No | |
| path | No | |
| port | No | |
| error | No | |
| query | No | |
| netloc | No | |
| scheme | No | |
| fragment | No | |
| hostname | No | |
| password | No | |
| username | No | |
| query_params | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must convey behavioral traits. It only states the action without disclosing edge cases, authentication needs, rate limits, or output structure. The existence of an output schema mitigates this slightly, but the description itself adds no behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant information. It efficiently conveys the core purpose without extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of a sibling tool with a nearly identical name, the description fails to distinguish itself. It also omits any information about return values or behavior, making it incomplete for an agent to fully understand the tool's role.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'url', which has a basic description. The tool description adds nothing beyond the schema's explanation. Baseline 3 is appropriate as no additional semantics are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'parse' and the resource 'URL', indicating the tool's purpose. However, it does not differentiate from the sibling tool 'parse_url', which has an identical name except for the '2' suffix, leading to potential confusion for the AI agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'parse_url', 'build_url', or 'normalize_url'. The description lacks context for selection, leaving the agent without decision-making support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pascal_caseBInspect
Convert text to PascalCase.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| pascal_case | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose how non-alphanumeric characters, spaces, or numbers are handled, leaving behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise and front-loaded. A single sentence communicates the core purpose with no extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and presence of output schema, the description is minimally adequate. However, it lacks edge case handling details, which could be expected for string conversion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'text' described as 'The text to convert'. The description adds no extra meaning beyond the schema, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (convert) and resource (text) and specifies the output format (PascalCase). However, it does not differentiate from siblings like camel_case or to_pascal_case, which might cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like camel_case, to_pascal_case, etc. The description does not provide context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
password_entropyBInspect
Calculate password entropy (bits of randomness).
| Name | Required | Description | Default |
|---|---|---|---|
| password | Yes | Password to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| strength | Yes | |
| has_digits | Yes | |
| has_special | Yes | |
| charset_size | Yes | |
| entropy_bits | Yes | |
| has_lowercase | Yes | |
| has_uppercase | Yes | |
| password_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as output format, performance implications, or safety (e.g., read-only). For a calculation tool that takes a password, it should at least state it does not store or transmit the password.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema is indicated, the description does not need to detail return values. However, the description lacks context about interpretation of entropy values (e.g., scale). It is minimally complete for a simple calculation tool but could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the 'password' param is described as 'Password to analyze'). The tool description adds no further semantic meaning beyond what the schema already provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'calculate' and the resource 'password entropy' with the unit 'bits of randomness'. It is specific about what the tool does. However, it does not differentiate from the sibling tool 'analyze_password', which may also calculate entropy. This keeps it from a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives like 'analyze_password' or 'validate_password_strength'. The description provides no context about prerequisites or recommended use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
percentageAInspect
Calculate what percentage value is of total.
| Name | Required | Description | Default |
|---|---|---|---|
| total | Yes | The total | |
| value | Yes | The value |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| total | No | |
| value | No | |
| percentage | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must cover behavioral details. It only states the core operation, omitting important behavior such as handling division by zero, negative numbers, or rounding. This is insufficient for a calculation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that communicates the tool's function without extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculation tool with an output schema, the description is nearly complete. However, it lacks mention of edge cases (e.g., total=0), which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with trivial descriptions ('The total', 'The value'). The tool description adds no extra meaning beyond what the schema provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate what percentage value is of total.' It specifies the verb 'calculate' and the resource 'percentage', distinguishing it from sibling tools like 'percentage_change'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Usage is implied by the simple calculation, but no exclusions or context are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
percentage_changeBInspect
Calculate percentage change between two values.
| Name | Required | Description | Default |
|---|---|---|---|
| new_value | Yes | New value | |
| old_value | Yes | Original value |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| direction | No | |
| new_value | No | |
| old_value | No | |
| percent_change | No | |
| absolute_change | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must disclose behavior. It fails to mention whether the result is signed, handling of zero old_value, or precision. Minimal behavioral information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundant words. Efficient but could benefit from slightly more detail without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values are covered. However, the description lacks edge-case behavior (e.g., division by zero) and sign convention. Adequate for a simple tool but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds no extra meaning beyond the schema; parameter descriptions are generic. No elaboration on order or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates percentage change between two values, with a specific verb and resource. It distinguishes itself from siblings like 'percentage' or 'calculate_discount'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. No mention of prerequisites or context. Among many calculation tools, the description provides no usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pick_randomCInspect
Pick random item(s) from a list.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of items to pick | |
| items | Yes | Comma-separated items to pick from |
Output Schema
| Name | Required | Description |
|---|---|---|
| from | No | |
| count | No | |
| picked | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral traits such as whether items are picked with replacement, uniqueness, or return format. Since no annotations are provided, the description carries the full burden but fails to add meaningful behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no waste. It is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of many similar sibling tools, the description lacks completeness. It does not help distinguish from alternatives, and the absence of output schema or behavioral details leaves gaps for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already explains both parameters. The description adds no extra meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Pick') and the resource ('random item(s) from a list'). It is specific but does not differentiate from similar sibling tools like 'random_choice' or 'random_element', which also pick random items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description gives no indication of when to use this tool over alternatives, nor any prerequisites or context for correct usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pingAInspect
Ping endpoint. Returns pong.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| ping | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description states 'Returns pong,' implying non-destructive, quick behavior. However, it does not disclose any potential side effects or limitations, though for a ping tool this is minimal concern.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, 7 words total. Every word earns its place. Front-loaded with 'Ping' immediately conveys the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a parameterless tool with an output schema, the description is fully adequate. It states the action and the expected response, leaving no gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so the description cannot add meaning beyond the schema. Baseline for zero-param tools is 4, and the description correctly avoids unnecessary detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Ping endpoint. Returns pong.' which succinctly defines the tool as a connectivity check. It uses a specific verb-resource pair and is distinct from all sibling tools, which are utility functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or alternatives, but the tool's purpose is self-evident. Lacks exclusionary context, but for a simple ping, the implied usage is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
point_in_polygonAInspect
Check if a point is inside a polygon (ray casting algorithm).
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Point latitude | |
| lon | Yes | Point longitude | |
| polygon | Yes | Polygon vertices as lat1,lon1;lat2,lon2;lat3,lon3... |
Output Schema
| Name | Required | Description |
|---|---|---|
| point | Yes | |
| is_inside | Yes | |
| polygon_vertices | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions the ray casting algorithm, offering some insight into behavior. However, it does not disclose edge cases, coordinate system assumptions, or performance implications. Without annotations, the description carries full burden but only partially addresses it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the core purpose. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return values need not be explained. However, the description lacks usage guidelines and behavioral details (e.g., point on boundary behavior). For a simple tool, it is minimally acceptable but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The tool description essentially restates the polygon format, adding no new meaning beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: checking if a point is inside a polygon using ray casting. It is specific and distinguishes from sibling tools like polygon_area or polygon_centroid.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool over alternatives, nor any context on prerequisites or exclusions. Given numerous sibling geo tools, this lack of guidance is a significant gap.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
polygon_areaBInspect
Calculate area of a polygon on Earth's surface.
| Name | Required | Description | Default |
|---|---|---|---|
| unit | No | Unit: km2 or mi2 | km2 |
| polygon | Yes | Polygon vertices as lat1,lon1;lat2,lon2;lat3,lon3... |
Output Schema
| Name | Required | Description |
|---|---|---|
| area | Yes | |
| unit | Yes | |
| polygon_vertices | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must disclose behavioral traits. It lacks details on algorithm (e.g., planar vs geodesic), assumptions, precision, or limitations. Only states basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff. Clearly front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists but description does not mention output format, precision, or behavior for invalid inputs. Lacks context for a geographic calculation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are well-documented. Description adds no extra meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it calculates the area of a polygon on Earth's surface, specifying verb, resource, and context. It is distinct from siblings like polygon_centroid or point_in_polygon.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use or when not to use this tool. No mention of prerequisites, alternatives, or typical use cases among many sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
polygon_centroidBInspect
Calculate centroid of a polygon.
| Name | Required | Description | Default |
|---|---|---|---|
| polygon | Yes | Polygon vertices as lat1,lon1;lat2,lon2;lat3,lon3... |
Output Schema
| Name | Required | Description |
|---|---|---|
| centroid | Yes | |
| polygon_vertices | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It implies a safe read operation (calculate) but does not disclose any behavioral traits beyond the basic purpose. The presence of an output schema mitigates the lack of return value description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no fluff. While concise, it could be slightly expanded with context without becoming wordy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool with one parameter and an output schema, the description is mostly sufficient but lacks examples or notes on coordinate system. It is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, and the parameter description is clear. The tool description does not add additional semantic meaning beyond what the input schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Calculate') and the resource ('centroid of a polygon'), with a specific verb+resource combination that distinguishes it from siblings like 'polygon_area'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, or any prerequisites/limitations. The description is purely functional without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
polyline_lengthBInspect
Calculate total length of a polyline.
| Name | Required | Description | Default |
|---|---|---|---|
| unit | No | Unit: km or mi | km |
| polyline | Yes | Polyline points as lat1,lon1;lat2,lon2;lat3,lon3... |
Output Schema
| Name | Required | Description |
|---|---|---|
| unit | Yes | |
| points | Yes | |
| segments | Yes | |
| total_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. It only states the basic function and omits details such as input validation assumptions, performance characteristics, or handling of invalid polylines.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no extraneous words. It is front-loaded and efficient, earning the highest score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, the description is adequate. An output schema exists to define return values, so the description need not elaborate. However, it lacks detail on edge cases or coordinate system assumptions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameters 'polyline' and 'unit' are already documented. The description adds no extra semantic information beyond what the schema provides, warranting a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate total length of a polyline' uses a specific verb ('calculate') and resource ('length of a polyline'), clearly distinguishing it from sibling geometry tools like 'distance' or 'haversine_distance'. The purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'distance' or 'haversine_distance'. There is no mention of prerequisites, context, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
port_infoBInspect
Get information about a port number.
| Name | Required | Description | Default |
|---|---|---|---|
| port | Yes | Port number |
Output Schema
| Name | Required | Description |
|---|---|---|
| port | Yes | |
| port_type | Yes | |
| description | Yes | |
| service_name | Yes | |
| is_well_known | Yes | |
| requires_root | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations and no behavioral details in description; does not disclose what information is returned or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single clear sentence with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and low complexity, description is adequate but minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage, description adds no extra meaning beyond 'port number' already in schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool retrieves information about a port number, but does not differentiate from siblings like ip_info or network_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use or not use this tool; usage is implied from the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
pounds_to_kilogramsCInspect
Convert pounds to kilograms.
| Name | Required | Description | Default |
|---|---|---|---|
| pounds | Yes | Weight in pounds |
Output Schema
| Name | Required | Description |
|---|---|---|
| pounds | Yes | |
| kilograms | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description fails to disclose any behavioral traits such as precision, rounding, error handling, or return format. The description is merely a restatement of the function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (5 words) and front-loaded, but it lacks substance. While concise, it misses opportunities to add helpful context without adding bulk.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no nested objects), the description should cover basic behavioral aspects. However, it omits details about the output (e.g., 'Returns weight in kilograms'), which is important since an output schema is indicated but not shown.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter schema fully describes the only parameter (pounds with type number and description 'Weight in pounds'), so schema coverage is 100%. The description adds no additional semantic value beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert pounds to kilograms' clearly states the verb (convert) and the specific resources (pounds, kilograms). It distinguishes itself from sibling tools like 'kilograms_to_pounds' by specifying the direction of conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., kilograms_to_pounds or other unit converters). There is no explicit context or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
powerBInspect
Calculate base raised to the power of exponent.
| Name | Required | Description | Default |
|---|---|---|---|
| base | Yes | The base | |
| exponent | Yes | The exponent |
Output Schema
| Name | Required | Description |
|---|---|---|
| base | Yes | |
| result | Yes | |
| exponent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose any behavioral traits beyond the basic operation. It doesn't mention potential issues like overflow, precision, or return type.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the tool's purpose without wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, two parameters, and the presence of an output schema, the description is adequate. It could mention the return type, but the output schema compensates for that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides full coverage for both parameters with descriptions. The description adds no extra meaning beyond what the schema already conveys, so it meets the baseline for a tool with high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the operation ('Calculate base raised to the power of exponent'), using a specific verb and resource. It distinguishes this tool from sibling math operations like add, subtract, multiply, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any exclusions or context. The agent is left to infer usage from the name and schema alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
present_valueBInspect
Calculate present value of a future amount.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual discount rate (percentage) | |
| years | Yes | Number of years | |
| future_value | Yes | Future value |
Output Schema
| Name | Required | Description |
|---|---|---|
| years | Yes | |
| future_value | Yes | |
| rate_percent | Yes | |
| present_value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds no behavioral insights beyond the basic calculation. Given the absence of annotations, the description should disclose assumptions (e.g., compounding frequency, annual discount rate, rounding). The schema covers parameter types but not behavioral implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It efficiently conveys the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the output schema exists (not shown) and the input schema is complete, the description lacks context on compounding frequency, valid ranges, or edge cases. For a financial tool, this is minimal but adequate given schema richness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add any additional meaning or context to the parameters (rate, years, future_value) beyond what is already in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb (calculate) and clearly identifies the resource (present value of a future amount). It is concise and distinguishes from siblings like future_value or compound_interest, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as future_value, rule_of_72, or loan_payment. There are no prerequisites, limitations, or context-specific recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
prettify_jsonBInspect
Prettify (format) a JSON string.
| Name | Required | Description | Default |
|---|---|---|---|
| indent | No | Indentation spaces | |
| sort_keys | No | Sort keys alphabetically | |
| json_string | Yes | JSON string to prettify |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | No | |
| prettified | No | |
| original_length | No | |
| prettified_length | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It does not mention error handling for invalid JSON, character encoding, or whether the tool validates input. The brief description lacks necessary behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence that efficiently conveys the core purpose. However, it could be slightly expanded to include key behavioral details without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple formatting tool, the description is adequate but lacks details on return format, error behavior, or performance considerations. The presence of an output schema reduces the need for return value explanation, but behavioral context is still missing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions for indent, sort_keys, and json_string. The tool description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Prettify (format) a JSON string' uses a specific verb ('prettify' or 'format') and clearly identifies the tool's purpose of formatting JSON strings. It distinguishes itself from sibling tools like json_minify and json_validate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives like json_minify or json_validate. The usage is implied but not clarified beyond the basic purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
prime_factorsAInspect
Get prime factors of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to factorize |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| is_prime | Yes | |
| prime_factors | Yes | |
| unique_factors | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not explain return format, whether factors are unique or repeated, or any edge cases (e.g., input is prime). The output schema exists but is not shown in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at 5 words, front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple math tool with output schema present, the description is adequate but lacks usage guidelines and behavioral details. It could be moderately enhanced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description 'Number to factorize'. The tool description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get prime factors of a number.' is a clear verb+resource combination. It distinguishes from siblings like 'is_prime' or 'primes_in_range' by focusing on factorization.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, but the purpose is straightforward enough that an agent can infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
primes_in_rangeAInspect
Get all prime numbers in a range.
| Name | Required | Description | Default |
|---|---|---|---|
| end | Yes | End of range | |
| start | Yes | Start of range |
Output Schema
| Name | Required | Description |
|---|---|---|
| end | No | |
| count | No | |
| error | No | |
| start | No | |
| primes | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full burden. It describes the operation accurately but lacks details on behavior like inclusive bounds, return format, or the fact that it returns a list. However, the schema constraints (start min 0, end max 100000) add some transparency. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that captures the tool's purpose without any unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool and the presence of an output schema (according to context signals), the description is complete enough. It covers the essential purpose and scope. Minor missing details like inclusive bounds are less critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the two parameters, so the schema already documents their meaning. The description adds no additional semantics beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'all prime numbers', and specifies the scope 'in a range'. It distinguishes itself from sibling tools like is_prime, prime_factors, and nth_prime by indicating it returns all primes in a range.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as is_prime for checking a single number or prime_factors for factoring. It does not mention constraints like bounds or performance considerations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
private_ip_rangesAInspect
Get RFC 1918 private IP address ranges.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| loopback | Yes | |
| link_local | Yes | |
| private_ranges | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden for behavioral disclosure. It states the tool returns private IP ranges but does not describe the return format, structure, or any behavioral aspects like caching. It is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that directly states the tool's purpose. It contains no unnecessary words and is highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there are no parameters and an output schema exists, the description provides sufficient context. However, it could briefly mention the well-known ranges (e.g., 10.0.0.0/8, 172.16.0.0/12, 192.168.0.0/16) for completeness, but the output schema likely covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema coverage is 100%. The description does not need to add parameter semantics, and the baseline of 4 is appropriate since no additional param info is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns RFC 1918 private IP address ranges, which is a specific and well-defined resource. It distinguishes itself from sibling tools like cidr_info (which provides info about a given CIDR) and is_private_ip (which checks if an IP is private).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives like cidr_info or expand_cidr. However, the purpose is self-explanatory, so a score of 3 reflects the lack of explicit usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
punycode_decodeBInspect
Decode Punycode to Unicode.
| Name | Required | Description | Default |
|---|---|---|---|
| encoded | Yes | Punycode to decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| decoded | No | |
| punycode | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It only states the function without disclosing any behavioral traits such as error handling, input validation, or output format. The output schema exists but is not referenced in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence, four words) and front-loaded. It is easy to parse, though it sacrifices completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (which defines the return type), the description is minimally adequate. However, it lacks any context about edge cases, performance, or error behavior, which would be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a description for the single parameter ('Punycode to decode'), and the tool description adds no additional meaning beyond that. With 100% schema coverage, a score of 3 is baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Decode Punycode to Unicode' clearly states the verb (decode) and resource (Punycode to Unicode), and it distinguishes this tool from its sibling 'punycode_encode' which performs the inverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., punycode_encode, base64_decode, etc.). There is no mention of context, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
punycode_encodeBInspect
Encode Unicode to Punycode (for internationalized domain names).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Unicode text to encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| original | No | |
| punycode | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description does not disclose any behavioral traits such as errors, limitations, or side effects. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, concise sentence with no wasted words. Efficiently communicates the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the straightforward nature of the tool and presence of an output schema, the description is adequate. It mentions the domain name context, which is helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter 'text', so baseline is 3. Description adds no extra meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Encode', resource 'Unicode to Punycode', and context 'for internationalized domain names'. It easily distinguishes from sibling punycode_decode.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like punycode_decode. Implied usage only.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
query_string_to_jsonAInspect
Convert a URL query string to JSON object.
| Name | Required | Description | Default |
|---|---|---|---|
| query_string | Yes | Query string to convert (without ?) |
Output Schema
| Name | Required | Description |
|---|---|---|
| json | No | |
| json_string | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; description is too brief. It does not disclose behavior details such as handling of missing '?' prefix, error cases, or encoding. The parameter description specifies 'without ?' but main description does not, creating potential ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, directly states purpose. Could be slightly improved by noting the 'without ?' clarification from the parameter description to avoid ambiguity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter) and presence of an output schema, the description is sufficiently complete for basic use. Lacks error handling or edge case notes but adequate for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter description is clear. However, the tool description does not add any new meaning beyond what the schema already provides, so baseline score is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Convert' and specifies the resource 'URL query string' and output 'JSON object'. Distinguishes from sibling `json_to_query_string` by direction of conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when or when not to use this tool. Usage is implied by the name and description, but no alternatives or exclusions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rad_to_degBInspect
Convert radians to degrees.
