mcp-devutils

Server Quality Checklist

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Latest release: v2.9.16
Disambiguation3/5
Overall tools are distinct, but there are overlapping pairs like timestamp/epoch_convert (both convert time) and uuid/nanoid/random_string (all generate random strings). Descriptions clarify most ambiguities, but an agent could still misselect between these.
Naming Consistency3/5
All names are lowercase snake_case, which is good, but the pattern is inconsistent: some are single nouns (uuid, base64), some are verb_noun (escape_html), and some are noun_verb (url_encode). This mixed convention makes the set slightly less predictable.
Tool Count2/5
46 tools is well above the typical 15-25 range and feels heavy even for a dev-utilities server. Several tools are near-redundant (timestamp/epoch_convert, uuid/nanoid/random_string), suggesting the count could be trimmed.
Completeness4/5
The server covers a broad range of developer needs: encoding, hashing, encryption, JSON/YAML/CSV, regex, date/time, networking, and text manipulation. Minor gaps exist (e.g., no string manipulation tool beyond regex), but overall it is a fairly complete utility surface.
Average 3.7/5 across 46 of 46 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
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 states 'Encode or decode base64,' which is a minimal restatement of the tool's name and does not disclose default behavior (e.g., default action is encode per schema), output format, or any limitations. This is insufficient transparency for a 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.
Conciseness4/5
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, but the extreme brevity leaves out important context that other dimensions need, so it is not a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no annotations and no output schema, the description needs to provide more context about return values and usage. It is too minimal to be considered complete; the agent would need to infer expected output and behavior from the schema alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool description adds no information about the parameters text and action. However, the input schema already provides full descriptions for both parameters (100% coverage), so per the scoring baseline, a score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Encode or decode base64' clearly states the tool's function with a specific verb and resource, making its purpose unambiguous. However, it does not explicitly distinguish this tool from sibling encoding tools like url_encode or hex_encode, so it falls 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.
Usage Guidelines2/5
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 when base64 is preferred over other encoding methods or any exclusions, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It only states the action without mentioning determinism, key handling, output encoding, or any side effects. This is insufficient for a cryptographic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant information. It is appropriately concise for the tool's simplicity and front-loads the core purpose effectively.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is too minimal for a 4-parameter tool with no output schema. It does not explain the return value format (e.g., hex string) or the default algorithm/encoding, leaving the agent to infer behavior from the schema enums. This creates a significant gap in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers all four parameters with descriptions, achieving 100% schema description coverage. The tool description adds no further meaning about the parameters, 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.
Purpose4/5
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 ('Generate') and resource ('an HMAC signature for a message'). It is distinct from sibling hashing tools by focusing on HMAC, though it does not explicitly differentiate itself from alternatives like 'hash' or 'aes_encrypt'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 siblings. It does not mention use cases, prerequisites, or alternative recommendations, leaving the agent without context to select HMAC over other crypto utilities.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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, but it only says 'test' without explaining the return format (e.g., boolean, match details), error behavior for invalid regex, or how flags affect execution. This is a significant transparency gap for a testing utility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words, making it highly concise and front-loaded. However, it is so brief that it under-specifies behavior, which is penalized in other dimensions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having three parameters and no output schema, the description fails to clarify what the tool returns or how results are structured. For an AI agent to correctly use the result of 'regex_test', this is a critical omission, making the description inadequate for full operational understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the schema; it does not elaborate on parameter relationships, expected formats, or edge cases.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'test' and identifies the resource ('regex pattern against a string'). It clearly states the core action and is distinct from siblings like regex_replace, though it does not explicitly differentiate or name alternatives.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 regex_replace or other string utilities. The description only states what the tool does, leaving the agent without context for selection decisions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 specify output format (e.g., hex string), default algorithm, or security implications of md5/sha1. The description is minimal and lacks important contextual details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no filler, directly stating the tool's function. It is well front-loaded and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the schema covers parameters, but there is no output schema and the description omits return format and default behavior. While a hash output is conventional, the description is minimally adequate but leaves some gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% parameter coverage, including descriptions for text and algorithm enum with default. The description listing the algorithms is redundant with the schema; baseline 3 is appropriate because the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (hash), the resource (text), and specific algorithms (md5, sha1, sha256). It distinguishes from simple hashing utilities, though it doesn't explicitly differentiate from HMAC or other cryptographic tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 hmac or scrypt_hash. It simply states what it does, leaving the agent to infer appropriate usage without 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.