| Name | Required | Description | Default |
|---|---|---|---|
| radians | Yes | Angle in radians |
Output Schema
| Name | Required | Description |
|---|---|---|
| degrees | Yes | |
| radians | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description lacks any behavioral details such as precision, range, or error handling for this conversion.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, front-loaded with verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool with one parameter and output schema; minimal description is sufficient but could mention output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no additional meaning beyond the schema's parameter description. Baseline 3 given high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Convert' and the specific resource 'radians to degrees', distinguishing it from inverse sibling 'deg_to_rad'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides no guidance on when to use this tool versus alternatives (e.g., deg_to_rad). No context for appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_addressCInspect
Generate random address(es) using Faker with locale support.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of addresses to generate | |
| locale | No | Locale (e.g., en_US, en_GB, de_DE, ja_JP) |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full burden. It only mentions locale support but does not disclose any behavioral traits such as whether the generation is deterministic, side effects, or performance considerations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is to the point. It could include a quick note about default count or limits, but it remains efficient and free of unnecessary fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown) and the simplicity of the tool, the description is adequate. However, it lacks contextual completeness by not addressing usage guidelines or sibling differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for both 'count' and 'locale'. The description adds no additional meaning beyond what the schema provides, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool generates random addresses using Faker with locale support, making its primary function evident. However, it does not differentiate from a similar sibling tool 'generate_addresses', which may cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'generate_addresses' or other random generators. The description lacks context for appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_booleanAInspect
Generate random boolean value(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of booleans to generate | |
| true_weight | No | Probability of True (0.0 to 1.0) |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| values | No | |
| true_count | No | |
| false_count | No | |
| true_weight | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist. The description does not contradict them but fails to disclose behavioral traits such as the ability to generate multiple booleans or the weighted probability via 'true_weight'. The schema provides these details, but the description adds no extra value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that efficiently conveys the tool's purpose without extraneous information. It is appropriately sized and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and full parameter documentation in the input schema, the description is adequate. However, it could mention the tool's ability to generate multiple booleans or weighted randomness to provide additional context, but this is not a critical gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description carries minimal burden. It adds no meaning beyond the schema, which already documents 'count' and 'true_weight' with defaults and ranges.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates random boolean values, using a specific verb ('Generate') and resource ('random boolean value(s)'). It distinguishes from siblings like random_integer or random_float, which produce different types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like flip_coin, random_coin, or random_choice. The description lacks explicit context or exclusions, leaving the agent without differentiation cues.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_bytesAInspect
Generate cryptographically secure random bytes.
| Name | Required | Description | Default |
|---|---|---|---|
| length | No | Number of bytes | |
| encoding | No | Output encoding: hex, base64 | hex |
Output Schema
| Name | Required | Description |
|---|---|---|
| bytes | Yes | |
| value | Yes | |
| encoding | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds 'cryptographically secure', which is a crucial behavioral trait not conveyed by annotations (none provided). However, it does not clarify how output depends on the 'encoding' parameter or other behaviors like performance or entropy source. This is adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-front-loaded sentence with zero redundancy. Every word earns its place, making it highly efficient for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple random generation tool with an output schema and no annotations, the description is minimal but covers the core purpose. However, given the large set of sibling random tools, more context (e.g., typical use cases, security implications) would improve completeness. Score reflects adequacy without standout.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add any extra meaning about the parameters (length, encoding) beyond what the schema already provides. No additional context or examples are given.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate cryptographically secure random bytes.' clearly states the verb (generate) and resource (random bytes), with the key qualifier 'cryptographically secure' distinguishing it from simple random bytes. It is specific and actionable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like random_bytes_2, random_password, or random_token. Given the many sibling tools for generating random data, this omission severely reduces the agent's ability to choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_bytes_2BInspect
Generate cryptographically secure random bytes.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Output format: hex, base64, urlsafe | hex |
| length | No | Number of bytes to generate |
Output Schema
| Name | Required | Description |
|---|---|---|
| bytes | Yes | |
| value | Yes | |
| format | Yes | |
| secure | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description highlights that bytes are cryptographically secure, which is a key behavioral trait. However, with no annotations provided, more details about performance, blocking, or security guarantees would be beneficial. The description is minimal but conveys essential security property.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence. It is front-loaded and concise, but could benefit from a brief mention of typical use cases or output format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description adequately covers the purpose. However, it doesn't mention any edge cases or restrictions beyond what is in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have complete descriptions in the schema (100% coverage). The tool description adds no additional semantic information about the parameters beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it generates cryptographically secure random bytes. However, it does not distinguish from sibling 'random_bytes', which likely has a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over other random generation tools (e.g., random_bytes, random_integer, etc.). There is no mention of use cases or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_cardBInspect
Draw random playing card(s) from a deck.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of cards to draw | |
| include_jokers | No | Include joker cards |
Output Schema
| Name | Required | Description |
|---|---|---|
| card | No | |
| cards | No | |
| count | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It does not clarify key behaviors: whether the deck is standard, whether drawing is without replacement (implied by max count 52), or how jokers affect the deck. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence with no filler. Every word is essential. Excellent conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two optional parameters and an output schema (presumably describing the return value), the description is mostly adequate. However, it could explicitly mention the deck type (52 cards + jokers) to avoid ambiguity. Nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with clear descriptions for both 'count' and 'include_jokers'. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Draw random playing card(s) from a deck' uses a specific verb and resource, clearly stating the tool's action and scope. It effectively distinguishes from sibling tools like flip_coin, roll_dice, and random_choice.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives such as random_coin, random_dice, or random_choice. There is no mention of context, exclusions, or alternative tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_choiceCInspect
Pick random item(s) from a list.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of choices to make | |
| items | Yes | Comma-separated items to choose from | |
| allow_duplicates | No | Allow same item to be chosen multiple times |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It does not mention any side effects, idempotency, or error conditions (e.g., empty list). Only a minimal functional statement is provided.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise at one sentence. No superfluous content; every word is necessary for stating the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite simple parameters and no output schema, the description does not clarify the return format (e.g., array, string). Given the lack of output schema, completeness is lacking.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond what the schema already provides for all three parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Pick random item(s) from a list' clearly states the verb and resource. It distinguishes from many sibling random tools that generate random values (e.g., random_boolean, random_number) but may overlap with random_element, though the specific list format is unique.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like random_element or random_weighted_choice. No mention of prerequisites or context where this tool is particularly useful.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_coinCInspect
Flip a coin (optionally biased).
| Name | Required | Description | Default |
|---|---|---|---|
| bias | No | Probability of heads (0.5 = fair coin) | |
| count | No | Number of coin flips |
Output Schema
| Name | Required | Description |
|---|---|---|
| bias | No | |
| count | No | |
| flips | No | |
| heads | No | |
| tails | No | |
| result | No | |
| heads_percent | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral disclosure burden. It mentions optional bias but does not disclose outcomes (heads/tails), effect of count parameter, or any side effects. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, front-loaded. Could be slightly more informative, but remains concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with output schema, the description is minimally adequate. It covers the core function but omits details about return format and edge cases like count > 1.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so both parameters are described in the schema. The description adds no new information; 'optionally biased' is redundant with schema's 'Probability of heads'. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Flip a coin') and the optional bias. It is specific and distinct from generic random tools, though it does not explicitly differentiate from sibling 'flip_coin'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like random_boolean or flip_coin. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_colorCInspect
Generate a random color.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| rgb | Yes | |
| rgb_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description fails to disclose any behavioral traits such as output format (hex, RGB, etc.), randomness properties, or color range. The agent has no insight into what the tool actually returns.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with four words, which is appropriate for a zero-parameter tool. It is front-loaded and to the point, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of parameters and the presence of an output schema, the description is minimally adequate. However, it provides no hint of the output format or how it compares to sibling tools, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema coverage is 100%. The description adds no additional meaning beyond the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a random color' states the verb and resource clearly, but it does not differentiate from sibling tools like 'random_color_2' or 'generate_color'. The purpose is clear but not unique among similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. No context, exclusions, or prerequisites are mentioned, leaving the agent without direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_color_2CInspect
Generate random color(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of colors to generate | |
| format | No | Output format: hex, rgb, hsl, rgba | hex |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| format | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description should disclose behavioral traits. It only states 'random color(s)' without mentioning randomness source, distribution, or any edge cases. Lacks transparency beyond what the schema already shows.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short and to the point, but arguably too terse. Still, it is front-loaded and wastes no words. Could be slightly improved with a bit more context without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (multiple siblings, output schema present, two parameters), the description is inadequate. It does not explain the output format, distinguish from similar tools, or provide any usage hints. Incomplete for effective tool selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description does not add any additional meaning beyond the schema; it only repeats the idea of generating random colors without explaining parameter behavior or format options.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states 'Generate random color(s)' which is a clear verb and resource. However, it does not differentiate from the sibling tool 'random_color', nor does it indicate that it can generate multiple colors or specific formats beyond the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives like 'random_color', 'generate_shades', 'blend_colors', etc. The description does not provide context for appropriate usage or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_companyBInspect
Generate random company name(s) using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of companies to generate | |
| locale | No | Locale (e.g., en_US, ja_JP, de_DE) |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions 'using Faker' but does not disclose non-deterministic behavior, that it can generate up to 100 companies (which is in the schema), or any side effects. Minimal behavioral context beyond the basic purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no unnecessary words. It is well-structured for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the description lacks mention of default behavior, locale impact, and differentiation from similar siblings. An output schema exists, so return values need not be explained, but overall completeness is adequate with clear gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers both parameters with descriptions, so the description adds no additional meaning. Baseline score of 3 is appropriate as schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates random company names using Faker, with a specific verb and resource. However, it does not distinguish itself from the sibling tool 'generate_companies', which might serve a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'generate_companies' or other random generators. There is no mention of prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_complimentBInspect
Generate a random compliment.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Name to compliment | You |
Output Schema
| Name | Required | Description |
|---|---|---|
| name | Yes | |
| compliment | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are absent, and the description offers no behavioral details beyond the action. Traits like randomness (implied by name) or personalization via 'name' are not explained, leaving the agent uncertain about behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no extraneous information, front-loaded with the core purpose. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (one optional parameter, output schema exists), the context is nearly complete. However, it lacks details on tone or variety of compliments, which could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the parameter 'name' having a description in the schema. The description does not add additional meaning, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a random compliment.' clearly states the action (generate) and the resource (compliment), distinguishing it from sibling tools like random_trivia or dad_joke. It's specific and not a tautology.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like random_trivia or friendly_roast. The description is minimal and does not provide any context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_coordinatesBInspect
Generate random geographic coordinates.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of coordinate pairs to generate | |
| region | No | Region: us, eu, asia, or null for worldwide | |
| decimals | No | Decimal precision |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| region | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It only states the basic function and adds no behavioral details such as the distribution of coordinates (e.g., uniform worldwide or biased by region), the effect of the region parameter, or any side effects. This is insufficient for a complete understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is immediately understandable. It is appropriately sized for a simple tool with no required parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and has an output schema, the description lacks context about common use cases. Without guidance on when to generate vs validate coordinates or use other geographic tools, an agent might not select it appropriately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides, e.g., it does not explain that 'region' restricts to specific areas or that 'decimals' affects precision.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description "Generate random geographic coordinates" clearly states a specific verb and resource. It distinguishes itself from sibling tools like random_address or coordinate-related tools, as it focuses solely on generating random coordinates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not mention when to prefer this tool over alternatives such as random_address, generate_addresses, or is_valid_coordinates. Without context, an agent may misuse it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_credit_cardAInspect
Generate random credit card details (fake, for testing only).
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Card type: visa, mastercard, amex, discover, or null for random | |
| count | No | Number of cards to generate |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| values | No | |
| disclaimer | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses that the data is fake and for testing, which is the key behavioral trait. No further details needed for a simple generation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence conveys the purpose and usage constraint with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with an output schema and clear purpose, the description is complete. All necessary information is provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the description adds no extra meaning beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate', the resource 'random credit card details', and the purpose 'for testing only'. It distinguishes from siblings like 'validate_credit_card' and 'format_credit_card' by focusing on generation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates use for testing only, providing clear context. It does not explicitly list when not to use or name alternatives, but the purpose is obvious for a simple generation tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_dateCInspect
Generate random date(s) within a range.
| Name | Required | Description | Default |
|---|---|---|---|
| end | No | End date (YYYY-MM-DD) | 2025-12-31 |
| count | No | Number of dates to generate | |
| start | No | Start date (YYYY-MM-DD) | 2020-01-01 |
| format | No | Output format: iso, us, eu, unix | iso |
Output Schema
| Name | Required | Description |
|---|---|---|
| end | No | |
| code | No | |
| count | No | |
| error | No | |
| start | No | |
| value | No | |
| format | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description is the only source. It does not disclose defaults, count limit, format options, or that dates are uniformly random. Lacks behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence, very concise but too brief; could include more context without being verbose. Adequate but not optimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters and no annotations, the description is too minimal. It does not address usage constraints, output behavior, or provide adequate context for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are documented. The description adds no additional meaning beyond the schema, so baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and resource 'random date(s)' within a range. However, it does not differentiate from similar siblings like 'generate_dates' or 'random_time'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'random_time' or 'generate_dates'. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_diceCInspect
Roll dice with configurable sides.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of dice to roll | |
| sides | No | Number of sides on the die |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| min | Yes | |
| sum | Yes | |
| count | Yes | |
| rolls | Yes | |
| sides | Yes | |
| average | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the action without mentioning return format (likely an array), randomness guarantees, or any constraints. This is insufficient for a complete understanding.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one phrase) and front-loaded. However, it may be too brief, missing opportunities to add value. Still, it is not verbose and meets efficiency standards.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description could be more informative about what the tool returns and how it differentiates from siblings. It feels incomplete for an agent to make an informed decision.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema provides full descriptions for both parameters (count and sides) including defaults and bounds. The description adds no new information beyond 'configurable sides', so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Roll dice') and the customization ('configurable sides'). It effectively communicates what the tool does, though it does not differentiate from the sibling 'roll_dice' which likely serves the same purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, especially the similar 'roll_dice' tool. The agent is left without context to choose appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_elementBInspect
Get random chemical element(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of elements to pick |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| element | No | |
| elements | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits such as randomness source, repeatability, or output format, leaving important details unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that is concise, but it may be too terse, sacrificing completeness for brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description lacks information about the output format, making it incomplete. Although an output schema exists, the description should still provide context about what is returned.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no extra meaning beyond the schema's parameter description. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get random chemical element(s).' clearly specifies the action (get) and the resource (random chemical element(s)), distinguishing it from many sibling tools like random_address or random_boolean.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives; lacks context on when not to use it or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_emailBInspect
Generate random email address(es) using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| safe | No | Use safe domains (example.com, etc.) vs realistic domains | |
| count | No | Number of emails to generate | |
| domain | No | Specific domain (e.g., 'example.com') | |
| locale | No | Locale for name-based emails |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only mentions using Faker, but does not disclose any behavioral traits such as idempotency, side effects, or performance implications. The description is too minimal for a tool with no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately sized and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations, the description should provide more context. While an output schema exists to clarify return format, the description lacks usage guidelines and behavioral details. It is minimally viable but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so parameters are already well-documented. The description adds no additional meaning beyond 'using Faker', which is acceptable but not enhancing. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates random email addresses using Faker. It specifies the verb 'generate' and the resource 'random email address(es)'. However, it does not distinguish from the sibling tool 'generate_emails', which likely serves a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'generate_emails'. The description lacks any context for usage or exclusions, leaving the agent without clear decision criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_emojiCInspect
Get random emoji(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of emojis | |
| category | No | Category: faces, animals, food, nature, objects, all | all |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| emojis | No | |
| category | No | |
| combined | No | |
| available | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only states the basic function without disclosing any specifics about randomness, limitations, or side effects. The schema already provides parameter details, so the description adds no new behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short with one sentence, which makes it concise. However, it is too sparse to be fully effective; it earns its place but could benefit from more detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional params, output schema exists), the description is minimal and lacks completeness. The presence of a sibling 'random_emoji_2' suggests a need for differentiation, which is absent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'count' and 'category' clearly described in the schema. The description does not add additional meaning beyond what the schema provides, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get random emoji(s)' clearly states the action (Get) and resource (random emoji(s)), making the purpose obvious. However, it does not distinguish from the sibling tool 'random_emoji_2', which likely serves a similar purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'random_emoji_2' or other random generation tools. There is no mention of context, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_emoji_2CInspect
Get random emoji(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of emojis to pick | |
| category | No | Category: faces, animals, food, nature, objects, or null for all |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| emoji | No | |
| emojis | No | |
| category | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits beyond getting random emojis. It does not mention randomness behavior (e.g., with/without replacement) or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence, but it could be slightly more informative without being verbose. It is adequately structured but minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the presence of an output schema, the description is somewhat complete. However, it lacks comparison to the sibling and does not elaborate on return format or edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already describes both parameters with count and category details (100% coverage). The description adds no additional meaning beyond what the schema provides, so baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get random emoji(s)' clearly states the action and resource, but it does not differentiate from sibling 'random_emoji'. It is specific and unambiguous, so scores 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. There is a sibling 'random_emoji', and the description does not clarify the difference or when each should be used.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_excuseBInspect
Generate a random excuse.
| Name | Required | Description | Default |
|---|---|---|---|
| context | No | Context: work, school, social | work |
Output Schema
| Name | Required | Description |
|---|---|---|
| excuse | Yes | |
| context | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It discloses the basic random behavior but does not elaborate on whether the excuse list is fixed, deterministic, or any side effects. Minimal but adequate for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. It states the purpose efficiently, though it could be slightly more informative. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, full schema coverage, and existing output schema, the description is adequate. It does not require extensive context. The parameter behavior is covered by the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (context parameter described as 'Context: work, school, social'). The tool description adds no additional meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a random excuse' clearly states the action and resource. It is specific to excuses but does not differentiate from sibling random generators like random_trivia or random_compliment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention when not to use it or provide context for preference over other random generators.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_floatCInspect
Generate random float(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | How many numbers to generate | |
| max_val | No | Maximum value | |
| min_val | No | Minimum value | |
| decimals | No | Decimal places |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| min | Yes | |
| count | No | |
| number | No | |
| numbers | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavioral traits beyond generating floats. It omits details about distribution, bounds, or side effects. The description adds minimal value over the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence. However, it is so brief that it sacrifices informativeness. Could be a 5 if it also clarified key aspects, but it's adequately sized for its minimal content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given four parameters and an output schema, the description is incomplete. It does not explain that the output is a list when count > 1 or the range behavior. The description leaves significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions. It does not explain the interaction between parameters like count, min, max, and decimals.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate random float(s).' clearly states the verb (generate) and resource (random float). However, it does not distinguish from the sibling tool 'random_float_2', which likely has a different behavior. The purpose is clear but lacks differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like random_integer or random_float_2. The description provides no context for appropriate use cases or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_float_2BInspect
Generate random floating-point number(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of floats to generate | |
| max_val | No | Maximum value | |
| min_val | No | Minimum value | |
| decimals | No | Number of decimal places |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | No | |
| min | No | |
| count | No | |
| value | No | |
| values | No | |
| decimals | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description is minimal but accurate. No annotations provided, so description carries full burden; missing details on distribution (uniform) and range beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Very short one-sentence description that is clear and to the point, though could include more context without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has output schema but description does not mention return format. For a simple random number generator, the description is adequate but not rich.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameters are fully described in schema (100% coverage). Description adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates random floating-point numbers. However, it does not distinguish from sibling tool 'random_float'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like random_float, random_integer, or random_gaussian.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_gaussianCInspect
Generate random number(s) from a Gaussian (normal) distribution.
| Name | Required | Description | Default |
|---|---|---|---|
| mean | No | Mean (center) of the distribution | |
| count | No | Number of values to generate | |
| std_dev | No | Standard deviation | |
| decimals | No | Decimal places |
Output Schema
| Name | Required | Description |
|---|---|---|
| mean | No | |
| count | No | |
| value | No | |
| values | No | |
| std_dev | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose important behavioral traits such as whether the generation is cryptographically secure, or the implications of the count parameter (returns an array). This leaves the agent uninformed about side effects or constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The single-sentence description is concise and front-loaded. It communicates the core function efficiently, though additional details about parameters could be integrated without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description does not need to explain return values. However, it misses mentioning the plural nature of 'number(s)' and edge cases like std_dev=0. While adequate for a simple tool, it could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with descriptions for all 4 parameters. The description adds no new semantic value beyond what the schema already provides, warranting a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate') and the resource ('random number(s) from a Gaussian distribution'), making the purpose explicit. However, it does not specify the plural behavior (count parameter) within the description itself, which slightly reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over siblings like random_float, random_number, or other distribution tools. An AI agent would lack context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_hexCInspect
Generate random hexadecimal string(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of hex strings to generate | |
| length | No | Number of hex characters | |
| prefix | No | Include 0x prefix | |
| uppercase | No | Use uppercase letters |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| length | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description has the full burden of disclosing behavior. It only states the basic function but omits important details such as whether the output is cryptographically secure, that multiple strings are returned when count > 1, or any warnings about potential randomness quality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, short sentence that is front-loaded and easy to parse. It is concise but slightly too minimal, missing an opportunity to add value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and 4 parameters, the description is incomplete. It does not explain that the tool can generate multiple hex strings, nor does it clarify how the output structure changes with the count parameter. This leaves gaps for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all four parameters (count, length, prefix, uppercase). The description adds no extra meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Generate') and the resource ('random hexadecimal string(s)'), making the tool's purpose unambiguous. However, it does not explicitly differentiate from similar sibling tools like random_string or random_bytes, which could also generate hex-like strings but are intended for general use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives. The description provides no context about appropriate use cases, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_integerBInspect
Generate random integer(s) within a range.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of integers to generate | |
| unique | No | Ensure all values are unique (count must be <= range) | |
| max_val | No | Maximum value (inclusive) | |
| min_val | No | Minimum value (inclusive) |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | No | |
| min | No | |
| code | No | |
| count | No | |
| error | No | |
| value | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It does not state whether the generator is cryptographically secure, whether it uses a pseudo-random algorithm, or any other behaviors. The simple statement is insufficient for full behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence with no unnecessary words. It is front-loaded with the action and resource, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a moderate complexity with 4 parameters and an output schema. The description is minimal but combined with the schema it is functionally adequate. However, it lacks context about default behavior, range inclusivity, and edge cases, which would justify a higher score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing detailed parameter descriptions. The description adds no additional meaning beyond the schema; it merely restates 'within a range'. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (generate) and resource (random integers) and the scope (within a range). While it does not explicitly differentiate from siblings like random_float or random_number, the precision is sufficient for a 4.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives such as random_float, random_number, or other random generation tools. The description provides no when-to-use or when-not-to-use information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_ipBInspect
Generate random IP address(es).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of IPs to generate | |
| private | No | Generate private IPs only (v4 only) | |
| version | No | IP version: 4 or 6 |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| values | No | |
| version | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations and description only says 'Generate random IP address(es)'. Does not disclose that generation can be controlled by count, private, or version parameters, nor any behavioral traits like randomness quality or restrictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, one sentence with no unnecessary words. Front-loaded with core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with an output schema; description covers the basic function. But could mention that it returns IP(s) based on parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, each parameter has a description in the schema. Description adds no additional meaning beyond what schema already provides, baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description uses a specific verb 'Generate' and resource 'random IP address(es)', clearly distinguishing it from other random generation tools like random_uuid or random_color.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., random_address, ip_info). No conditions or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_jobBInspect
Generate random job title(s) using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of job titles to generate | |
| locale | No | Locale (e.g., en_US, fr_FR, de_DE) |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral traits such as whether the tool is read-only, requires authentication, or has side effects. Since no annotations are provided, the description should cover this, but it only states the action without any behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the purpose. It is front-loaded and concise, though it could include a brief note on usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally complete. However, it lacks usage differentiation from sibling tools, which is a gap for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already describes both parameters. The description adds no additional meaning beyond the schema, which is adequate for a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and the resource 'random job title(s)', using 'Faker' to indicate the underlying library. This distinguishes it from sibling tools like random_company or random_name, as it specifically generates job titles.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as random_company or random_name. There are no prerequisites, exclusions, or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_macBInspect
Generate random MAC address(es).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of MAC addresses to generate | |
| separator | No | Separator: :, -, or none | : |
| uppercase | No | Use uppercase letters |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| values | No | |
| separator | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only says 'generate random MAC address(es)' without disclosing whether addresses are valid (unicast/multicast, locally administered), uniqueness, or output behavior beyond what parameters imply.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with no unnecessary words. One sentence captures the essence.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of output schema, the description is adequate but could mention that generated addresses follow standard MAC format and respect separator/case settings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema, but the schema itself is clear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool generates random MAC addresses, using a specific verb and resource. It is distinct from sibling random generation tools like random_uuid or random_hex.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., random_hex for hex strings, validate_mac for validation). The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_nameCInspect
Generate random name(s) using Faker with locale support.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Name type: first, last, full, prefix, suffix | full |
| count | No | Number of names to generate | |
| gender | No | Gender hint: male, female, or null for random | |
| locale | No | Locale (e.g., en_US, es_ES, ja_JP, zh_CN, fr_FR, de_DE) |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | No | |
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Minimal behavioral disclosure. Only states basic function. No details on randomness source, performance characteristics, or side effects. Without annotations, description should provide more context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. Efficiently communicates core functionality. Could be slightly more descriptive but not verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and full schema plus output schema, description is adequate. However, it lacks any mention of output structure or edge cases, which keeps it from being fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 4 parameters with descriptions. Description adds no extra meaning beyond schema, hence baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it generates random names with locale support. Specific verb-resource pair, but does not explicitly differentiate from sibling 'generate_names' tool, though the use of Faker is implied.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives like 'random_person' or 'generate_names'. No when-not-to-use or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_numberCInspect
Generate random integer(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | How many numbers to generate | |
| max_val | No | Maximum value (inclusive) | |
| min_val | No | Minimum value (inclusive) |
Output Schema
| Name | Required | Description |
|---|---|---|
| max | Yes | |
| min | Yes | |
| count | No | |
| number | No | |
| numbers | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only states 'Generate random integer(s)' without mentioning that it can return multiple values, the default range (0-100), or that all parameters are optional. The agent might assume it returns a single integer. The schema covers details, but the description lacks behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it very concise. It front-loads the core purpose. However, it sacrifices detail for brevity, which is acceptable given the schema's richness, but it could add one more sentence for clarity without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and exists among many random generators, the description is incomplete. It fails to mention that it can generate multiple integers or that the output is an array (implied by output schema). The agent may need to infer functionality from the schema, which is risky. The description should be more descriptive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (all parameters have descriptions), so the baseline is 3. The description adds no additional meaning beyond the schema; it does not explain parameter roles or relationships (e.g., min_val must be ≤ max_val). It does not reduce ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates random integers, matching the name. However, it does not distinguish it from the sibling 'random_integer', which likely has a similar purpose but possibly different parameters (e.g., single integer vs. multiple). The verb 'generate' and resource 'integer(s)' are specific, but ambiguity remains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'random_integer', 'random_float', or 'random_boolean'. There are no prerequisites, exclusions, or context for selection. The agent must infer usage from the tool's parameters alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_passwordBInspect
Generate secure random password(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of passwords to generate | |
| length | No | Password length | |
| numbers | No | Include numbers | |
| symbols | No | Include symbols | |
| lowercase | No | Include lowercase letters | |
| uppercase | No | Include uppercase letters | |
| exclude_ambiguous | No | Exclude ambiguous characters (0O1lI) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| count | No | |
| error | No | |
| value | No | |
| length | No | |
| values | No | |
| entropy_bits | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description is minimal but adequate for a generation tool; it doesn't disclose security guarantees or randomness source, but no annotations are present to contradict. Moderate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single clear sentence with no fluff. Perfectly concise for the information conveyed.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 7 parameters and an output schema (not shown), the description lacks a high-level overview of features like character types and count, making it slightly incomplete for full understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, so the description adds no extra meaning. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates secure random passwords, which is specific. However, it does not differentiate from sibling tools like generate_password, generate_password_2, etc., which have similar purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other password generators or alternatives. There is no mention of context, prerequisites, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_personBInspect
Generate complete random person profile(s) using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of people to generate | |
| gender | No | Gender hint: male, female, or null for random | |
| locale | No | Locale (e.g., en_US, es_ES, ja_JP, zh_CN) |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It does not disclose side effects, rate limits, or specifics about what constitutes a complete profile (e.g., fields included), which is important for an agent to understand the output structure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the core purpose without extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity and presence of an output schema, the description is adequate but vague about what the profile contains. More specificity would improve completeness, especially with many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all 3 parameters. The description adds no additional semantic value beyond the schema, meeting baseline expectations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates complete random person profiles using Faker, which implies multiple attributes beyond just a name or address. However, it does not explicitly differentiate from siblings like random_name or random_address, which generate single attribute types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus the many sibling random generators. It does not exclude alternatives or provide context for when a complete profile is preferable over individual attributes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_phoneBInspect
Generate random phone number(s) using Faker with locale-appropriate formats.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of phone numbers to generate | |
| locale | No | Locale for phone format (e.g., en_US, en_GB, de_DE, ja_JP) |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It mentions using Faker for locale-appropriate formats, implying non-destructive generation. However, it does not disclose whether numbers are valid, if seeds are used, or other behavioral traits, which is minimal but acceptable for a simple generator.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence that is front-loaded with the core action. No wasted words; every part is informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low complexity and presence of an output schema, the description covers purpose and parameters adequately. However, it lacks usage differentiation from siblings, preventing a perfect score.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The description reinforces locale usage but adds no extra semantic depth beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Generate' and resource 'random phone number(s)', specifying locale-appropriate formats. It distinguishes from 'format_phone' (formatting existing numbers) but not from the sibling 'generate_phones' which appears similar, lacking differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool vs similar siblings like 'generate_phones' or 'random_phone' alternatives. No context for selection is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_shuffleBInspect
Randomly shuffle a list of items.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items to shuffle |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| original | Yes | |
| shuffled | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior but only states 'randomly shuffle'. It omits whether the shuffle is in-place or idempotent, and lacks any caution about potential side effects or randomness guarantees.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence with no superfluous words. It efficiently conveys the core function.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description is minimally adequate but lacks behavioral details that would help an agent use it safely. It does not cover whether randomness is cryptographically secure or any constraints.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema coverage is 100% with a clear description for 'items'. The tool description adds no extra meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'shuffle' and the resource 'list of items', making the tool's purpose unambiguous. While a sibling tool 'shuffle_list' exists, the description does not differentiate between them, but the core action is well-defined.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'shuffle_list', nor are any prerequisites or exclusions mentioned. The agent receives no context for appropriate selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_stringCInspect
Generate random string(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | How many strings to generate | |
| length | No | Length of string | |
| charset | No | Character set: alphanumeric, alpha, numeric, hex, base64 | alphanumeric |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| length | Yes | |
| string | No | |
| charset | Yes | |
| strings | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It only states that it generates strings, failing to mention randomness quality, seed behavior, output format, or any side effects. Essential context is missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short (one phrase) but not structurally helpful. It is concise but lacks any front-loading of critical information. It could benefit from a brief sentence on output or use case.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters and an output schema, the description does not provide enough context. It omits details on the return format (array of strings?), length constraints beyond schema, and behavior with default values. The agent is left to infer too much.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter descriptions in the input schema are complete (100% coverage), and the tool description adds no additional meaning. The description simply says 'Generate random string(s).' which does not enhance understanding beyond the schema fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate random string(s)' clearly states the action (generate) and resource (random string). However, it does not distinguish this tool from similar siblings like random_string_2, random_password, or random_text, which also generate random strings. The verb-resource pair is specific but undifferentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives or what use cases are appropriate. There is no mention of prerequisites, exclusions, or comparisons to sibling tools, leaving the agent without decision logic.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_string_2CInspect
Generate random string(s) from specified character set.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of strings to generate | |
| length | No | Length of the string | |
| charset | No | Character set: alphanumeric, alpha, numeric, lowercase, uppercase, hex, base64, ascii, symbols | alphanumeric |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| length | No | |
| values | No | |
| charset | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears full responsibility for behavioral disclosure. It only states the basic purpose, omitting details about randomness quality (e.g., cryptographically secure), default behavior, or output format. The presence of an output schema does not fully compensate for the lack of behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and front-loaded. While it is not verbose, it could include more useful information without becoming lengthy. It efficiently communicates the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (3 parameters, output schema present, good schema descriptions), the description provides the minimum viable information. However, it lacks context about return format or number of strings generated (implied by count). The agent might need additional context to differentiate from siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the baseline is 3. The description adds minimal value beyond the schema, merely mentioning 'specified character set' which corresponds to the charset parameter. No additional semantics are provided for count or length.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and the resource 'random string(s)' with a specified character set. However, it does not distinguish itself from the similarly named sibling tool 'random_string', which could cause confusion for an AI agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'random_string' or 'random_password'. The description lacks any context about preferred use cases or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_textBInspect
Generate random text using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No | Type: word, words, sentence, sentences, paragraph, paragraphs, text | paragraph |
| count | No | Number of items (words, sentences, or paragraphs) | |
| locale | No | Locale for text generation |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | Yes | |
| value | Yes | |
| locale | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description bears the full burden of behavioral disclosure. It states the tool generates random text using Faker but does not mention return type, side effects, or randomness guarantees. The schema and output schema partially compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no unnecessary words. It is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and well-documented input parameters, the description is minimally adequate. However, it lacks context about Faker's capabilities and comparisons to similar sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no additional meaning beyond the schema. The mention of 'Faker' hints at locale but does not elaborate on parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate random text using Faker' clearly states the verb (generate) and resource (random text), and mentions the underlying library (Faker). It distinguishes itself from siblings that generate specific types like random_name or random_address.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as lorem_words, random_string, or generate_lorem. The description lacks context for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_timeBInspect
Generate random time(s) of day.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of times to generate | |
| format | No | Output format: 24h, 12h, iso | 24h |
| include_seconds | No | Include seconds in output |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| format | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states that random times are generated, with no insight into side effects, idempotency, or permissions. For a random generator, behavior is predictable but the description does not explicitly confirm read-only or non-destructive nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words. However, it is very brief and could be restructured to include key usage context while remaining concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has three optional parameters and an output schema, the description is too sparse. It does not clarify what time range is covered (e.g., 00:00:00 to 23:59:59), or how the output relates to the format. The output schema exists but is not shown; the description should provide enough context for the agent to understand the tool's behavior holistically.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents all three parameters (count, format, include_seconds) with descriptions. The tool description adds no additional meaning or context beyond what is in the schema, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate random time(s) of day' clearly states the action (generate) and resource (random time(s) of day). It is specific and distinguishes from siblings like 'current_time' (current time) and other random generators that do not produce times (e.g., random_date produces dates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'random_date' for datetimes, 'current_time' for the current time, or other random generators. There are no when-to-use or when-not-to-use indications, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_triviaBInspect
Get a random trivia fact.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| fact | Yes | |
| category | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does not disclose any behavioral traits such as whether the fact is sourced from a database, if it is deterministic, or any side effects. This leaves the agent with no insight into the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence that directly states the tool's function. Every word is necessary, and there is no fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and an output schema exists, the description is minimally adequate. However, in the context of many similar random tools, it fails to provide distinguishing context, such as the source or range of trivia facts.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and schema coverage is 100%. The description does not add any semantics beyond the schema, but since there are no parameters, no additional param info is needed. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'random trivia fact', making the purpose immediately understandable. However, it does not differentiate from many sibling tools that also generate random content, such as random_fact (if present) or dad_joke, fortune_cookie, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool over similar random generators, nor does it mention any prerequisites or contextual constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_urlCInspect
Generate random URL(s) using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of URLs to generate |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only reveals that it uses Faker. It does not disclose whether the URLs are valid, deterministic, or safe, nor any rate limits or behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is efficient, though it could be slightly longer to add value without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description does not need to explain return values. However, it lacks context about the nature of generated URLs (e.g., valid domains, format) and does not help differentiate from similar tools, making it minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (count parameter documented), so baseline is 3. The description adds no extra meaning beyond the schema; it simply mentions 'URL(s)' without elaborating on the count parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate random URL(s) using Faker.' clearly states the action (generate) and resource (random URLs). It distinguishes the tool from other random generation siblings like random_email or random_string, though it does not provide details on URL format or structure.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool vs alternatives (e.g., random_email, random_username). There is no mention of use cases, prerequisites, or exclusions, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_usernameBInspect
Generate random username(s) using Faker.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of usernames to generate | |
| locale | No | Locale for username style |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| locale | No | |
| values | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose behavior like locale effect, uniqueness, username format, or return structure. Minimal transparency beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff. Efficient, though it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite schema coverage, the description lacks details about output format (array? string?) and behavioral nuances. Given the tool's simplicity and many siblings, more completeness would help.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters (count, locale) in the schema. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (generate), resource (random username(s)), and method (using Faker). It distinguishes from sibling tools like random_name, random_email, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Siblings include many random generation tools, but the description provides no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_uuidBInspect
Generate random UUID(s).
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of UUIDs to generate | |
| version | No | UUID version (1 or 4) |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | No | |
| value | No | |
| values | No | |
| version | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only repeats the name without adding behavioral traits like parameter effects or side effects. With no annotations, the description should clarify behavior, but it remains minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and has an output schema, the description lacks context about version support, count limits, or how it differs from similar UUID tools, making it somewhat incomplete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no semantic value beyond what the schema already provides for 'count' and 'version'.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and resource 'random UUID(s)', making the purpose obvious. However, it does not differentiate from sibling tools like 'generate_uuid' or 'generate_uuids' which likely have similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs. alternative random generation tools or other UUID tools. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
random_weighted_choiceBInspect
Pick random item(s) with weighted probabilities.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of choices to make | |
| items | Yes | Comma-separated items (e.g., 'red,green,blue') | |
| weights | Yes | Comma-separated weights (e.g., '50,30,20') |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations present. The description mentions weighted probabilities but omits critical behavior: whether selection is with or without replacement (important when count > 1), whether weights are normalized, and error handling for mismatched items/weights arrays.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, very concise. Could be expanded with key behavioral details without losing conciseness, but current form is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema and missing behavioral details (e.g., replacement, normalization) leave the description incomplete for a weighted random tool with multiple parameters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all parameters. The description adds no extra meaning beyond what the schema provides, meeting the baseline but not exceeding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the purpose: picking random items with weighted probabilities, which distinguishes it from uniform random selection tools like random_choice or random_element.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use for weighted selection but does not provide explicit guidance on when to use this tool versus alternatives (e.g., random_choice for uniform picks). No 'when not to use' or alternative tools mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
range_to_cidrAInspect
Convert an IP range to CIDR notation.
| Name | Required | Description | Default |
|---|---|---|---|
| end_ip | Yes | End IP address | |
| start_ip | Yes | Start IP address |
Output Schema
| Name | Required | Description |
|---|---|---|
| cidrs | No | |
| error | No | |
| end_ip | No | |
| start_ip | No | |
| total_addresses | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states the conversion action, which is transparent and non-destructive. No side effects or prerequisites are missing for this simple transformation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the essential information. No unnecessary words or details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and the existence of an output schema, the description is mostly adequate. However, it lacks information on input validation or edge cases (e.g., invalid IPs or non-CIDR-compliant ranges), which could be helpful for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both start_ip and end_ip having descriptions in the schema. The description adds no additional parameter details beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert an IP range to CIDR notation' clearly states the verb (convert) and resource (IP range to CIDR). It distinguishes from sibling tools like cidr_info, cidr_to_netmask, and expand_cidr, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for converting an IP range to CIDR notation but does not provide explicit guidance on when to use this tool vs alternatives (e.g., cidr_info for a single CIDR block). No when-not or alternative information is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rank_numbersBInspect
Rank a list of numbers from largest to smallest (or vice versa).
| Name | Required | Description | Default |
|---|---|---|---|
| order | No | Order: 'asc' (smallest first) or 'desc' (largest first) | desc |
| numbers | Yes | Comma-separated numbers to rank |
Output Schema
| Name | Required | Description |
|---|---|---|
| order | Yes | |
| range | Yes | |
| ranked | Yes | |
| largest | Yes | |
| numbers | Yes | |
| smallest | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present. The description does not disclose behavior such as how ties are resolved, whether it returns a new list or modifies input, or the structure of the output. The output schema exists but is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no unnecessary words. It is front-loaded effectively but could benefit from a slightly more structured format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with only 2 parameters and an existing output schema, the description is minimally complete. However, it lacks details on output format, edge cases (ties), and usage guidance, which would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters clearly. The description adds minimal value beyond paraphrasing the order parameter's default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool ranks a list of numbers with an optional order direction. The verb 'rank' and resource 'list of numbers' are specific, and the tool is distinguishable from siblings like 'sort_items' which sorts generic items.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like 'sort_items' or other list operations. There is no mention of when not to use it or comparison to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
readability_scoreBInspect
Calculate readability scores (Flesch-Kincaid, etc.).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to analyze |
Output Schema
| Name | Required | Description |
|---|---|---|
| difficulty | Yes | Human-readable difficulty label: Very Easy, Easy, Moderate, Difficult, or Very Difficult |
| word_count | Yes | Total number of words |
| text_length | Yes | Total character count of the input text |
| sentence_count | Yes | Total number of sentences |
| syllable_count | Yes | Total number of syllables |
| flesch_reading_ease | Yes | Flesch Reading Ease score (0-100, higher = easier) |
| flesch_kincaid_grade | Yes | Flesch-Kincaid grade level (US school grade) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description bears full responsibility for behavioral context. It only states the calculation action, with no mention of side effects, authorization needs, rate limits, or limitations. The behavior is implied but not explicitly disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence. It is appropriately concise but omits potentially helpful details like the specific formulas included or output format expectations. Remains focused.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (not shown) which reduces the need to describe returns, but the description does not clarify which readability scores are computed beyond 'Flesch-Kincaid, etc.' The existence of multiple possible scores is implied but vague. Could be more precise.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with a basic description ('Text to analyze'). The description adds no additional semantic value beyond the schema, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates readability scores and specifically mentions 'Flesch-Kincaid, etc.', making the purpose obvious. The name 'readability_score' further reinforces this. Among many sibling text analysis tools, it stands out uniquely as readability metrics.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like basic_sentiment or text_similarity. The description does not provide context, prerequisites, or exclusions, leaving the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
regex_replaceCInspect
Replace pattern matches in text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to process | |
| flags | No | Flags: i=ignore case, m=multiline, s=dotall | |
| pattern | Yes | Regular expression pattern | |
| replacement | Yes | Replacement string |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| result | No | |
| pattern | Yes | |
| original | No | |
| replacement | No | |
| valid_pattern | No | |
| replacements_made | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description should disclose behavior. It only says 'replace' without specifying scope (global vs single), flag effects, or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but lacks structure; it is minimally adequate but not efficiently front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large number of sibling tools and the existence of an output schema, the description is too minimal, omitting details about output, flag semantics, and replacement behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Replace pattern matches in text' clearly states the verb and resource, but it does not differentiate from siblings like 'replace', 'regex_split', or 'test_pattern', which perform similar operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, no context or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
regex_splitCInspect
Split text by regex pattern.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to split | |
| pattern | Yes | Regular expression pattern to split on | |
| max_split | No | Maximum splits (0=unlimited) |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | No | |
| count | No | |
| error | No | |
| parts | No | |
| pattern | Yes | |
| valid_pattern | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only states 'Split text by regex pattern' without mentioning what happens on invalid patterns, how max_split works (0=unlimited is in schema but not described), or error handling. The output format is not described, though an output schema exists (not shown).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It conveys the core purpose but could be expanded with minimal detail about the behavior or parameters.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple split operation, the description is minimally adequate. However, given the existence of output schema and the need to differentiate from siblings, it is incomplete. It does not mention edge cases or the return format (array of strings).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and each parameter already has a clear description. The tool description adds no extra meaning beyond what the schema provides, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Split text by regex pattern' clearly states the action and resource. The name 'regex_split' further reinforces the method, distinguishing it from a generic 'split' sibling. However, it does not explicitly differentiate from similar tools like 'split' or 'find_all_matches'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'split' (string delimiter) or 'find_all_matches' (extract matches). The description does not mention prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
relative_timeCInspect
Get relative time description (e.g., '2 days ago').