Behavior2/5
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 mentions decimal (SI) and binary (IEC) representations, but it does not clarify how conversion works given the schema has no target-unit parameter — e.g., whether output returns all units or a single converted value. The '[PRO — 3 trial uses left]' prefix adds no behavioral clarity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single concise sentence, but it is prefixed with irrelevant trial-usage text ('[PRO — 3 trial uses left]') that does not help an agent select the tool. The important semantic content is not front-loaded due to this noise, making it less effective than it could be.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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, the description covers the basic unit types, but it does not specify the output format or behavior when no target unit is provided. Since there is no output schema, the description should clarify what the conversion returns, and it remains ambiguous.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 repeats the unit list already in the enum and adds the decimal/binary context, but it does not add meaningful new semantics for the value parameter or clarify the missing target-unit behavior beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 ('data size units'), and clearly enumerates the unit scope (bytes, KB, MB, GB, TB, PB) plus decimal/binary representation. This is precise enough to distinguish it from sibling tools like byte_count or number_base.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The purpose strongly implies it should be used when converting between data size units, but it does not explicitly state when to use it versus alternatives or mention any exclusions. There is no comparison to sibling tools such as byte_count, leaving usage context implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 conversion direction and omits details such as whether milliseconds are supported, timezone handling, or the behavior when the input is empty (which is only in 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. Perfectly concise for a simple utility.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 adequately conveys the core functionality. It could mention edge cases but is sufficient for the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for the single optional parameter, so the baseline is 3. The description adds no additional parameter semantics beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts between Unix timestamps and ISO 8601 dates, with a specific verb and resource. It does not distinguish from the sibling 'epoch_convert', so it loses the top score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 'epoch_convert'. The description implies use for date-time conversion but offers no exclusions or explicit context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full responsibility for behavioral disclosure, but it only states the core conversion action. It does not mention how input casing is detected, how non-alphanumeric characters are handled, whether spaces are treated as word delimiters, or any error behavior. This leaves significant ambiguity for 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.
Conciseness5/5
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 instantly. The '[PRO — 3 trial uses left]' note is slight extra but not damaging. Every word earns its place; no unnecessary filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the schema fully covers parameters, but there is no output schema or annotations. The description does not mention return value format or behavior with unusual inputs, which could matter for complete usage. It is minimally viable but lacking some contextual richness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%: both 'text' and 'to' have descriptive entries, and the enum for 'to' lists all acceptable values. The description adds no extra parameter meaning beyond what the schema already 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Convert') and explicitly lists all supported target formats (camelCase, snake_case, PascalCase, kebab-case, CONSTANT_CASE, Title Case), clearly distinguishing it from other text utility siblings. The function is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 any exclusions, prerequisites, or context where another tool (e.g., slug, string_escape) would be more appropriate. The only extra note is a PRO trial limit, not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 specify which characters get escaped/unescaped, whether it handles named or numeric entities, or what the default behavior is beyond an implicit understanding. The one-line description lacks behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
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 without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 no output schema, the description is minimally adequate. However, it leaves gaps such as which HTML entities are affected and what the return value looks like. Given the tool's simplicity, a more detailed description would be expected to fully complete the context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides descriptions for both parameters ('Text to escape or unescape' and 'Action: escape or unescape (default: escape)'), achieving 100% schema_description_coverage. The description adds no additional semantic meaning beyond what the schema states, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Escape or unescape HTML entities' uses specific verbs (escape/unescape) and identifies the resource (HTML entities), which clearly distinguishes it from sibling tools like url_encode or string_escape. The scope is explicit and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 string_escape or url_encode. It merely states the functionality without any when-to-use or when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 whether the random generation is cryptographically secure, what the default length is, or how the 'password' charset differs