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Date (ISO format) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| date | No | |
| error | No | |
| is_past | No | |
| relative | No | |
| seconds_diff | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden of behavioral disclosure. It does not mention behavior for future dates, invalid dates, timezone handling, or error states. The simple description leaves the agent to infer behavior from the example and schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at 12 words, providing the key purpose and an example. It front-loads the core idea. However, it could be slightly more structured, but for a simple tool this is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and a single parameter, the description is mostly adequate. However, it lacks notes on edge cases (e.g., future dates, invalid input) and how the tool fits into the broader set of utilities. It meets the minimum viable standard.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the one parameter, describing it as 'Date (ISO format)'. The description adds no additional meaning beyond the schema; the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it returns a relative time description like '2 days ago', specifying the verb and resource. However, it does not explicitly distinguish from sibling 'format_relative_time', which could also produce similar output. The example provides clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'format_relative_time' or other time-related utilities. There is no mention of context, prerequisites, or exclusions. This is a significant gap for a tool with many siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remove_duplicate_wordsBInspect
Remove consecutive duplicate words.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text with potential duplicate words |
Output Schema
| Name | Required | Description |
|---|---|---|
| cleaned | Yes | Text with consecutive duplicate words removed |
| original | Yes | Original input text |
| duplicates_removed | Yes | Number of duplicate words removed |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description fails to disclose behavioral traits such as handling of punctuation, case sensitivity, or non-word characters. For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded and concise, but it could be slightly more precise about what constitutes a 'consecutive duplicate word.'
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description is adequate but lacks details on edge cases or return format. It is minimally viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter described as 'Text with potential duplicate words.' The tool description adds no further meaning beyond the schema, so it meets the baseline for full coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Remove' and resource 'consecutive duplicate words,' making it distinct from sibling tools like remove_whitespace or other text manipulation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., remove_whitespace). The description provides no context about when not to use it or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remove_query_paramBInspect
Remove a query parameter from a URL.
| Name | Required | Description | Default |
|---|---|---|---|
| key | Yes | Parameter key to remove | |
| url | Yes | URL to modify |
Output Schema
| Name | Required | Description |
|---|---|---|
| modified | Yes | |
| original | Yes | |
| removed_param | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose behavior such as what happens if the key is not found, or if the URL is modified in place or returned as a new string. Lacks details on side effects or return value nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise single sentence with no unnecessary words. Perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple tool with two parameters and an output schema presumably documenting the return type, the description is mostly complete. However, it lacks edge-case behavior (e.g., missing key).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described. The description adds no extra meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Remove a query parameter from a URL' clearly states the action (remove) and the resource (query parameter from a URL). It directly distinguishes from sibling tools like add_query_param.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as add_query_param or parse_url. No context about typical use cases or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
remove_whitespaceBInspect
Remove all whitespace from text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to process |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states 'remove all whitespace'. It does not disclose handling of edge cases (e.g., empty string, newlines, tabs) or performance characteristics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and has an output schema, the description does not clarify what constitutes 'whitespace' (e.g., spaces, tabs, newlines). Slightly ambiguous given related sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes the parameter as 'The text to process'. The description adds no additional meaning beyond that, meeting the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'remove all whitespace' and the resource 'text'. It is specific and distinguishes from sibling tools like 'normalize_whitespace' or 'trim'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs. alternatives. There is no mention of when not to use it or what distinguishes it from related tools like 'normalize_whitespace' or 'replace'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
repeatCInspect
Repeat text a specified number of times.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to repeat | |
| times | Yes | Number of repetitions | |
| separator | No | Separator between repetitions |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| repeated | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states 'repeat text' without detailing that the output is a single concatenated string, that the 'times' parameter has a maximum of 1000 (though schema covers min/max), or that the separator joins repetitions. The description adds minimal behavioral context beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and to the point. For a simple tool with well-documented schema, this level of conciseness is appropriate. However, it could be slightly longer to include behavioral notes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (mentioned in context) and full parameter descriptions, the description is minimally sufficient. However, it does not elaborate on the return value format (e.g., concatenated string) or edge cases like empty text, which could be important for an AI agent. It achieves adequacy but not completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all three parameters (text, times, separator). The tool description 'Repeat text a specified number of times.' adds no new meaning beyond what the schema already provides. Baseline score of 3 is appropriate since schema already does the job.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Repeat text a specified number of times.' clearly indicates the tool repeats a text string. It distinguishes itself from sibling tools like 'array_repeat' by specifying 'text' rather than arrays. However, it does not explicitly differentiate from other text manipulation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. It does not mention that for repeating text with separators or that 'array_repeat' is for arrays. The description lacks any context about appropriate usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
replaceCInspect
Replace occurrences in text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The original text | |
| search | Yes | Text to search for | |
| replacement | No | Replacement text |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes | |
| original | Yes | |
| occurrences_replaced | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose whether replacements are global or single, case-sensitive, or if the empty replacement deletes matches. With no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (one sentence), which is concise but misses essential details. It is appropriately sized for a simple tool but could be more informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description fails to specify key behavioral aspects (e.g., all vs. first occurrence, case sensitivity). This makes it incomplete for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for all three parameters, so the baseline is 3. The description adds no additional meaning beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Replace' and resource 'occurrences in text', indicating a text substitution operation. However, it does not differentiate from siblings like regex_replace, which also performs replacements.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as regex_replace or other text manipulation tools. The description lacks context for appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
return_on_investmentBInspect
Calculate Return on Investment (ROI).
| Name | Required | Description | Default |
|---|---|---|---|
| cost | Yes | Cost of investment | |
| gain | Yes | Gain from investment |
Output Schema
| Name | Required | Description |
|---|---|---|
| cost | Yes | |
| gain | Yes | |
| net_profit | Yes | |
| roi_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits. It only states the calculation, without mentioning output format, edge cases, or restrictions. The burden falls entirely on the description, which is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no unnecessary words. It is appropriately concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool with an output schema, the description is minimally adequate. However, it lacks completeness in terms of usage context and behavioral details, especially given the lack of annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no new meaning beyond the existing parameter descriptions ('Cost of investment', 'Gain from investment'). The description does not enhance understanding beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate Return on Investment (ROI)' clearly states the verb and resource, making the tool's purpose clear. However, among a large set of financial sibling tools (e.g., simple_interest, future_value), it does not differentiate itself beyond the name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'simple_interest' or 'compound_interest'. The description gives no context for choosing this tool over similar financial calculation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
reverse_numberBInspect
Reverse the digits of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to reverse |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| reversed | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No behavioral details beyond the basic purpose. Does not disclose behavior for edge cases like negative numbers or trailing zeros. Annotations are absent, so description carries full burden but fails to provide transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no wasted words. Highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 1 parameter and implied output (reversed integer), description suffices but lacks detail on return type and edge cases. Output schema exists but is not provided in the definition.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter description 'Number to reverse'. Description adds no extra meaning beyond schema, which is acceptable given high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action (reverse) and the target (digits of a number). It distinguishes from sibling reverse_string and other number-related tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention handling of negative numbers, leading zeros, or integer limits.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
reverse_stringAInspect
Reverse a string.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to reverse |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| reversed | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It minimally discloses behavior (reversing a string) but omits potential edge cases or side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, immediately clear, no wasted words. Front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool and 100% schema coverage (plus an output schema), the description is complete for an agent to understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter fully described). The description adds no extra meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Reverse a string.' clearly states the action and resource, distinguishing it from siblings like 'reverse_number' which operate on numbers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., uppercase, lowercase). The description offers no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rgb_to_hexAInspect
Convert RGB to hex color.
| Name | Required | Description | Default |
|---|---|---|---|
| b | Yes | Blue (0-255) | |
| g | Yes | Green (0-255) | |
| r | Yes | Red (0-255) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| rgb | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It states a simple conversion with no side effects, which is sufficient for this straightforward tool. However, it does not explicitly mention deterministic behavior or edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with zero waste. Front-loaded and appropriate for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description is complete enough. No further context is necessary for an AI agent to understand and use this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with min/max and descriptions for all parameters. The description adds no extra meaning beyond what the schema already provides. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts RGB to hex color (specific verb+resource). However, there are many color conversion siblings (hex_to_rgb, etc.) and no differentiation from them, so it doesn't fully distinguish.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like hex_to_rgb or other color converters. The description provides no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rgb_to_hslAInspect
Convert RGB to HSL color.
| Name | Required | Description | Default |
|---|---|---|---|
| b | Yes | Blue (0-255) | |
| g | Yes | Green (0-255) | |
| r | Yes | Red (0-255) |
Output Schema
| Name | Required | Description |
|---|---|---|
| hsl | Yes | |
| rgb | Yes | |
| hsl_string | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description must convey behavior. It states a pure conversion, implying no side effects, but does not explicitly confirm safety or lack of destructive behavior. For a simple conversion, this is adequate but not exceptional.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no redundant words. The description earns its place by clearly stating the tool's purpose with maximum efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with a fully documented input schema and an output schema present, the description is complete. It covers the essential information without requiring additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already explains each parameter. The description adds no extra meaning beyond 'Convert RGB to HSL color', meeting the baseline for parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert RGB to HSL color' uses a specific verb and resource, clearly stating the conversion direction. It distinguishes well from sibling tools like hex_to_hsl or rgb_to_hex, which convert different color models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives (e.g., hex_to_hsl). The description does not provide context, exclusions, or comparisons to sibling tools, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
roll_diceDInspect
Roll dice.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of dice to roll | |
| sides | No | Number of sides |
Output Schema
| Name | Required | Description |
|---|---|---|
| sum | Yes | |
| count | Yes | |
| rolls | Yes | |
| sides | Yes | |
| average | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description provides no behavioral details beyond the name. It does not disclose that the tool uses random generation, what values are returned, or any safety considerations. Annotations are absent, so the description carries full burden but fails to inform.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief but at the cost of missing critical information. It is not appropriately sized for a tool with parameters and expected output; it is under-specified rather than concisely informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having a complementary output schema, the description fails to explain the return value structure or any behavioral aspects. Given the tool's simplicity, a minimal description would still need to state that it returns a random dice roll result.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions for count and sides. The description adds no extra meaning beyond what the schema already provides, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Roll dice' states a verb and resource, but is overly generic. It does not distinguish from sibling tools like random_dice or random_integer, lacking specificity on what the tool returns or its scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. There is no indication of when to use this tool versus alternatives such as random_dice or other randomization tools, nor any exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
roman_to_numberBInspect
Convert Roman numerals to a number.
| Name | Required | Description | Default |
|---|---|---|---|
| roman | Yes | Roman numeral to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| roman | Yes | |
| number | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral details such as case sensitivity, handling of invalid Roman numerals, supported range, or output format. With no annotations, this gap leaves the agent uncertain about edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, understandable sentence. While very brief, it is appropriately concise for a simple conversion tool, though it could include more detail without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (though not shown), the description provides minimal but contextually adequate information. It does not explain output format or error handling.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a description for the only parameter, achieving 100% coverage. The description adds no additional meaning beyond the schema's own documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Convert' and the specific conversion from Roman numerals to a number. It is distinct from sibling tools like 'number_to_roman' which does the opposite.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'number_to_roman'. It lacks context on prerequisites, input validation, or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rot13BInspect
Apply ROT13 cipher (encoding and decoding are the same operation).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to ROT13 encode/decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| rot13 | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the symmetric behavior (encoding=decoding), which is a key trait. However, it omits other behavioral details like case preservation, character range, or that it only affects letters. No annotations are provided to compensate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single focused sentence with no unnecessary words. It conveys the essential point efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema (presumably returning a string), the description is sufficient. It covers the symmetric operation, which is the main behavioral nuance. No major gaps given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'text' described as 'Text to ROT13 encode/decode'. The description adds no additional semantics beyond what the schema already provides, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool applies ROT13 cipher and notes that encoding and decoding are the same operation. It effectively distinguishes from siblings like base64_encode or various hash functions that are not symmetric.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., for simple obfuscation vs. secure hashing). The description does not mention when not to use it or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
round_numberBInspect
Round a number to specified decimal places.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number to round | |
| decimals | No | Number of decimal places |
Output Schema
| Name | Required | Description |
|---|---|---|
| floor | Yes | |
| number | Yes | |
| ceiling | Yes | |
| rounded | Yes | |
| decimals | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure, but it only states the basic operation without specifying the rounding method (e.g., half-up, half-even) or handling of edge cases like negative numbers or precision limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is concise and front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and presence of an output schema, the description is minimally adequate. However, it does not clarify the rounding method, which could lead to different results depending on expectations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds no additional meaning beyond what the schema provides, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'round' and resource 'number', specifying 'to specified decimal places', which distinguishes it from integer-only operations. However, it does not explicitly differentiate from siblings like floor, ceil, or truncate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as floor, ceil, or truncate. The description lacks any 'when-not-to-use' or context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rule_of_72AInspect
Calculate time to double investment using Rule of 72.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual interest rate (percentage) |
Output Schema
| Name | Required | Description |
|---|---|---|
| rate_percent | Yes | |
| years_to_double_exact | Yes | |
| years_to_double_approx | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the use of 'Rule of 72', which implies an approximation method. While it does not explicitly state limitations or assumptions, the mention of the rule itself provides essential context about the behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the verb. No waste; every word earns its place. Ideal for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description is sufficient. It explains the purpose and method, and the output schema will handle return value documentation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description does not add meaning beyond the schema; it only repeats the function name. No additional context is given about the parameter format or typical values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate time to double investment using Rule of 72.' It specifies the verb (calculate), the resource (time to double investment), and the method (Rule of 72), distinguishing it from sibling tools like compound_interest or future_value.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks explicit guidance on when to use this tool versus alternatives. It does not mention that the Rule of 72 is an approximation or that for precise calculations one should use compound_interest. No when-not or alternative suggestions are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
saturate_colorBInspect
Increase color saturation by a percentage.
| Name | Required | Description | Default |
|---|---|---|---|
| amount | No | Amount to saturate (0-100) | |
| hex_color | Yes | Hex color to saturate |
Output Schema
| Name | Required | Description |
|---|---|---|
| amount | Yes | |
| darkened | No | |
| original | Yes | |
| lightened | No | |
| saturated | No | |
| desaturated | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description fails to disclose behavioral traits such as whether the operation is reversible, if there are limits on saturation increase, or what the output format is. The minimal description leaves the agent guessing about edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one sentence) and front-loaded. However, it is so brief that it may be under-specified, but it earns points for efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, a complete description is less critical. Still, the description could mention that the output is a hex color or that the original input is modified. It is adequate but not thorough.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds 'by a percentage' which aligns with the amount parameter's description, but does not provide additional meaning beyond what the schema already indicates (e.g., amount range, default).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'increase color saturation' and the resource 'color'. It distinguishes from sibling tools like darken_color, desaturate_color, etc., by specifying the operation and the parameter 'by a percentage'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs alternatives (e.g., desaturate_color). The description does not mention any context or preconditions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
seconds_to_hmsBInspect
Convert seconds to hours:minutes:seconds.
| Name | Required | Description | Default |
|---|---|---|---|
| seconds | Yes | Time in seconds |
Output Schema
| Name | Required | Description |
|---|---|---|
| hours | Yes | |
| minutes | Yes | |
| seconds | Yes | |
| formatted | Yes | |
| total_seconds | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention edge cases (e.g., negative seconds, large values) or output format specifics (e.g., zero-padding, what happens with zero seconds). The description is too brief to fully inform the agent of expected behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no fluff. Every word is necessary and contributes to understanding. It is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with 100% schema description and an output schema (presumably documenting return format), the description is mostly adequate. It could mention output format details like zero-padding, but overall it is sufficiently complete for an agent to use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage (one parameter described as 'Time in seconds'), and the description adds no additional semantic detail. Per the rule, with high schema coverage, a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'seconds to hours:minutes:seconds', making the tool's purpose unambiguous. It distinguishes itself from sibling time conversion tools like hours_to_minutes or format_duration by specifying the exact output format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. For example, it does not mention that this tool is for converting seconds to a colon-separated H:M:S string, whereas format_duration might produce a more human-readable string. No when-to-use or when-not-to-use information is included.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sentence_caseCInspect
Convert text to sentence case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to sentence case |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| sentence_case | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It merely restates purpose without revealing edge case handling (e.g., punctuation, existing capitals) or side effects. The description adds minimal behavioral context beyond the name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no extraneous words. It efficiently conveys the core purpose, appropriate for a simple transformation tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, straightforward transformation) and presence of an output schema (assumed to document return format), the description is minimally adequate. However, it lacks details on sentence detection logic, which could be ambiguous among multiple sibling case tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema defines the sole parameter 'text' with a description. The tool description adds no additional meaning beyond what the schema already provides, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states converting text to sentence case with a specific verb and resource. However, there is no differentiation from numerous sibling case conversion tools like camel_case, kebab_case, title_case, etc. Without distinctiveness, it stops short of a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives like title_case or to_sentence_case. No mention of prerequisites, context, or exclusions, leaving the agent to guess among many similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sha1_checksumBInspect
Generate SHA1 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| sha1 | Yes | |
| text | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral details such as output format (e.g., hex string, case) or performance characteristics. The minimal statement lacks transparency beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no redundant words. It conveys the core purpose without extraneous content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no nested objects, output schema exists), the description is reasonably complete. It does not explain the output format, but the presence of an output schema likely covers that. Still, adding a note about the 40-character hex result would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'text' described as 'Text to hash'. The description adds no additional meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb 'Generate' and resource 'SHA1 checksum', distinguishing it as a hash tool. However, it does not differentiate from similar sibling tools like 'hash_sha1', which likely perform the same function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternative hash tools. No context provided about appropriate scenarios or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sha256_checksumCInspect
Generate SHA256 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| sha256 | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It only states the basic function without disclosing behavioral traits like input encoding, output format, or deterministic nature. The presence of an output schema is noted but not described here.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise but under-specified. While short, it lacks key details, making it less useful than a slightly longer but more informative description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 1 parameter and an output schema, the description is minimal. It does not help the agent distinguish from many similar hash siblings, and lacks behavioral context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter. The description adds no extra meaning beyond the schema's 'Text to hash', but baseline is 3 due to high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Generate SHA256 checksum' and the resource. It is specific and unambiguous, but does not differentiate from sibling tools like 'hash_sha256' which likely performs the same operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternative hash tools in the sibling list. No mention of when-not-to-use or context-specific conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sha512_checksumBInspect
Generate SHA512 checksum.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to hash |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| sha512 | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must bear full weight. It only states the action without revealing behaviors like output format (hex string), determinism, or handling of empty input. The output schema exists but the description does not mention it.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no wasted words. While it lacks structure like bullet points, it is appropriately concise for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and complete parameter documentation, the description is minimally complete. However, for a tool in a large family of hash functions, additional context (e.g., 'returns hex string') would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a clear parameter description ('Text to hash'). The tool description adds no extra meaning, but the schema already suffices, earning a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate SHA512 checksum' clearly states the action (generate) and the resource (SHA512 checksum), which distinguishes it from sibling hash tools like md5_checksum or sha256_checksum.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use SHA-512 versus other hash algorithms, nor any context about security or performance. The description is purely declarative without usage scenarios or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
shuffle_listBInspect
Shuffle a list of items.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items to shuffle |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| shuffled | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description does not disclose whether the shuffle is random, deterministic, or any side effects. Leaves important behavioral aspects unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with no unnecessary words. It is front-loaded and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the core function is described. However, missing details about randomness and usage in context of sibling tools limit completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the description adds no extra meaning beyond the schema's parameter description. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool shuffles a list of items, with a specific verb and resource. It is clear but does not differentiate from sibling tools like random_shuffle, which may also shuffle arrays.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as random_shuffle or array_reverse. No prerequisites or context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
signAInspect
Get the sign of a number (-1, 0, or 1).
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| sign | Yes | |
| number | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It clearly discloses return values (-1, 0, 1), which is sufficient for this simple mathematical tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with front-loaded verb and resource. No wasted words, perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter and an output schema, the description is complete. It explains purpose and output, adequate for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a description for the parameter. The tool description adds context about output values but does not enhance parameter meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'sign of a number', listing possible outcomes (-1, 0, 1). This distinguishes it from sibling tools like absolute_value or compare.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for sign determination but lacks explicit guidance on when to use this tool vs alternatives, such as absolute_value or is_positive.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
simple_interestCInspect
Calculate simple interest.
| Name | Required | Description | Default |
|---|---|---|---|
| rate | Yes | Annual interest rate (percentage) | |
| time | Yes | Time in years | |
| principal | Yes | Initial principal |
Output Schema
| Name | Required | Description |
|---|---|---|
| interest | Yes | |
| principal | Yes | |
| time_years | Yes | |
| final_amount | Yes | |
| rate_percent | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks details on behavioral traits such as whether the result is interest amount or total, handling of edge cases, or any side effects. No annotations are provided to compensate, so the description is insufficient for complete behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence, concise and front-loaded. It is minimal but not wasteful, though it could be more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, high schema coverage, and existence of an output schema, the description is minimally sufficient. However, it could be improved by mentioning output format or linking to related tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the input schema has 100% coverage, the description adds no meaning beyond the schema's field descriptions. It does not explain relationships between parameters or clarify units beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates simple interest, which is a specific verb and resource. It implicitly distinguishes from sibling tools like 'compound_interest' by the different term, but does not explicitly differentiate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. The description does not indicate when to use this tool versus financial alternatives like 'compound_interest', 'future_value', or 'loan_payment'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sinCInspect
Calculate the sine of an angle.
| Name | Required | Description | Default |
|---|---|---|---|
| angle | Yes | Angle in radians |
Output Schema
| Name | Required | Description |
|---|---|---|
| sin | Yes | |
| angle_radians | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does not disclose that the angle must be in radians (though the schema states this), nor does it describe the output range or precision. For a simple math function, this is insufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no unnecessary words. It is appropriately sized for a straightforward mathematical function, though it could be more informative without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, output schema exists), the description is minimally adequate. However, it lacks contextual details like output interpretation or common edge cases, which could be beneficial for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter 'angle' already has the description 'Angle in radians'. The tool description adds no further meaning beyond what the schema provides, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Calculate the sine of an angle' uses a specific verb ('calculate') and resource ('sine of an angle'), clearly stating the tool's function. It effectively distinguishes from siblings like cos or tan through the distinct operation name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like cos or tan. The description does not mention input prerequisites or preferred use cases, leaving the agent to infer from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sleep_cyclesCInspect
Calculate optimal sleep/wake times based on 90-minute sleep cycles.
| Name | Required | Description | Default |
|---|---|---|---|
| wake_time | No | Desired wake time (HH:MM) | |
| sleep_time | No | Desired sleep time (HH:MM) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| wake_time | No | |
| sleep_time | No | |
| fall_asleep_time | No | |
| recommended_bed_times | No | |
| recommended_wake_times | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description merely states the output is 'optimal' times without explaining the algorithm (e.g., number of cycles considered, assumption about sleep onset latency). With no annotations, the description fails to disclose behavioral traits like destructive potential or rate limits, leaving the agent to guess.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence of 9 words, extremely concise with no filler. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not mention return values (e.g., list of recommended times). The tool's logic (e.g., whether both parameters can be provided together) is unclear, making it incomplete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions for both parameters (wake_time and sleep_time). The description does not add extra meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it calculates optimal sleep/wake times based on 90-minute cycles, which clearly identifies the tool's function. However, it does not differentiate from sibling tools like time_since_sleep (not present) or other time calculators, though no direct sibling competes for sleep cycle calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, how to choose between providing wake_time or sleep_time, or what happens if both or neither are provided. The user is left to infer usage from the schema.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slugBInspect
Convert text to URL-friendly slug.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to slugify |
Output Schema
| Name | Required | Description |
|---|---|---|
| slug | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavioral traits such as handling of special characters, case normalization, or character limits. The description is too minimal to inform agent behavior beyond the obvious conversion.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no wasted words. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema. The description, while brief, is largely sufficient given the low complexity. However, additional context about character handling would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents the parameter. The description adds the phrase 'URL-friendly slug', which implies the output format but does not add significant new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (convert) and resource (text to URL-friendly slug). However, it does not distinguish from the sibling tool 'slugify', which appears to have the same purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'slugify' or other text transformation tools. No exclusions or context provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
slugifyBInspect
Convert text to URL-friendly slug.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert to slug | |
| lowercase | No | Convert to lowercase | |
| separator | No | Word separator | - |
| max_length | No | Maximum slug length |
Output Schema
| Name | Required | Description |
|---|---|---|
| slug | Yes | |
| length | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only states the general purpose without explaining details like how special characters are handled, truncation behavior, or the effect of parameters. However, the input schema's parameter descriptions (lowercase, separator, max_length) partially compensate, so the description adds minimal value beyond the schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the core purpose. It is efficient but might be too terse given the complexity of the tool (4 customizable parameters). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 4 parameters and an output schema, the description does not mention the output format, the fact that it can be customized via parameters, or provide examples. It is insufficient for an agent to fully understand the tool's capabilities without inspecting the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning for parameters beyond what is already in the schema (e.g., 'text' is described as 'Text to convert to slug' in schema but not elaborated here).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert text to URL-friendly slug' clearly states the verb (convert) and resource (text to URL-friendly slug). It is specific and distinct from many siblings like case converters, but there is a sibling named 'slug' which could be similar, and the description does not differentiate from it. Still, it is clear enough for an agent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'slug', 'kebab_case', or 'deslugify'. There is no mention of prerequisites, when not to use it, or comparison to related tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
smart_title_caseBInspect
Smart title case (handles articles, prepositions).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | Original input text |
| title_case | Yes | Text converted to smart title case (articles/prepositions lowercased) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions handling articles and prepositions but does not specify which words are affected or the exact capitalization rules. Lacks detail on what the transformation entails beyond basic title case.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the core functionality without unnecessary words. It is well-structured for quick understanding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, and the description covers the basic purpose. However, given the presence of similar sibling tools (e.g., 'title_case', 'to_title_case'), the description should have differentiated them. The existence of an output schema is noted, but not shown. Overall, adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'text' is described as 'Text to convert', which is clear. The description adds value by noting that the tool handles articles and prepositions, providing semantic context beyond the schema. With 100% schema coverage, baseline is 3, and the extra context justifies a 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts text to title case with special handling for articles and prepositions. However, it does not distinguish itself from sibling tools like 'title_case' or 'to_title_case', which may do similar things.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other case conversion tools. The description does not mention prerequisites, use cases, or scenarios where this tool is preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
snake_caseCInspect
Convert text to snake_case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to convert |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| snake_case | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral traits beyond the basic conversion. It fails to explain what 'snake_case' entails (e.g., lowercase with underscores, handling of special characters) or any side effects. With no annotations, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is one sentence with no redundancy. It is appropriately concise for a simple conversion tool, though could include more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema (implied), the description is minimally adequate. However, it lacks context about the exact output format and how it differs from similar tools, making it incomplete for informed selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% description coverage with 'The text to convert'. The tool description adds minimal value by restating the purpose. Given high coverage, baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'text to snake_case'. It distinguishes the tool's function from generic text manipulation, but there is a sibling tool 'to_snake_case' with a similar purpose, and no differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives like 'to_snake_case' or other case converters. The description does not provide context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sort_itemsDInspect
Sort a list of items.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items to sort | |
| order | No | Sort order (asc or desc) | asc |
| numeric | No | Sort as numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| order | No | |
| sorted | No | |
| original | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and description fails to disclose behavioral traits: input is a comma-separated string, sorting behavior (lexicographic vs numeric), case sensitivity, or output format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise (one sentence) but lacks essential details. Conciseness without substance reduces effectiveness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not explain the comma-separated input format or the behavior of the numeric flag. Insufficient for a tool with 3 parameters and no annotation coverage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all three parameters. Description adds no additional semantic value beyond the schema; baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description is vague; merely restates the name 'sort a list of items' without specifying input format or differentiating from many sibling list tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like shuffle_list, reverse_array, or unique_items. Missing context for choosing sort over other list operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
soundexBInspect
Generate Soundex phonetic encoding.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Word to encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | Input word (uppercased) |
| soundex | Yes | 4-character Soundex phonetic code |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It lacks details on input constraints (e.g., English words only), output format (letter-digit pattern), or edge cases. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no waste. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description lacks context on input restrictions, behavior for non-English text, or return format. Incomplete for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'text' described as 'Word to encode'. The description adds no extra meaning beyond the schema, meeting baseline but not elevating.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate Soundex phonetic encoding' clearly states the verb (generate) and resource (Soundex phonetic encoding). It distinguishes this tool from many sibling encoding/hash tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use Soundex versus other phonetic or encoding tools. The description does not mention alternatives or specific use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
splitCInspect
Split text by delimiter.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to split | |
| delimiter | No | Delimiter to split by | , |
Output Schema
| Name | Required | Description |
|---|---|---|
| count | Yes | |
| parts | Yes | |
| original | Yes | |
| delimiter | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description does not disclose behavior beyond basic splitting (e.g., handling of empty delimiter, whitespace, output format). For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no waste. However, could include more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple and has output schema, so description is adequate but lacks edge-case details. Completeness is sufficient for basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. Description adds no extra meaning beyond schema parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states action 'split' on resource 'text' using 'delimiter'. But does not differentiate from sibling tools like regex_split, which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., regex_split for pattern-based splits). No exclusions or prerequisites provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
split_complementary_colorsBInspect
Get split-complementary colors.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color |
Output Schema
| Name | Required | Description |
|---|---|---|
| triadic | No | |
| original | Yes | |
| tetradic | No | |
| analogous | No | |
| split_complementary | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose what the tool returns (e.g., number of colors, format), leaving behavioral traits unspecified beyond the obvious.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it could be slightly improved without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the many sibling color tools and the presence of an output schema, the description is too minimal to provide sufficient context for an AI agent to understand what split-complementary colors are or how they differ.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter, but the description adds no extra meaning beyond 'Hex color' already in the schema; baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get split-complementary colors' uses a specific verb (Get) and resource (split-complementary colors), clearly distinguishing it from sibling tools like complementary_colors, triadic_colors, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like analogous_colors or tetradic_colors, and no exclusions or context are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
squareBInspect
Calculate the square of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to square |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral burden. It only states the basic purpose without disclosing any traits such as being deterministic, side-effect-free, or handling special cases (e.g., negative numbers).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words. It is front-loaded with the purpose. However, it could be slightly more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the existence of an output schema, the description is minimally adequate. It does not address edge cases or differentiate from numerous sibling tools, but for a basic mathematical operation, it covers the essential purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides a clear description for the parameter 'number' ('Number to square'). With 100% schema coverage, the description adds no additional meaning. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Calculate the square of a number.' The verb 'Calculate' and resource 'square of a number' are specific. Among siblings like 'cube', 'square_root', 'cube_root', it is distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There is no mention of when to prefer 'square' over 'square_root', 'cube', or other mathematical operations. The description provides no context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
square_feet_to_square_metersBInspect
Convert square feet to square meters.
| Name | Required | Description | Default |
|---|---|---|---|
| square_feet | Yes | Area in square feet |
Output Schema
| Name | Required | Description |
|---|---|---|
| square_feet | Yes | |
| square_meters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided; the description does not disclose rounding behavior, precision, error handling, or any edge cases. With a conversion tool, such details are important but omitted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no extraneous information, front-loading the core action. However, it could be slightly expanded to include return format without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema and a simple conversion, the description lacks usage guidelines and behavioral transparency. For a tool with no annotations, it should provide more context to be fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter 'square_feet' is described in the schema as 'Area in square feet'. The description adds no additional meaning beyond the schema, so baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the resource 'square feet to square meters', making the tool's purpose unmistakable. It distinguishes itself from sibling tools like feet_to_meters (linear) and square_meters_to_square_feet (reverse).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as square_meters_to_square_feet or other area conversions. No context on prerequisites or typical use cases provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
square_meters_to_square_feetAInspect
Convert square meters to square feet.
| Name | Required | Description | Default |
|---|---|---|---|
| square_meters | Yes | Area in square meters |
Output Schema
| Name | Required | Description |
|---|---|---|
| square_feet | Yes | |
| square_meters | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility. It only says 'Convert', which implies a safe, pure transformation, but does not disclose any behavioral details like precision, rounding, or that it is a simple multiplication.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, perfectly sized for a straightforward conversion tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity, full schema coverage, and the presence of an output schema, the description is adequately complete. It could mention edge cases or the conversion factor, but it is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool's description adds no additional meaning beyond what the schema already provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert square meters to square feet' clearly states the action (convert) and the specific unit conversion, distinguishing it from sibling tools like square_feet_to_square_meters.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (when converting square meters to square feet) but does not explicitly mention alternatives or when not to use. For a simple conversion, this is adequate but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
square_rootBInspect
Calculate the square root of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | The number |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| square_root | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only states it calculates the square root, without detailing behavior such as precision, error handling, or that it is a read-only operation. Output schema exists but is not described.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. Clearly states the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple mathematical tool, the description is adequate. The output schema exists to explain return values. Could mention that it works only for non-negative numbers, but schema already conveys that via minimum constraint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter 'number' described as 'The number' with a minimum of 0. The description adds no additional meaning beyond the schema. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool calculates the square root of a number. It uses a specific verb and resource, distinguishing it from siblings like 'square', 'cube_root', and 'nth_root'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Does not mention that it is for non-negative numbers (though schema enforces min 0) or compare to similar tools like nth_root.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
start_of_periodAInspect
Get the start of a time period.
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Period: year, month, week, day, hour | day |
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| start | No | |
| period | No | |
| original | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It does not explain what 'start' means (e.g., timezone handling, definition of week start), leaving significant ambiguity for the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence with no waste. It is front-loaded but could benefit from additional details without being overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (date/time periods) and lack of annotations, the description is incomplete. It does not specify output format, behavior for invalid inputs, or edge cases like daylight saving time.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional insight beyond what the schema already provides for both parameters, but it does not detract.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the start of a time period', which is a specific verb and resource. It distinguishes from the sibling tool 'end_of_period', so the purpose is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies that the tool is used when the start of a period is needed. However, it does not explicitly mention when not to use it or list alternatives, such as 'add_time' for shifting dates. The context is clear but lacks exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
starts_withBInspect
Check if text starts with a prefix.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to check | |
| prefix | Yes | The prefix to look for |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| prefix | Yes | |
| starts_with | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It states a simple boolean check but does not disclose any behavioral traits like case sensitivity or whitespace handling. For a straightforward check, this is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, which is efficient. However, it could include more context without being verbose. It is front-loaded but under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the minimal description is sufficient but leaves gaps for an AI agent to understand nuances. It is minimally viable but could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the schema already describes both parameters. The description does not add additional meaning beyond the schema, so the baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check if text starts with a prefix' clearly states the verb 'check' and the resource 'text' with the specific operation 'starts with a prefix'. It effectively distinguishes from sibling tools like 'ends_with' and 'contains'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention case sensitivity, whitespace, or context where this tool is preferred. With many sibling tools, explicit usage notes would help.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
status_code_infoBInspect
Get information about an HTTP status code.
| Name | Required | Description | Default |
|---|---|---|---|
| code | Yes | HTTP status code |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| name | Yes | |
| category | Yes | |
| description | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations; description does not reveal any behavioral traits such as the format or extent of information returned, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise but too terse; could include more detail without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, description need not detail returns, but it still fails to specify what 'information' entails, making the tool somewhat ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with 'HTTP status code' for the code parameter; description adds no further meaning, meeting baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get information about an HTTP status code', which is specific and distinguishes it from siblings like http_method_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No when-to-use guidance or alternatives provided, leaving the agent to infer context from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
stone_to_kilogramsBInspect
Convert stone to kilograms.
| Name | Required | Description | Default |
|---|---|---|---|
| stone | Yes | Weight in stone |
Output Schema
| Name | Required | Description |
|---|---|---|
| stone | Yes | |
| kilograms | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden, but it only states the conversion. It does not disclose any behavioral traits such as accuracy, unit system (UK vs US stone), or whether it is a simple arithmetic transformation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no wasted words, front-loading the essential information immediately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter conversion tool with an output schema, the description is largely sufficient. However, it could be improved by noting that the input is numeric and output is in kilograms.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single parameter, and the description adds no new meaning beyond 'Weight in stone'. Baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert stone to kilograms' clearly identifies the action (convert) and the specific resource (stone to kilograms), distinguishing it from sibling conversion tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus similar conversion tools (e.g., kilograms_to_pounds). The description simply states the function without context or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
string_lengthCInspect
Get the length of a string.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to measure |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| length | Yes | |
| line_count | Yes | |
| word_count | Yes | |
| length_without_spaces | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavioral traits such as whether it counts characters or bytes, or how it handles Unicode. This could lead to incorrect usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise—one sentence—and directly communicates the core purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool and presence of an output schema, the description is minimally adequate. However, it lacks context about potential edge cases (e.g., empty string, Unicode).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'text' described in the schema. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose ('Get the length of a string') with a specific verb and resource. However, it does not differentiate itself from sibling tools like 'word_count' or 'count_char', which could be ambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it doesn't mention that this counts characters (including whitespace) while 'word_count' counts words.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
subnet_calculatorBInspect
Calculate subnets from a network.
| Name | Required | Description | Default |
|---|---|---|---|
| network | Yes | Network in CIDR notation | |
| new_prefix | Yes | New prefix length for subnets |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| subnets | No | |
| truncated | No | |
| new_prefix | No | |
| total_subnets | No | |
| original_prefix | No | |
| hosts_per_subnet | No | |
| original_network | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It only states 'Calculate subnets' without explaining output format, validation, error handling, or side effects (none expected). This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence without extraneous information. It wastes no characters, though it could include more context without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (likely describing the result), the description is somewhat adequate. However, it lacks details on edge cases, invalid inputs, or whether it returns multiple subnets or a single summary. Missing annotations increase the need for more completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear explanations ('Network in CIDR notation', 'New prefix length for subnets'). The tool description adds no additional meaning beyond the schema, so baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates subnets from a network, using a specific verb and resource. It distinguishes itself from sibling tools like cidr_info, expand_cidr, and supernet_calculator, which perform different networking calculations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks context on prerequisites, such as requiring new_prefix > network prefix, or when to choose supernet_calculator instead.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
subnet_mask_infoAInspect
Get subnet mask from prefix length.
| Name | Required | Description | Default |
|---|---|---|---|
| prefix_length | Yes | CIDR prefix length (0-32) |
Output Schema
| Name | Required | Description |
|---|---|---|
| binary | Yes | |
| subnet_mask | Yes | |
| num_addresses | Yes | |
| prefix_length | Yes | |
| wildcard_mask | Yes | |
| num_usable_hosts | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It only states the basic functionality without disclosing error handling, return format, or edge cases. The parameter constraints are already in the schema, so the description adds minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, straightforward sentence with no unnecessary words. It is appropriately sized for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description is complete. It clearly expresses the core functionality, and the parameter is well-documented in the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%. The description does not add any additional meaning beyond what the schema already provides for the 'prefix_length' parameter. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get subnet mask from prefix length' clearly states the tool's action and resource. It distinguishes from siblings like 'cidr_info' and 'netmask_to_cidr' by specifying the conversion direction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like 'netmask_to_cidr' or 'cidr_info'. However, the context of sibling tool names implies the use case, but no explicit guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
subtractAInspect
Subtract b from a.