from others. This is a significant gap for a security-related operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no redundant information. It is maximally concise and front-loaded, earning a perfect score for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 mostly complete. However, without annotations or an output schema, it would benefit from mentioning the default length or that 'password' includes special characters to be truly comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the schema's param descriptions, but the schema already documents length and charset defaults. No extra value is provided, but none is strictly required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a random string or password' clearly states the tool's function with a specific verb and resource. However, it does not differentiate from sibling tools like uuid or nanoid that also generate random strings, 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied: it's for generating random strings or passwords. But no explicit guidance is given on when to use this tool versus alternatives, nor any exclusions like 'use uuid for unique identifiers'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. 'URL-safe slug' conveys basic transformation intent, but it does not disclose exact character handling, lowercase conversion, or output format. Some context is added beyond the name, but it is 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that is direct and contains no filler. It perfectly balances brevity with clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with only two parameters and no output schema. The description provides the essential purpose but lacks context on when to use it, expected output shape, or edge-case behavior. It is adequate for a straightforward utility but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters documented ('Text to slugify' and 'Word separator (default: '-')'). The description adds no extra parameter details, so it relies on the schema, which is adequate for this simple tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and clearly identifies the resource ('URL-safe slug') and the source ('text'). It is immediately understandable, though it does not explicitly differentiate from sibling tools like url_encode or case_convert.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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 url_encode or case_convert. The description merely states what it does, leaving the agent to infer appropriate usage contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 operation without detailing character encoding rules, handling of special characters, or return format. No behavioral nuances are revealed beyond what the schema already conveys.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single compact sentence that communicates the core function without any redundant words. It is appropriately sized for such a straightforward utility.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, but the lack of an output schema means the return format is not explicitly stated. The description implies the output is the encoded/decoded string, but it does not mention default behavior (defaults to encode) or potential error conditions. It is adequate for a minimal tool but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage for both parameters ('text' and 'action'), so the description need not elaborate. The description adds no extra meaning beyond the schema, but does not need to given the high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifically names the resource ('URL') and the action ('encode or decode'), which clearly distinguishes it from sibling tools like base64 or hex_encode. The phrase 'URL encode or decode a string' 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.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance is given for when to use this tool versus alternatives like base64 or string_escape. The description does not mention excluded 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the expected outputs (network address, broadcast, host range, number of hosts) which gives the agent an idea of what to expect. However, it doesn't address invalid input handling, IPv6 support, or its read-only nature. Since no annotations are provided, the description carries the full burden, and it partially fulfills that.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The functional description is a single sentence, which is concise. However, it's prefixed with '[PRO — 3 trial uses left]', which is irrelevant to the tool's behavior and could confuse an agent. This meta-information reduces the structure quality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with a single parameter and no output schema, the description lists the output fields, providing adequate context. However, it doesn't specify the output format (e.g., JSON structure) or edge-case behaviors, leaving some ambiguity. Overall, it's reasonably complete for its simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes the 'notation' parameter as 'CIDR notation (e.g. "192.168.1.0/24")' with 100% coverage. The description doesn't add any additional parameter details beyond restating that it parses CIDR. Therefore, it meets the baseline but doesn't exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Parse CIDR notation and show network address, broadcast, host range, and number of hosts.' This uses a specific verb (parse) and resource (CIDR notation) and even lists the expected outputs. It distinguishes itself from siblings like ip_info by focusing on CIDR parsing rather than general IP info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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. It doesn't mention any prerequisites, exclusions, or alternative tools. The sibling list includes ip_info which could be an alternative, but the description doesn't address it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 states that differences are shown 'line by line', but it does not disclose the