| Name | Required | Description | Default |
|---|---|---|---|
| a | Yes | First number | |
| b | Yes | Number to subtract |
Output Schema
| Name | Required | Description |
|---|---|---|
| a | Yes | |
| b | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not mention any behavioral traits beyond the basic operation. Since no annotations are present, the description carries the full burden, but for a simple arithmetic function, moderate transparency is acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It is maximally concise for the information it conveys.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is largely complete. However, it could mention the return type or constraints (e.g., numbers only) for full completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds ordering context ('Subtract b from a') beyond the schema's individual parameter descriptions, enhancing understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Subtract b from a' clearly states the operation and the order of operands. It distinguishes subtraction from other arithmetic operators but does not differentiate among sibling tools like 'multiply', 'divide', etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'add', 'multiply', or 'divide'. There is no context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
subtract_timeBInspect
Subtract time from a date.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Start date (ISO format) | |
| days | No | Days to subtract | |
| hours | No | Hours to subtract | |
| weeks | No | Weeks to subtract | |
| minutes | No | Minutes to subtract | |
| seconds | No | Seconds to subtract |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| error | No | |
| result | No | |
| original | No | |
| subtracted | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral details. It only restates the operation; it does not mention edge cases (e.g., invalid date format), return format, or any side effects. The output schema may cover return format, but the description adds no value beyond the tool's name.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple date arithmetic tool with an output schema, the description is minimally adequate. However, it could benefit from mentioning that the date must be in ISO format (though in schema) or the supported units. Sibling tools like 'subtract_time_2' suggest a need for differentiation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so parameters are fully documented in the schema. The description adds no extra meaning beyond what the schema already provides. Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Subtract time from a date.' clearly states the verb and resource. However, it does not differentiate from sibling tools like 'subtract_time_2' or 'add_time', so it scores a 4 instead of 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
subtract_time_2CInspect
Subtract time from a datetime.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Days to subtract | |
| hours | No | Hours to subtract | |
| minutes | No | Minutes to subtract | |
| seconds | No | Seconds to subtract | |
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| result | No | |
| original | No | |
| subtracted | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It only states the action but does not disclose any behavioral traits such as timezone handling, input validation, or output format, which are critical for datetime operations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, but it lacks detail and does not add value beyond the name. It is appropriately short but under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While an output schema exists, the description does not clarify the purpose of this specific tool among closely named siblings (e.g., 'subtract_time'). It fails to provide enough context for an agent to reliably select this tool over others.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so all parameters have individual descriptions. The title and description add no additional meaning beyond what the schema already provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'subtract' and the resource 'time from a datetime,' making the primary action obvious. However, it does not differentiate from sibling tools like 'subtract_time' or 'add_time_2', leaving ambiguity about why this specific tool exists.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. There are no prerequisites, exclusions, or examples of appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
suggest_improvementsCInspect
Suggest improvements for a password.
| Name | Required | Description | Default |
|---|---|---|---|
| password | Yes | Password to improve |
Output Schema
| Name | Required | Description |
|---|---|---|
| suggestions | Yes | |
| current_length | Yes | |
| suggestion_count | Yes | |
| meets_basic_requirements | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully convey behavior. It only says 'suggest improvements' without detailing what improvements are (e.g., character additions, pattern changes) or whether it returns multiple suggestions. This is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short and front-loaded, but it could include more detail without being verbose. It meets minimal conciseness but lacks substance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description is extremely brief and fails to explain what the output represents (e.g., a list of improvement suggestions). For a password tool, more context on the nature of improvements is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'password' is well-described in the schema ('Password to improve'). The description adds no new meaning beyond the schema, and coverage is 100%, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool suggests improvements for a password, which is specific. However, it does not differentiate from sibling tools like analyze_password or validate_password_strength, which might overlap in function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. For example, it does not specify whether to use this for generating passwords or analyzing strength, leaving ambiguity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sum_digitsBInspect
Sum the digits of a number.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to sum digits of |
Output Schema
| Name | Required | Description |
|---|---|---|
| sum | Yes | |
| digits | Yes | |
| number | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It does not address edge cases such as negative numbers or zero, leaving ambiguity. For example, summing digits of -123 might be interpreted differently (1+2+3 vs ignoring sign). The tool's behavior beyond the basic operation is not explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at 5 words and one sentence. Every word is necessary, and there is no filler. It is front-loaded with the core purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema (present but not shown), the description is mostly complete. However, it lacks handling of edge cases like negative numbers, which would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter description in the schema ('Number to sum digits of') is adequate. The tool description does not add extra meaning or clarify formatting, so the default baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Sum the digits of a number' clearly states the verb (sum) and resource (digits of a number). It is specific and distinguishes from sibling tools like 'digital_root' (which sums recursively) and 'count_digits' (which counts digits).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'digital_root'. There is no mention of prerequisites, exclusions, or context that would help an agent decide between similar tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sum_numbersCInspect
Calculate the sum of numbers.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Comma-separated numbers |
Output Schema
| Name | Required | Description |
|---|---|---|
| sum | Yes | |
| numbers | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does not disclose behavior such as error handling for non-numeric input, output format, or any constraints on the number of inputs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence. No wasted words, but it could be more informative without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple sum tool, the description is minimally adequate given that the schema covers the parameter and an output schema likely exists. However, it lacks details on usage context and edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter description is clear. The tool description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates the sum of numbers, indicating the verb and resource. However, it does not differentiate from sibling tools like 'calculate_sum' which likely performs a similar function, and could be more specific about the input format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., 'add' for two numbers, 'calculate_sum' for similar functionality). There is no mention of prerequisites or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
sun_positionBInspect
Calculate approximate sun position (azimuth and elevation).
| Name | Required | Description | Default |
|---|---|---|---|
| day | Yes | Day | |
| lat | Yes | Latitude | |
| lon | Yes | Longitude | |
| hour | No | Hour (24h format) | |
| year | Yes | Year | |
| month | Yes | Month |
Output Schema
| Name | Required | Description |
|---|---|---|
| is_day | Yes | |
| azimuth | Yes | |
| datetime | Yes | |
| location | Yes | |
| elevation | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, description must disclose behavioral traits. It only says 'approximate' but no detail on accuracy, assumptions, or limitations. Does not reveal any potential pitfalls.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, 8 words, front-loaded verb and resource. No filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists so return values need not be explained. However, description lacks context on coordinate system and time handling; it is adequate but minimal.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions, so baseline is 3. Description adds no extra meaning about parameters, but the schema already adequately documents them.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Calculate approximate sun position (azimuth and elevation)', specifying the verb and key outputs. It distinguishes from siblings as no other tool computes sun position.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives or any prerequisites. Description only states what it does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
supernet_calculatorBInspect
Calculate the supernet that contains all given networks.
| Name | Required | Description | Default |
|---|---|---|---|
| networks | Yes | Comma-separated networks in CIDR notation |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| supernets | No | |
| input_networks | No | |
| collapsed_count | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but fails to disclose behavioral traits. It does not specify output format, error handling, or edge cases (e.g., overlapping networks). The one-sentence description is insufficient for a non-trivial network tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant words. It is appropriately sized and front-loaded with the core information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema (not shown), the description lacks completeness. It doesn't explain what the supernet is, what constraints apply, or how it interacts with sibling tools. For a network calculation, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'networks' is described in the schema as 'Comma-separated networks in CIDR notation', and the description adds no extra meaning. Schema coverage is 100%, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to calculate the supernet that contains all given networks. The verb 'calculate' and resource 'supernet' are specific, and it distinguishes from sibling tools like 'subnet_calculator' which operates on subnets.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It does not mention prerequisites, scenarios, or when not to use it. The description implies basic usage but lacks explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
swap_caseAInspect
Swap case of each character.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description accurately states the behavior of toggling each character's case. With no annotations, it adequately conveys the action without hidden side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no unnecessary words, efficiently communicating the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple string operation with one parameter and no output schema, the description is sufficiently complete, though a brief usage hint could enhance it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description does not add meaning beyond the schema-provided parameter description ('Text to convert').
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Swap case of each character' uses a specific verb and resource, clearly distinguishing it from siblings like uppercase, lowercase, and other case conversion tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., uppercase, lowercase) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tanBInspect
Calculate the tangent of an angle.
| Name | Required | Description | Default |
|---|---|---|---|
| angle | Yes | Angle in radians |
Output Schema
| Name | Required | Description |
|---|---|---|
| tan | Yes | |
| angle_radians | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose important behavioral traits, such as handling of undefined values (e.g., angle = π/2 radians) or the range of output. The description is too minimal for a math function with potential edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and concise, but it could be slightly improved by adding a brief note about the expected input format or output. It is not overly wordy, but lacks some context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description is moderately complete. However, it fails to cover behavioral details like undefined inputs, which are relevant for a trigonometric function. The output schema likely provides return value info, so the description adequately covers the basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, as the parameter 'angle' includes a description 'Angle in radians.' The description adds no extra meaning beyond that, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate the tangent of an angle,' which is a specific verb and resource. It is unambiguous and distinguishes from sibling tools like sin, cos, and sqrt.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as sin, cos, or other trigonometric functions. There is no mention of context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
test_patternBInspect
Test if a regex pattern matches text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to test against | |
| flags | No | Flags: i=ignore case, m=multiline, s=dotall | |
| pattern | Yes | Regular expression pattern |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | No | |
| error | No | |
| matches | No | |
| pattern | Yes | |
| match_end | No | |
| match_start | No | |
| matched_text | No | |
| valid_pattern | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but provides minimal behavioral info. It does not state return type, error handling, or flag behavior beyond schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded, no wasted words. Perfectly concise for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple tool with rich schema and output schema. However, missing return value explanation or example usage, which would help given many sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% description coverage, so parameters are already documented. The description adds no additional meaning beyond what the schema provides, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool tests if a regex pattern matches text, with a specific verb and resource. However, it does not explicitly differentiate from sibling tools like 'contains' or 'find_all_matches'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. For example, it does not mention that 'validate_pattern' is for regex syntax validation or 'find_all_matches' for multiple matches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
tetradic_colorsBInspect
Get tetradic colors (four colors forming a rectangle on color wheel).
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color |
Output Schema
| Name | Required | Description |
|---|---|---|
| triadic | No | |
| original | Yes | |
| tetradic | No | |
| analogous | No | |
| split_complementary | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description only states the basic operation without discussing behavior on invalid input, return format, or other traits. Minimal transparency beyond the essential purpose.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, no wasted words, front-loaded with the core action. Highly concise and structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple color tool with output schema, the description is adequate but lacks usage context and parameter clarification. Given sibling similarity, it could be improved.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, but the parameter description 'Hex color' is minimal. The tool description adds no additional meaning or formatting hints, leaving the user with no extra insight.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool gets tetradic colors and explains they form a rectangle on the color wheel. It distinguishes from sibling tools like analogous_colors and triadic_colors.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for tetradic color schemes but provides no explicit when-to-use or alternatives. Given the sibling list, the purpose is implied but not elaborated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
text_similarityBInspect
Calculate similarity between two texts (Jaccard similarity).
| Name | Required | Description | Default |
|---|---|---|---|
| text1 | Yes | First text | |
| text2 | Yes | Second text |
Output Schema
| Name | Required | Description |
|---|---|---|
| text1_words | Yes | Unique word count in text1 |
| text2_words | Yes | Unique word count in text2 |
| common_words | Yes | Number of words shared between both texts |
| jaccard_similarity | Yes | Jaccard similarity coefficient (0-1) |
| similarity_percent | Yes | Similarity as a percentage (0-100) |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose key behaviors like case sensitivity, handling of whitespace/punctuation, output range (e.g., 0-1), and symmetry. The current description only states the algorithm without these details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with verb and resource, no wasted words. Efficient and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-string tool with an output schema, the description is minimally adequate but lacks details about output format (e.g., range) and edge cases like empty strings, so not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with basic descriptions ('First text', 'Second text'), but the tool description adds no semantic nuance beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool calculates similarity between two texts, specifies the algorithm (Jaccard similarity), and the verb+resource combination distinguishes it from sibling tools like levenshtein_distance, compare, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use Jaccard similarity versus alternative similarity measures (e.g., Levenshtein distance, cosine similarity) or any usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
time_differenceBInspect
Calculate difference between two datetimes.
| Name | Required | Description | Default |
|---|---|---|---|
| datetime1 | Yes | First datetime in ISO format | |
| datetime2 | Yes | Second datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| datetime1 | No | |
| datetime2 | No | |
| difference | No | |
| human_readable | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are available, and the description does not disclose behavioral traits such as the format of the returned difference (e.g., seconds, milliseconds) or handling of edge cases (e.g., negative results). The description carries the full burden but fails to provide this information.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is 100% relevant and front-loaded with the core action. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has two simple parameters and an output schema, the description could be more complete by specifying the unit of the difference. However, it is minimally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters are described in the schema with 'ISO format' hints. The description adds no additional meaning beyond what the schema provides. With 100% schema coverage, a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool calculates the difference between two datetimes. It is specific but does not differentiate from siblings like date_diff. However, the purpose is clear.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description is minimal with no exclusions or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
timezone_offsetBInspect
Estimate timezone offset from longitude (approximate).
| Name | Required | Description | Default |
|---|---|---|---|
| lon | Yes | Longitude |
Output Schema
| Name | Required | Description |
|---|---|---|
| lon | Yes | |
| note | Yes | |
| estimated_timezone | Yes | |
| estimated_utc_offset | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description only mentions 'approximate', leaving out behavioral traits like ignoring DST, political boundaries, or accuracy. With no annotations, the description should provide more transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with one sentence. No waste, but could benefit from slightly more detail without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool estimating timezone offset, the description fails to mention output format, caveats, or limitations. Though an output schema exists, it's not shown, and the description alone is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the 'lon' parameter, which already explains it's longitude. The description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool estimates timezone offset from longitude using a specific verb and resource. It distinguishes itself from siblings like convert_timezone which convert between named timezones.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Siblings include many other tools, but no when-not-to-use or context given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
title_caseBInspect
Convert text to title case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to title case |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| title_case | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior, but it only states the basic function. It fails to mention title casing rules (e.g., handling of articles, prepositions, acronyms) or return format, which are important for correct usage. The existence of an output schema does not compensate for this lack of detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no unnecessary words, front-loaded with the core purpose. It is perfectly concise for a simple tool, earning the highest score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a straightforward string transformation, the description covers the basic purpose. However, given the presence of many sibling case tools (including 'to_title_case'), the context is incomplete without differentiation. The output schema exists but the description does not leverage it to explain return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'text' is described in the schema with 'The text to title case', providing full coverage (100%). The tool description adds no additional semantic value beyond what the schema already offers, earning a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (convert) and resource (text to title case), providing a specific verb+resource pair. However, it does not differentiate from the sibling tool 'to_title_case', which likely performs the same function, leading to ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'to_title_case' or other case converters. The description lacks context for appropriate usage, which is critical given the large number of sibling case tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_alternating_caseCInspect
Convert text to aLtErNaTiNg case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert | |
| start_upper | No | Start with uppercase |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It only says 'convert to alternating case' without explaining how non-alphabetic characters are handled, the default starting case (inferred from start_upper defaulting to false), or the overall pattern. The parameter start_upper is not mentioned in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and to the point. It wastes no words, but its brevity leaves out important behavioral details. For a simple tool, the length is acceptable, though better structure (e.g., bullet points) would improve clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large number of sibling case converters, the description is incomplete. It fails to explain the alternating algorithm (e.g., starting case, handling of non-letters) or provide examples beyond the name. With no output schema, the description should fill gaps but does so minimally.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: both parameters (text, start_upper) have descriptions in the input schema. The description does not add any additional meaning beyond the schema, such as clarifying the role of start_upper or format constraints. Baseline 3 is appropriate since schema already documents parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert text to aLtErNaTiNg case' clearly communicates the tool's function: it transforms text into alternating case. The example 'aLtErNaTiNg' illustrates the output pattern, which distinguishes it from sibling tools like to_lower_case, to_upper_case, or swap_case. However, it could be more explicit about the exact alternating pattern (e.g., starting with lowercase or uppercase).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. Given many sibling case converters (e.g., camel_case, kebab_case, snake_case, inverse_case, swap_case), the lack of usage context or when-not-to-use instructions makes it harder for an AI to select the right tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_camel_caseCInspect
Convert text to camelCase.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It lacks details on how it handles special characters, numbers, or Unicode, and does not specify if it preserves acronyms or treats empty input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise (one sentence), but it sacrifices necessary detail. While it is front-loaded, it fails to earn its place by providing adequate information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool, the description is incomplete. It does not define camelCase conventions (e.g., lower camelCase), handle edge cases, or mention the return format. With many similar siblings, more specificity is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter 'text' described as 'Text to convert'. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action and target format ('Convert text to camelCase.'). However, it does not distinguish itself from similar siblings like 'camel_case', 'to_pascal_case', etc., which may cause ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over other case conversion tools (e.g., when to choose 'to_camel_case' vs 'camel_case' or 'to_snake_case'). No context or exclusions provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_constant_caseAInspect
Convert text to CONSTANT_CASE (alias for screaming snake).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states the transformation outcome but does not detail specifics like handling of special characters, digits, or whitespace. For a simple string conversion, this is adequate but not thorough; a 3 reflects its minimal disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words. It is front-loaded with the core action and includes a helpful alias note. Every element earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is minimal but sufficient for the simple one-parameter tool. However, given the large number of sibling case converters, a brief note on the exact format (e.g., 'UPPERCASE_SEPARATED_BY_UNDERSCORES') would improve completeness. No output schema exists, but the return type is implied.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single parameter 'text' with a clear description. The tool description adds no extra semantic value beyond restating the parameter's purpose. Baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the target format 'CONSTANT_CASE', with the added alias clarification 'screaming snake'. This fully specifies the tool's function and distinguishes it from other case converters in the sibling list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over other case converters (e.g., when constant case vs screaming snake case might be preferred). The description lacks any contextual advice or alternatives, which is a significant gap given the many sibling case conversion tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_dot_caseCInspect
Convert text to dot.case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description is minimal and does not disclose behavioral traits. It does not explain how it handles input text (e.g., does it handle punctuation, spaces, mixed case?). Without annotations, the description should provide more context about the conversion process, but it adds no value beyond the literal statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded, and contains no unnecessary words. It is concise and to the point, which is appropriate for a simple conversion tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, and the presence of many sibling tools, the description is incomplete. It does not explain the output format or give enough context for an agent to understand 'dot.case' without prior knowledge. The description is too sparse.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes the single parameter 'text' as 'Text to convert'. The description adds no additional meaning or constraints. The baseline is 3, and the description does not compensate further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert text to dot.case.' clearly states the verb and resource. It indicates the tool converts text to dot.case format. However, it does not explain what dot.case means (e.g., lowercase with dots) nor distinguish it from siblings like to_kebab_case or to_snake_case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling case conversion tools, the description should include hints about when dot.case is appropriate or preferred, but it offers no such context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_header_caseBInspect
Convert text to Header-Case (HTTP header style).
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden but only gives a vague 'HTTP header style' without detailing the exact transformation rules, side effects, or return format.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, front-loaded with the action, no unnecessary words. Highly concise and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one input and no output schema, the description is minimal but leaves ambiguity about the exact definition of 'Header-Case' and lacks return value explanation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter described as 'Text to convert'. The description adds no extra meaning beyond the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Convert text' and specifies the output format as 'Header-Case (HTTP header style)', which distinguishes it from sibling case conversion tools like to_camel_case or to_kebab_case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool over alternatives. The description only states what it does, without any context about selection criteria or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_kebab_caseCInspect
Convert text to kebab-case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure. It fails to explain how the conversion handles edge cases like spaces, special characters, or existing hyphens, which is critical for text transformation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, but it sacrifices informativeness. Important context about the conversion rule is omitted, making it under-specified.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the large number of similar case conversion siblings, the description is insufficient. It does not explain what kebab-case is (e.g., lowercase with hyphens) or note any sanitization behavior, leaving the agent with little guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the parameter description 'Text to convert' is clear. The tool description adds no additional meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts text to kebab-case, using a specific verb and target format. However, it does not distinguish itself from a sibling tool named 'kebab_case', limiting differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., 'kebab_case', 'slugify', or other case converters). The description lacks usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_lower_caseBInspect
Convert text to lowercase.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must convey behavioral traits. It only states the basic transformation without detailing edge cases, character handling, or the return format. This is insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and no output schema. The description is minimally adequate, but lacks details on return value or handling of non-string inputs. Could be improved with examples.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%: the only parameter 'text' is described as 'Text to convert'. The description adds no extra meaning beyond what the schema already provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert text to lowercase' clearly states the verb (convert) and resource (text to lowercase). However, it does not distinguish from the sibling tool 'lowercase', which likely performs the same function. The purpose is specific but lacks differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'lowercase' or other case conversion tools. The description gives no context for appropriate usage or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_pascal_caseCInspect
Convert text to PascalCase.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It only states the conversion without explaining how it handles spaces, special characters, or edge cases. This is insufficient for a simple but potentially nuanced operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short and somewhat concise, but it lacks critical details. It is not well-structured for efficient agent understanding; every sentence should add value, and this one sentence is too sparse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no output schema), the description is still incomplete. It fails to specify the exact PascalCase rules (e.g., handling of numbers, underscores, or mixed case). Additionally, the presence of a similarly named sibling 'pascal_case' suggests a need for differentiation that is not addressed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a single parameter 'text' described as 'Text to convert'. The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it converts text to PascalCase, which is a specific transformation. However, it does not differentiate from the sibling tool 'pascal_case', which could cause confusion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'to_camel_case' or 'pascal_case'. The agent has no basis for choosing among similar operations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_path_caseCInspect
Convert text to path/case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits such as handling of spaces, punctuation, or case of the output. It is insufficiently transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely brief (one sentence) but omits essential information. Conciseness without substance is not effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool, the description fails to specify the output format or any conversion rules, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'text' with description 'Text to convert'. The tool description adds no extra meaning beyond this. While schema coverage is 100%, the description does not enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool converts text to path/case, but does not define what path case is (e.g., using slashes). Among many sibling case converters, this lacks specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other case converters like to_kebab_case or to_snake_case. The description implies a context but does not elaborate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_romanBInspect
Convert number to Roman numerals.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to convert (1-3999) |
Output Schema
| Name | Required | Description |
|---|---|---|
| roman | Yes | |
| number | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states the conversion without mentioning the valid input range (1-3999), which is defined in the schema but not highlighted in the description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no wasted words. It could be slightly improved by including the range, but it remains appropriately concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter conversion tool with full schema coverage and an output schema, the description is largely sufficient. The presence of the sibling 'number_to_roman' suggests a need for differentiation, but the description alone still conveys the core functionality.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter description already specifying 'Number to convert (1-3999)'. The tool description adds no additional meaning beyond what the schema provides, meriting the baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert number to Roman numerals' uses a clear verb-resource structure and distinguishes from the sibling 'roman_to_number' which does the reverse. However, it does not differentiate from the similarly named sibling 'number_to_roman', which likely performs the same conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool over alternatives like 'number_to_roman'. It lacks context on prerequisites or typical use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_screaming_snake_caseBInspect
Convert text to SCREAMING_SNAKE_CASE.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, and description doesn't disclose edge cases (e.g., handling of numbers, special characters, whitespace). Minimal behavioral info for a transformation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence, no wasted words. Could be more informative but efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple, but description doesn't mention return value or output format. Without output schema, this gap reduces completeness for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with parameter described as 'Text to convert'. Description adds no extra meaning beyond schema, so baseline score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states action (Convert) and target format (SCREAMING_SNAKE_CASE). Distinct from siblings like to_snake_case (lowercase) and to_upper_case.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use vs alternatives. Implied by name and description but lacks when-not or comparison to siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_sentence_caseCInspect
Convert text to Sentence case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description bears full burden. It only states the conversion, lacking details on how punctuation, numbers, or multiple sentences are handled. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at five words and front-loaded. While it earns its place with no wasted text, it could be slightly expanded to improve clarity without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple text conversion tool, the description gives the basic idea. However, without an output schema, it does not mention the return format (e.g., string). It is minimally complete but could be more helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of parameters with a description for 'text' ('Text to convert'), which is adequate. The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Convert text to Sentence case,' which is a specific verb and resource. However, it does not differentiate from sibling case-conversion tools like 'sentence_case' or 'to_title_case', but the name itself provides distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. With many sibling case-conversion tools, explicit usage context would help the agent choose correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_snake_caseBInspect
Convert text to snake_case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full responsibility. It only states the basic function without detailing behavior for edge cases (e.g., handling of special characters, preserve of casing, or delimiter handling).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: a single clear sentence with no unnecessary words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description is adequate but lacks details on return format, handling of empty strings, or character normalization. It could be improved by mentioning that spaces become underscores.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage, describing the single 'text' parameter. The description adds minimal value beyond repeating 'Text to convert'. With full schema coverage, the baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: convert text to snake_case. It uses a specific verb and resource, and distinguishes itself from sibling case converters like to_camel_case and to_kebab_case through its name and description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance is provided. There is no mention of when to use this tool over other case converters, nor any context about prerequisites or alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_title_caseCInspect
Convert text to Title Case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks behavioral details such as how Title Case is applied (e.g., handling of articles, prepositions, or non-letter characters). No annotations are provided to compensate for this gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with a single sentence. It is well-structured for the simplicity of the tool, though it could benefit from slightly more structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple text transformation with one parameter and no output schema, the description is minimally adequate. It does not mention return type or edge cases, but the tool's behavior is fairly self-evident.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides a description for the 'text' parameter ('Text to convert'), covering 100% of parameters. The tool description adds no additional semantic value, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action and resource ('Convert text to Title Case'). However, it does not differentiate from sibling tools like 'title_case' or 'smart_title_case', which may have identical or similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus alternatives, nor does it mention any prerequisites or conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_train_caseCInspect
Convert text to Train-Case.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It only states the conversion action without detailing how special characters, whitespace, or case are handled. Minimal behavioral disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise. However, it is almost too minimal; a bit more detail would improve it without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with 100% schema coverage and no output schema, the description is inadequate. It fails to explain what 'Train-Case' means or provide examples, which is especially problematic given the many similar case converters.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has one parameter 'text' described as 'Text to convert' (100% coverage). The description adds no further semantic value beyond the schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb 'Convert' and the resource 'text to Train-Case', which is specific. However, it does not differentiate Train-Case from similar case formats like kebab-case, which exists as a sibling tool. The purpose is clear but not uniquely distinguished.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus other case conversion siblings (e.g., to_kebab_case, to_snake_case). The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
to_upper_caseBInspect
Convert text to UPPERCASE.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to convert |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility but only states the obvious function. It does not disclose edge-case handling, character encoding, or any other behavioral details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, consisting of a single sentence that directly conveys the tool's purpose. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one required parameter, no output schema), the description is largely adequate. It could mention that the conversion is locale-independent or note ASCII vs Unicode, but for most use cases, it suffices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes the parameter as 'Text to convert', which is clear. The description adds no additional semantic value beyond what the schema already provides. Baseline 3 applies due to 100% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts text to uppercase. However, there is a sibling tool named 'uppercase' which likely performs the same function, and no differentiation is provided.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'uppercase' or other case conversion tools. No context for usage is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
triadic_colorsAInspect
Get triadic colors (three colors equally spaced on color wheel).
| Name | Required | Description | Default |
|---|---|---|---|
| hex_color | Yes | Hex color to get triadic colors for |
Output Schema
| Name | Required | Description |
|---|---|---|
| triadic | No | |
| original | Yes | |
| tetradic | No | |
| analogous | No | |
| split_complementary | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. Description mentions it returns three colors equally spaced, which is the core behavior. Does not disclose output format, error handling, or side effects, but for a pure color calculation tool, this is minimally adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence of 12 words, front-loaded with the key action and explanation. No wasted words, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description sufficiently explains the tool's purpose. It could optionally mention the format of returned colors, but that is likely covered by the output schema. Minor gap is not penalized heavily.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with basic parameter description. The description adds the concept of triadic colors but does not add parameter-specific details beyond what the schema provides. Baseline of 3 applies due to high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'Get' and resource 'triadic colors'. Explains what triadic means (three colors equally spaced on color wheel), distinguishing it from sibling color tools like analogous, complementary, tetradic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance. Usage is implied by the tool's name and description, but there is no mention of alternatives or context for choosing this over other color tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
trimCInspect
Trim whitespace from text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to trim |
Output Schema
| Name | Required | Description |
|---|---|---|
| trimmed | Yes | |
| original | Yes | |
| trimmed_left | Yes | |
| trimmed_right | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description does not disclose whether trimming applies to only leading/trailing whitespace or all whitespace. Edge cases like empty strings or whitespace-only inputs are not mentioned.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, which is efficient for a simple tool. However, it may be too minimal, lacking details that would justify its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description does not explain the return format. For a text manipulation tool with many siblings, more context about what exactly gets trimmed would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema documents one parameter 'text' with a description. With 100% schema coverage, the description adds no additional meaning. It could benefit from specifying the type of whitespace trimmed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool trims whitespace from text, which is a common operation. However, it does not specify whether it trims leading/trailing or all whitespace, which could be ambiguous compared to sibling tools like 'remove_whitespace'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives such as 'remove_whitespace' or 'normalize_whitespace'. The description lacks context for selection among similar sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
true_endpointAInspect
Returns true.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| value | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The behavior is fully disclosed: it returns true. No ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise, two words, front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a constant-return tool; output schema likely confirms boolean type.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters, so description adds no param semantics but none needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns the boolean true, and the sibling false_endpoint contrasts, making purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidance provided; agent must infer from name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
truncateAInspect
Truncate to integer (remove decimal part).
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Number to truncate |
Output Schema
| Name | Required | Description |
|---|---|---|
| number | Yes | |
| result | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It honestly discloses the behavior of removing the decimal part, which is straightforward and sufficient for a simple numeric operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no verbosity, front-loaded with the key verb and action. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description provides sufficient context about the operation. It could mention the output type but is otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the schema already documents the parameter 'number'. The description adds no extra meaning beyond what the schema provides, meeting the baseline expectation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'truncate' and the resource 'integer' with the action 'remove decimal part', making the purpose unmistakable and distinct from sibling tools like floor, ceil, or round.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use truncation (to remove decimals), but does not explicitly differentiate from alternatives like floor or round, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
truncate_2CInspect
Truncate text to a specified length.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to truncate | |
| length | No | Maximum length | |
| suffix | No | Suffix to add if truncated | ... |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| truncated | Yes | |
| was_truncated | Yes | |
| original_length | Yes | |
| truncated_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully describe behavior. It omits details such as what happens when text is shorter than length (no truncation, no suffix), or edge cases like suffix exceeding length.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that communicates the core purpose efficiently. However, it may be too minimal and could benefit from a bit more context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with an output schema, the description is adequate but lacks details on truncation behavior (e.g., suffix handling, what happens with short input). It meets the minimum but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema; it does not clarify that 'length' refers to character count or other nuances.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'truncate' and the resource 'text', and specifies the key parameter 'specified length'. However, it does not differentiate from the sibling tool 'truncate', which likely performs the same operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool vs. alternatives like 'truncate' or 'format_truncate'. There are no when-to-use or when-not-to-use instructions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unflatten_jsonAInspect
Unflatten a flat JSON object back to nested structure.
| Name | Required | Description | Default |
|---|---|---|---|
| separator | No | Key separator | . |
| json_string | Yes | Flattened JSON string |
Output Schema
| Name | Required | Description |
|---|---|---|
| depth | No | |
| error | No | |
| valid | No | |
| unflattened | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description offers minimal behavioral details. It does not explain how the unflattening works (e.g., separator handling, edge cases, validation). The description is too sparse to fully inform an agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and front-loaded with the action verb. It conveys the essential information without any superfluous words. Ideal for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 parameters, output schema present), the description is almost complete. However, it could briefly mention that it reverses 'flatten_json'. Still, it provides sufficient context for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for both parameters. The description adds no extra meaning beyond the schema; it merely states the operation. Baseline score of 3 applies as the schema already documents the parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: unflattening a flat JSON object to nested structure. The verb 'unflatten' and resource 'flat JSON object' are specific, and it directly contrasts with sibling tool 'flatten_json'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one needs to restore a nested structure from a flat JSON, but it does not explicitly state when to use or not, nor mention alternatives or prerequisites. Given the simplicity, a score of 3 is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unique_itemsCInspect
Get unique items from a list.
| Name | Required | Description | Default |
|---|---|---|---|
| items | Yes | Comma-separated items |
Output Schema
| Name | Required | Description |
|---|---|---|
| unique | Yes | |
| original | Yes | |
| unique_count | Yes | |
| original_count | Yes | |
| duplicates_removed | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, and the description does not disclose behavioral traits such as order preservation, case sensitivity, or handling of whitespace in comma-separated items. For a tool with no annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence. While it is efficient, it could be slightly more informative without becoming verbose, earning a 4 rather than a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate. However, it does not explain behavioral details like order preservation or definition of uniqueness, leaving some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers the only parameter 'items' with a description of 'Comma-separated items', so schema coverage is 100%. The description adds no additional meaning beyond what the schema provides, earning a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get unique items from a list' clearly states the verb and resource, indicating deduplication. However, it does not distinguish from sibling tools like 'array_dedupe' which likely performs the same operation, so it's not maximally specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'array_dedupe' or 'sort_items'. The description lacks context for choosing this tool among many array-related siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unix_to_datetimeBInspect
Convert Unix timestamp to datetime.
| Name | Required | Description | Default |
|---|---|---|---|
| timestamp | Yes | Unix timestamp | |
| timezone_name | No | Timezone for output | UTC |
Output Schema
| Name | Required | Description |
|---|---|---|
| date | Yes | |
| time | Yes | |
| datetime | Yes | |
| timezone | Yes | |
| timestamp | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It fails to mention that the input timestamp is expected in seconds, the output datetime format (e.g., ISO 8601), or that the timezone_name parameter accepts IANA timezone names.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words), but at the cost of missing important details. While brevity can be positive, here it leads to under-specification. It is front-loaded but does not earn its place due to lack of informative content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of many sibling conversion tools and an output schema (not shown), the description should provide more context about the output format and any edge cases. It is insufficient for a tool that could have ambiguities in timestamp interpretation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully describes both parameters (timestamp as 'Unix timestamp', timezone_name as 'Timezone for output'). The description adds no additional semantic value beyond what the schema provides, meeting the baseline for 100% coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Convert' and the specific resource transformation 'Unix timestamp to datetime'. It is unambiguous and distinguishes itself from sibling tools like 'datetime_to_unix' which does the reverse.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as 'convert_timestamp' or 'format_date'. It does not mention the expected timestamp format (seconds vs milliseconds) or any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
uppercaseAInspect
Convert text to uppercase.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to uppercase |
Output Schema
| Name | Required | Description |
|---|---|---|
| original | Yes | |
| uppercase | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the core behavior (uppercasing text) but does not elaborate on edge cases, such as handling of non-alphabetic characters, locales, or special Unicode. Without annotations, some additional context would be helpful, but the behavior is straightforward.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is front-loaded with the key action. It is concise with no unnecessary words, earning its place perfectly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (one parameter, no output schema needed), the description is adequate. However, since an output schema exists, a brief note on the return type would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a clear parameter description 'The text to uppercase'. The tool description adds no extra meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Convert text to uppercase' clearly states the action (convert) and the resource (text), and the output format (uppercase). It distinguishes from sibling tools like 'lowercase' and 'capitalize' by specifying the exact transformation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. While it's obvious for a simple utility, the description does not mention any prerequisites, limitations, or situations where other tools might be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
url_decodeCInspect
URL decode text.
| Name | Required | Description | Default |
|---|---|---|---|
| encoded | Yes | URL encoded string to decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| decoded | Yes | |
| encoded | Yes | |
| decoded_plus | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It fails to mention any traits like handling of invalid input, character set, or error behavior, offering zero transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise, but it sacrifices substance. It could include brief operational details without harming conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the tool's simplicity and the presence of an output schema, the description lacks completeness. It doesn't explain the decoding process or mention percent-encoding, which is critical for correct usage among similar tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% description coverage for the single parameter 'encoded' as 'URL encoded string to decode'. The description adds no additional meaning beyond that baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'URL decode text' restates the tool's name without adding specificity. It vaguely indicates decoding but doesn't clarify that it decodes percent-encoded URL strings or distinguish from sibling url_decode_2.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like url_decode_2 or url_encode. Context signals show siblings, but the description offers no usage criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
url_decode_2BInspect
URL decode a string.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to URL decode |
Output Schema
| Name | Required | Description |
|---|---|---|
| decoded | Yes | |
| encoded | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description only states 'URL decode a string'. No details on encoding assumptions, error handling, or behavior beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exceedingly concise with one short sentence containing no fluff. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema and the simplicity of the tool, the description is minimally adequate. However, it could be more explicit about the decoding standard.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the parameter description in the schema is sufficient. The description does not add extra meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool decodes a URL string, but does not differentiate it from sibling tool 'url_decode' which likely has identical functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'url_decode' or 'url_encode_2'. The description does not specify context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
url_encodeCInspect
URL encode text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to URL encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| encoded | Yes | |
| original | Yes | |
| encoded_plus | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not disclose behavioral traits such as the encoding standard (e.g., RFC 3986), character handling, or any side effects. For a transformation tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at four words. It is efficiently front-loaded, though it could be slightly more informative without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple nature of the tool and the existence of an output schema, the description is adequate but lacks behavioral details and differentiation from similar tools. It is minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the baseline is 3. The description adds no extra meaning beyond the schema's description of 'Text to URL encode'. It does not compensate for any gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'URL encode text' clearly states the tool's function. However, it does not differentiate from the sibling tool 'url_encode_2', which likely has similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'url_encode_2' or 'url_decode'. No usage context is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
url_encode_2CInspect
URL encode a string.
| Name | Required | Description | Default |
|---|---|---|---|
| safe | No | Characters to not encode | |
| text | Yes | Text to URL encode |
Output Schema
| Name | Required | Description |
|---|---|---|
| encoded | Yes | |
| original | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as idempotency, side effects, or safety. For a simple encoding function, at least stating it is safe and stateless would add transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise and to the point. However, it could include more context without being overly verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic purpose but lacks differentiation from siblings and fails to explain the return value (though output schema exists). For a simple tool, it is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for both parameters. The description adds no additional meaning beyond what is already in the schema, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'URL encode a string' clearly states the action and resource. However, it does not differentiate from the sibling tool 'url_encode', leaving ambiguity about when to use this variant.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'url_encode'. No context for usage or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
user_agentBInspect
Parse a user agent string.
| Name | Required | Description | Default |
|---|---|---|---|
| ua | Yes | User agent string to parse |
Output Schema
| Name | Required | Description |
|---|---|---|
| os | No | |
| raw | Yes | |
| device | Yes | |
| browser | No | |
| browser_version | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must disclose behavior. It only states the function without mentioning output format, error handling, or limitations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise but under-specified. One sentence may be sufficient for a simple tool, but it lacks structure or any additional context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description is minimally acceptable. However, it does not clarify the parsing scope or expected result structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The tool description adds no new meaning beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states exactly what the tool does with a specific verb (Parse) and resource (user agent string), distinguishing it from siblings like parse_url or parse_date.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as parse_url or other string parsers. The description does not specify context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_alphanumericAInspect
Check if text is alphanumeric.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Text to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| is_alpha | Yes | |
| is_digit | Yes | |
| is_numeric | Yes | |
| is_alphanumeric | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses the core behavior (checking alphanumeric). No annotations provided, but description is sufficient for a simple validation tool. Could clarify what 'alphanumeric' includes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, clear, and concise sentence with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for a simple tool with output schema. Could include a brief example or mention of return type, but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and parameter description is minimal. Description adds no extra meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'check' and the condition 'alphanumeric'. Distinguishes from sibling validation tools like validate_email or validate_ip.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus other text validation tools. Missing context about alternatives or when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_base64CInspect
Validate a base64 string.
| Name | Required | Description | Default |
|---|---|---|---|
| base64_str | Yes | Base64 string to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| base64 | Yes | |
| is_valid | Yes | |
| decoded_length | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose behavior such as whether it returns a boolean, throws an error on invalid input, or performs a decode check. For a validation tool, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short (4 words), which is concise but lacks detail. For a simple tool, it is acceptable but could benefit from additional context without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has an output schema (unknown structure) and a single parameter, but the description does not mention what the tool returns. For validation, agents may need to know the return type. Adequate but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the one parameter with a description ('Base64 string to validate'), so the description adds no extra meaning. Baseline 3 applies as schema coverage is 100%.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Validate a base64 string.' It clearly identifies the tool's action (validate) and resource (base64 string), distinguishing it from sibling tools like base64_encode and base64_decode. However, it does not specify what 'validate' entails (e.g., syntax check, decodeability).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., base64_decode for verification, validate_email for emails). It lacks context about prerequisites or complementary tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_credit_cardBInspect
Validate a credit card number using Luhn algorithm.