diff format (e.g., unified, +/− markers), whether the output is a string or structured data, or behavior on identical inputs. This is insufficient for an AI agent to predict the tool's exact output representation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single, concise sentence that front-loads the primary purpose. However, the leading bracket '[PRO — 3 trial uses left]' is extraneous with respect to tool functionality, adding noise without value. This minor bloat prevents a perfect score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is relatively simple with two string parameters and no output schema, so the description is somewhat adequate. Yet, the absence of any mention of return format or edge cases (e.g., large inputs) leaves a gap. The existence of a sibling json_diff tool suggests a note about text-vs-JSON usage would round out the context. Overall, it is minimally complete but lacks some helpful context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides clear descriptions for both parameters: 'First text (original)' and 'Second text (modified)'. Coverage is 100%, so the schema adequately explains the parameters. The description itself does not add any further semantic nuance 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Compare' and clearly identifies the resource 'two text strings'. It also specifies the output type 'show the differences line by line', which distinguishes it from siblings like json_diff that compare JSON structured data rather than arbitrary text. 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for comparing plain text strings, but it does not explicitly state when to use this tool over alternatives. Since a sibling tool named json_diff exists, an explicit note about using diff for non-JSON text would improve clarity. However, the 'line by line' mention gives some contextual cue about the intended use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 disclosing behavioral traits. It only states the main action without explaining whether the tool modifies anything, what output format is returned, or how errors are handled. For a tool with no annotations, this is a significant gap in 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single, front-loaded sentence with no wasted words. However, the prefix '[PRO — 3 trial uses left]' adds noise and does not contribute to understanding the tool's purpose or usage. The essential content is concise and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 but incomplete. It does not mention the output format or behavior for edge cases (e.g., empty markdown, invalid headings). Since there is no output schema and no annotations, the description should provide more context to fully enable correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 'markdown' and 'max_depth'. The tool description does not add any additional parameter semantics, but since the schema already fully documents the parameters, the score is at the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a table of contents from markdown headings' uses a specific verb ('Generate') and resource ('table of contents from markdown headings'), clearly distinguishing it from all sibling tools. It is a concise, unambiguous statement of the tool's primary function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool's usage (input markdown, output a TOC) but does not provide explicit guidance on when to use it versus alternatives or any exclusions. There is no mention of prerequisites, edge cases, or when not to use it. This 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.
Behavior2/5
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 restates the action and formats already covered by the schema, without disclosing behavioral traits such as how escaping handles edge cases, whether it is safe for SQL injection contexts, or what the output looks like. This adds no value beyond the structured schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single, front-loaded sentence that efficiently conveys purpose. However, the '[PRO — 3 trial uses left]' prefix is irrelevant noise that does not earn its place, slightly reducing the conciseness score.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 parameter descriptions, the description is minimally viable. However, with no output schema, it does not mention that the tool returns the transformed string or any caveats about usage. A bit more context (e.g., return value or safety notes) would make it complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already describes all three parameters with 100% coverage, including the action default. The description adds no extra meaning to the parameters—it only repeats the enum values already present in the schema. Thus, baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's action ('Escape or unescape') and resource ('strings'), and explicitly lists the supported formats (JSON, CSV, regex, SQL, or shell). This distinguishes it from siblings like escape_html (HTML-only) and base64 (encoding), 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.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides the context of formats (JSON, CSV, regex, SQL, shell), implying when to use the tool. However, it does not explicitly state when to choose this tool over alternatives (e.g., 'use escape_html for HTML') or any exclusions, leaving the guidance only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full transparency burden. It does disclose a behavioral trait via the '[PRO — 3 trial uses left]' note, indicating a usage limit. However, it does not mention that the operation is non-destructive, return format, or any other side effects, leaving gaps in 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that front-loads the core purpose. The PRO traffic note is brief and adds relevant context without bloat.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the schema covers parameters, but with no output schema, the description should at least indicate the return type or form of output. It also lacks usage guidance. Some context is missing, though the simplicity of the tool keeps the gap moderate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% (both parameters have descriptions with defaults), so the baseline is 3. The description adds no additional parameter meaning beyond what the schema already provides, but the schema fully compensates.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Generate') and resource ('placeholder lorem ipsum text'), making it immediately clear what the tool does. It also distinguishes itself from sibling tools like random_string by naming the specific lorem ipsum placeholder format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