| Name | Required | Description | Default |
|---|---|---|---|
| number | Yes | Credit card number |
Output Schema
| Name | Required | Description |
|---|---|---|
| length | No | |
| number | Yes | |
| reason | No | |
| is_valid | Yes | |
| card_type | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It mentions the Luhn algorithm but does not disclose return type, error behavior, or what happens for invalid inputs. The agent cannot infer whether it returns a boolean, validation object, or throws an error.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence with no wasted words. It is front-loaded with the verb and resource, making it efficient for an AI agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description provides the core purpose but lacks details on the validation result. It is adequate but could be improved by stating the return type or behavior for invalid inputs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter 'number' described as 'Credit card number'). The description adds no additional semantics beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates a credit card number using the Luhn algorithm, which is a specific verb-resource pair. It distinguishes from siblings like format_credit_card and generate_credit_card by focusing on validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not indicate when to use this tool versus other validation tools (e.g., validate_email, validate_ip) or alternative credit card validation methods.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_dateCInspect
Validate a date string.
| Name | Required | Description | Default |
|---|---|---|---|
| format | No | Expected date format | %Y-%m-%d |
| date_str | Yes | Date string to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| date | Yes | |
| error | No | |
| format | Yes | |
| parsed | No | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It only states 'Validate a date string' without disclosing return format (e.g., boolean, object), behavior on invalid input, or output schema details. The agent cannot predict how to interpret the result.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence with no wasted words, but it sacrifices completeness. It is appropriately sized but could include more information without becoming verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown), the description still fails to explain output semantics, edge cases, or how it differs from parse_date. The low complexity of the tool is offset by missing return behavior details.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters have schema descriptions covering 100% of the meaning. The description adds no extra value beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate a date string' clearly states the verb (validate) and resource (date string), but it doesn't distinguish from sibling tools like parse_date, which may also perform validation. The purpose is clear but lacks differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description does not mention when to use this tool instead of alternatives like parse_date or format_date, nor does it specify prerequisites or constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_domainCInspect
Validate a domain name.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | Domain name to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| tld | No | |
| domain | Yes | |
| is_valid | Yes | |
| subdomain | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, and the description adds no behavioral details. It does not disclose return type, error handling, or what constitutes a valid domain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) and front-loaded, but it sacrifices useful detail. It is not overly verbose, but could include more context without becoming long.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, output schema exists), the description is minimal but incomplete. It lacks context on validation criteria, which is important for a validation tool. The output schema likely provides return structure, but the description should hint at behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no extra meaning beyond what the schema provides. The parameter 'domain' is adequately defined in the schema, but the description does not clarify nuances like allowed formats or length limits.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'validate' and the resource 'domain name,' distinguishing it from siblings like validate_url or validate_email. However, it does not specify what aspects of the domain are validated (e.g., syntax, DNS, existence), leaving some ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as validate_url or validate_email. The agent must infer usage from the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_emailCInspect
Validate an email address.
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | Email address to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| Yes | ||
| parts | Yes | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose any behavioral traits beyond the bare action. The agent cannot infer what validation is performed, what the output schema provides (though known to exist), or if it has side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely brief (two words). While free of fluff, it omits critical details, making it under-specification rather than effective conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema and the tool's simplicity, the description is insufficient. It fails to convey validation specifics, expected input format, or output nature, leaving the agent underinformed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, and the description adds no extra meaning beyond the parameter's schema description. The baseline of 3 applies as the schema carries the burden.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate an email address' clearly states the action (validate) and the resource (email address), distinguishing it from sibling validation tools like validate_url or validate_ip.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No information on when to use this tool vs alternatives. No context on validation strictness, RFC compliance, or if it performs syntax vs existence checks.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_hexCInspect
Validate a hexadecimal string.
| Name | Required | Description | Default |
|---|---|---|---|
| hex_str | Yes | Hex string to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| hex | Yes | |
| length | No | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose what happens upon validation (e.g., returns boolean, throws error). For a validation tool, this is a significant gap; agents need to know how to interpret the result.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise and front-loaded. However, it could be more informative without losing brevity. A 4 reflects appropriate size for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has only one parameter and an output schema (not shown), the description might be sufficient if the output schema explains the return value. However, without context on behavior and sibling differentiation, it is only minimally complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The parameter 'hex_str' is described in the input schema as 'Hex string to validate', and schema coverage is 100%. The description adds no additional semantic value beyond the schema, earning a baseline 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (validate) and the resource (hexadecimal string), but does not differentiate from the sibling tool 'is_valid_hex', which likely performs a similar check. A 4 reflects a clear purpose without sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool over alternatives like 'is_valid_hex' or other validation tools. There is no context on expected input format or behavior on invalid strings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_ipBInspect
Validate an IP address (v4 or v6).
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | Yes | |
| version | No | |
| is_valid | Yes | |
| is_global | No | |
| is_private | No | |
| is_loopback | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fails to disclose behavior such as return type (boolean, error) or side effects. It only states 'validate' without specifics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is minimally adequate but could be more helpful by specifying the output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single parameter 'ip', and the description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates an IP address and mentions both v4 and v6, but does not differentiate from the sibling tool 'validate_ip_2'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'validate_ip_2' or other validation tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_ip_2CInspect
Validate if a string is a valid IP address.
| Name | Required | Description | Default |
|---|---|---|---|
| ip | Yes | IP address to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| ip | Yes | |
| valid | Yes | |
| is_ipv4 | Yes | |
| is_ipv6 | Yes | |
| version | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose validation criteria (e.g., IP version, allowed formats) or the output format, despite the existence of an output schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single concise sentence with no excess, though it could add more context without losing efficiency.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple validation tool, but lacks specification of IP version and fails to distinguish from the sibling 'validate_ip'.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear parameter description. The description adds no further semantic value beyond stating the tool's purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool validates IP addresses, but does not differentiate it from the sibling 'validate_ip' tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives like 'validate_ip', or what constitutes a valid IP (IPv4, IPv6, etc.).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_jsonCInspect
Validate JSON syntax.
| Name | Required | Description | Default |
|---|---|---|---|
| json_str | Yes | JSON string to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| json | Yes | |
| type | No | |
| error | No | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description does not disclose behavior beyond basic validation. Does not mention return format or error handling.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
One concise sentence that communicates the core purpose efficiently. No unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema, the description is minimally adequate. However, more context about what 'validate' entails (e.g., strictness, error messages) would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for the single parameter. The tool description adds no additional meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate JSON syntax' clearly states the verb and resource. However, it does not differentiate from the sibling tool 'validate_json_2' or other validation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives. Does not specify prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_json_2CInspect
Validate if a string is valid JSON.
| Name | Required | Description | Default |
|---|---|---|---|
| json_string | Yes | JSON string to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| type | No | |
| error | No | |
| valid | Yes | |
| error_line | No | |
| error_column | No | |
| error_position | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided. The description only says it validates JSON, but does not disclose what happens for invalid input, whether it returns a boolean or throws, or any other behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no wasted words. It is appropriately sized for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter and an output schema exists. The description covers the basic purpose but does not explain return format. Adequate for a straightforward validator but could be more explicit.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter description. The tool description adds no additional meaning beyond the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it validates JSON strings. However, it does not distinguish from the sibling 'validate_json', which likely does the same thing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like 'validate_json'. No context on prerequisites or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_macCInspect
Validate a MAC address.
| Name | Required | Description | Default |
|---|---|---|---|
| mac | Yes | MAC address to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| mac | Yes | |
| is_valid | Yes | |
| normalized | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It fails to mention accepted MAC formats (e.g., colon-separated, hyphen-separated), case sensitivity, or whether the tool returns a boolean or detailed response. This is a critical gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (one short sentence) but lacks essential details, crossing from concise into under-specification. Every sentence should earn its place, but this one is too brief to be helpful.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and presence of an output schema, the description could be brief, but it does not mention what the output indicates (e.g., true/false for valid/invalid) or any edge cases. It is incomplete for an agent to use confidently.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the 'mac' parameter is described as 'MAC address to validate'). The description adds no extra meaning beyond the schema, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate a MAC address' clearly states the tool's action (validate) and resource (MAC address). It is distinct from sibling validation tools for email, IP, etc., though it does not explicitly differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like validate_ip or validate_hex. It does not specify any conditions or prerequisites for validation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_password_strengthCInspect
Check password strength.
| Name | Required | Description | Default |
|---|---|---|---|
| password | Yes | Password to check |
Output Schema
| Name | Required | Description |
|---|---|---|
| score | Yes | |
| checks | Yes | |
| strength | Yes | |
| max_score | Yes | |
| password_length | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavioral traits. It only states 'Check password strength' without explaining criteria, return type, or whether the password is transmitted securely. An output schema exists but does not compensate for missing behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely short, but this brevity sacrifices necessary detail. It is under-specified rather than effectively concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, output schema exists), the description still lacks essential context about what 'strength' entails, how it is evaluated, and how it differs from similar tools. It is incomplete for effective agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single 'password' parameter. The description adds no additional meaning, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Check password strength' clearly indicates the action (check) and resource (password strength). However, it does not differentiate from sibling tools like 'analyze_password' which may perform similar analysis. The purpose is clear but lacks sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as 'analyze_password', 'is_common_password', or 'password_entropy'. The description offers no context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_patternAInspect
Validate if a regex pattern is syntactically correct.
| Name | Required | Description | Default |
|---|---|---|---|
| pattern | Yes | Regular expression pattern to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| valid | Yes | |
| pattern | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided so description carries burden. It states validation of syntax but does not specify return type, behavior for invalid patterns, or regex dialect. Adequate but minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. Could be more structured (e.g., brief usage note) but efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With output schema present, return values need not be detailed. Description covers purpose, but lacks regex flavor and edge-case behavior. Good for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description covers 100% of parameter meaning. Description adds no extra context beyond what schema already provides, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool validates regex syntax (verb+resource). It distinguishes from siblings like 'test_pattern' (matching) and 'escape_pattern' (escaping).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs alternatives. For example, if matching is needed, 'test_pattern' is appropriate, but not mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_phoneCInspect
Validate a phone number.
| Name | Required | Description | Default |
|---|---|---|---|
| phone | Yes | Phone number to validate | |
| country | No | Country code for validation | US |
Output Schema
| Name | Required | Description |
|---|---|---|
| phone | Yes | |
| cleaned | Yes | |
| country | Yes | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description bears full responsibility for behavioral disclosure. It fails to describe what validation entails (e.g., format, length, country-specific rules), whether it returns a boolean or detailed result, or any side effects. The agent gains no insight into the tool's behavior beyond the trivial statement.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is too brief to convey necessary nuances. While concise, it sacrifices usefulness. It lacks any structure (e.g., providing examples, limitations, or behavioral notes), and every sentence should earn its place. Here, the sentence does not adequately inform.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has an output schema, return values are documented. However, the description is incomplete because it does not explain what 'validate' means (e.g., format check, existence check, country-specific rules) or provide any context about pruning behavior. The agent is left guessing about the tool's full capability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description does not need to repeat parameter details. The schema already documents 'phone' and 'country' with types and defaults. The description adds no new semantics, but the baseline for full coverage is a 3, which is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate a phone number' clearly states the action (validate) and the resource (phone number). It distinguishes from siblings like 'format_phone' and 'get_phone_pattern' by focusing on validation rather than formatting or pattern extraction. However, it does not explicitly contrast these alternatives, which would push it to a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus sibling tools like 'format_phone', 'get_phone_pattern', or other validation tools (e.g., 'validate_email'). There are no conditions, prerequisites, or exclusions mentioned, leaving the agent without context for appropriate invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_semverCInspect
Validate a semantic version string.
| Name | Required | Description | Default |
|---|---|---|---|
| version | Yes | Semantic version to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| parts | Yes | |
| version | Yes | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description lacks behavioral details beyond the verb 'validate'. With no annotations, the agent is left uninformed about return format (e.g., boolean, error), handling of edge cases (e.g., null values), or validation criteria (e.g., strict semver standard vs. looser format). The existing output schema might cover return type, but the description adds no transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no extraneous words. It is optimally concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema, the description is incomplete. It fails to specify the expected semver format (e.g., does it support pre-release or build metadata?), the validation result type, or error handling. For a tool among many validators, this lack of context hinders correct selection and invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since schema description coverage is 100%, the schema already describes the 'version' parameter as 'Semantic version to validate'. The description adds no new meaning, so baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Validate') and the resource ('semantic version string'), effectively distinguishing it from siblings like validate_email or validate_credit_card. However, it does not define what a semantic version is (e.g., MAJOR.MINOR.PATCH format), relying on the tool name for specificity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus other validation tools in the sibling list. There is no mention of prerequisites, alternatives, or conditions under which this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_urlCInspect
Validate a URL.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | URL to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| url | Yes | |
| parts | Yes | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It does not state what constitutes a valid URL, what the output is, or any side effects. The description is too minimal to inform the agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (4 words) and front-loaded with the key purpose. However, it is too short to fully inform the agent, so it is not a model of conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given a single parameter and an output schema (not shown but noted as present), the description could be slightly more complete, e.g., mentioning the return type. It is at the minimum viable level for such a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (the one parameter 'url' is described as 'URL to validate'). The description adds no additional meaning beyond the schema, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate a URL' clearly states the verb and resource, but it is very generic. Among many sibling validation tools (validate_email, validate_domain, etc.), and specifically 'is_valid_url', it does not differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'is_valid_url' or other validation tools. There are no exclusions or context given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
validate_uuidCInspect
Validate a UUID.
| Name | Required | Description | Default |
|---|---|---|---|
| uuid_str | Yes | UUID to validate |
Output Schema
| Name | Required | Description |
|---|---|---|
| uuid | Yes | |
| version | No | |
| is_valid | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden but only states the action without detailing behavior. It does not explain what constitutes a valid UUID (e.g., version, case sensitivity), the return value (boolean? error?), or any side effects. The input schema covers the parameter but adds no behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (two words), which is efficient for a simple tool. However, a slightly more informative sentence could improve clarity without losing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity (1 required param), high schema coverage, and existence of an output schema, the description is minimally adequate. It lacks explanation of the output or validation criteria, but for a straightforward validation tool, it meets basic needs.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline 3. The description adds no meaning beyond the parameter's own description 'UUID to validate'. The parameter is self-explanatory from its name and schema, but the tool description does not enhance it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Validate a UUID' clearly states the tool's purpose with a specific verb and resource. It distinguishes itself from sibling validation tools (e.g., validate_email, validate_url) but does not specify which UUID versions are supported or the exact format validated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No usage guidelines are provided. The description gives no indication of when to use this tool versus alternative validation tools or patterns, nor does it mention any prerequisites or context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
verify_hashBInspect
Verify a hash matches the text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Original text | |
| algorithm | No | Algorithm used | sha256 |
| hash_value | Yes | Hash to verify |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| matches | No | |
| algorithm | No | |
| computed_hash | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It fails to disclose whether the tool performs a cryptographic comparison, returns a boolean, or has any side effects. The agent is left guessing about the output and safety profile.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, making it efficient. However, it could be slightly more structured by mentioning the default algorithm or return type without adding significant length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity and full schema coverage, the description is adequate but minimal. With an output schema present, the return type need not be described, but additional context about verification semantics would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear parameter descriptions ('Original text', 'Algorithm used', 'Hash to verify'). The description adds no additional meaning beyond the schema, earning the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Verify a hash matches the text' clearly states the tool's action (verify) and resources (hash and text). It distinguishes from sibling tools like generate_hash (creates hash) and identify_hash (identifies algorithm), making it specific and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like compare_hashes or identify_hash. The description lacks context about scenarios where verification is appropriate or when other tools should be preferred.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
week_numberBInspect
Get the ISO week number of a date.
| Name | Required | Description | Default |
|---|---|---|---|
| date | Yes | Date (YYYY-MM-DD) |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | No | |
| date | No | |
| error | No | |
| day_name | No | |
| iso_year | No | |
| day_of_week | No | |
| week_number | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It only states the basic function but omits details such as return range, handling of invalid dates, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, concise sentence that gets straight to the point. No unnecessary words or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and output schema, the description covers the core functionality. However, it could benefit from additional context about the ISO week number standard or typical use cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema's date format specification.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it gets the ISO week number of a date. The verb and resource are specific. However, it does not differentiate from sibling 'week_number_2', leaving ambiguity about the specific standard used.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like week_number_2 or other date-related tools. The description implies usage but does not explicitly state when or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
week_number_2CInspect
Get the ISO week number for a date.
| Name | Required | Description | Default |
|---|---|---|---|
| datetime_str | Yes | Datetime in ISO format |
Output Schema
| Name | Required | Description |
|---|---|---|
| error | No | |
| datetime | No | |
| day_name | No | |
| iso_week | No | |
| iso_year | No | |
| day_of_week | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It states a simple read operation but does not disclose limitations, error handling, or whether it accepts any ISO date format. Minimal behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no redundant words. Efficient, though could be slightly more informative while remaining concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has an output schema (not shown) which likely describes the return value, so description need not explain returns. However, lacks completeness in contextualizing usage relative to sibling and providing any edge-case behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'datetime_str' has a description 'Datetime in ISO format' in the schema. The tool description adds no further meaning beyond the schema, and with 100% schema coverage, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states verb 'Get' and resource 'ISO week number for a date', which is specific. However, sibling tool 'week_number' exists and the description does not differentiate between them, so it loses a point for not providing distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives like 'week_number' or 'day_of_year'. The description does not mention context or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
word_countBInspect
Count words in text.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | The text to count words in |
Output Schema
| Name | Required | Description |
|---|---|---|
| text | Yes | |
| word_count | Yes | |
| character_count | Yes | |
| character_count_no_spaces | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description does not disclose behavioral details such as how words are defined (e.g., whitespace splitting, punctuation handling), what happens with empty strings, or performance considerations. No annotations are provided to supplement this.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise (5 words) and front-loaded with the core action. Every word is necessary, and there is no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
While the tool is simple and has an output schema, the description omits edge-case behavior (e.g., whitespace handling, punctuation, non-string inputs). It is minimally complete but lacks depth for nuanced understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with one parameter (text) described. The description adds 'words' context but does not elaborate on input format or edge cases, making it baseline adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Count words in text.' uses a specific verb (Count) and resource (words in text), making the tool's purpose immediately clear. It distinguishes itself from many sibling text tools like count_all_chars or count_substring.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is given on when to use this tool versus alternatives such as count_all_chars, count_char, count_substring, or other counting tools. The description provides no context about prerequisites or suitability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
would_you_ratherAInspect
Get a 'Would You Rather' question.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| option_a | Yes | |
| option_b | Yes | |
| question | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, but the description implies a simple read operation. It does not disclose any behavioral traits beyond the obvious, which is acceptable for a trivial tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with one sentence, no wasted words, and front-loaded information. It earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the low complexity and presence of an output schema, the description is sufficient. It tells the agent what it does without needing to detail output format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters, and the schema coverage is 100%. The description adds no parameter information, which is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get a 'Would You Rather' question.' clearly states the action and resource. It is specific enough to distinguish from sibling random generators, though it does not further elaborate on the nature of the question.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like dad_joke or random_trivia. The description lacks context for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
yes_noAInspect
Get a random yes or no answer.
| Name | Required | Description | Default |
|---|---|---|---|
| question | Yes | Your yes/no question |
Output Schema
| Name | Required | Description |
|---|---|---|
| answer | Yes | |
| question | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the full burden of behavioral disclosure. The description includes no details about randomness quality, whether it's truly random, or any usage limits. It only states the basic function without any behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no filler. It is front-loaded and to the point, earning a perfect score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, clear purpose), the description is adequate. However, it does not describe the output format, which might be expected due to no output schema visible here. For such a simple tool, the completeness is high.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema includes one parameter 'question' with a description 'Your yes/no question'. Schema coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema's parameter description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a random yes or no answer.' It specifies the verb 'get' and the resource 'random yes or no answer.' This distinguishes it from sibling tools like 'magic_8_ball' or 'random_boolean' by requiring a question parameter and returning a binary answer.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives like 'flip_coin' or 'random_boolean'. The purpose is implied for yes/no questions, but no exclusions or comparisons are provided. While the name and schema make the context clear, the description lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
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For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
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