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, and no exclusions or context are provided. It simply states the action without any selection criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It does disclose a behavioral constraint via the '[PRO — 3 trial uses left]' prefix, indicating quota limits. However, it does not describe the output format, error behavior, or any limitations on input values, which would be expected for a conversion tool without 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core functional description is a single, clear sentence. The leading '[PRO — 3 trial uses left]' is extraneous to the function but provides necessary usage constraint information; it is front-loaded, which is good, though it adds a bit of noise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, and the description does not specify what the tool returns. 'Convert between' is ambiguous: whether it returns all representations at once or only one target base is unclear given the single input parameter. This is a significant completeness gap for a conversion tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description for the 'value' parameter covers 100% of its meaning by explaining the prefix conventions (0x, 0o, 0b, or plain decimal). The tool description adds no additional parameter semantics beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
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 names the resource and scope: numbers between decimal, hexadecimal, octal, and binary. This distinguishes it from sibling tools like base64 or hex_encode, which are string encodings, not numeric base conversions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the use case: converting among number bases. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention any exclusions or alternative tools. The usage context is implied by the purpose rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral burden. It only states the high-level action and fails to disclose return format, error handling, or the semantics of the 'satisfies a range' mode relative to the two parameters. The trial-use prefix is a business constraint, not a 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single clear sentence, but it is prefixed by '[PRO — 3 trial uses left]', which is non-functional metadata that distracts from the tool's purpose. The sentence itself is succinct and front-loads the verb after the prefix.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should explain what the tool returns (e.g., boolean, comparison code) and clarify how the 'range' mode maps to the two parameters, especially since the schema describes version2 as a simple version. These gaps leave the description incomplete for a tool with two modes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents both parameters with examples (coverage 100%), so the baseline is 3. The description adds the concept of checking a version against a range, which is not present in the schema descriptions, providing extra semantic meaning about the second parameter's possible role.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Compare' and 'check if') applied to semantic versions and ranges, which distinguishes it from the sibling utility tools. It names the exact resource type (semantic versions) and the two supported operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for comparing semantic versions or range checks, but it does not explicitly state when to choose this tool over alternatives, nor does it provide exclusions or mention related tools for version operations. There are no explicit 'use this when' or 'for X use' statements.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 correctly states that the tool can both encode and decode, and the schema adds the default action of 'encode'. However, it does not disclose edge-case behaviors such as handling of invalid hex input, case sensitivity, or whether whitespace is trimmed. For a pure transformation tool, this is acceptable but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is one sentence and front-loaded with the action. However, it includes an irrelevant prefix '[PRO — 3 trial uses left]' that does not aid tool selection and adds noise. While the body is concise, the unintended prefix detracts from overall conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with only two parameters and no output schema, the description covers the primary use case. It does not explain the exact output format (e.g., lowercase/uppercase hex) or error behavior for invalid hex during decode, but these are minor gaps for a utility of this simplicity. The description is sufficiently complete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with clear parameter descriptions for 'text' and 'action'. The tool description does not add any additional semantic nuance beyond what the schema already provides. Therefore, it meets the baseline 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Encode text to hexadecimal or decode hex back to text'. This includes a specific verb (encode/decode), a resource (text/hex), and also covers the binary nature of the operation. It distinguishes itself from siblings like base64 or url_encode by explicitly naming hexadecimal.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool by stating its function, but it does not explicitly mention alternatives or provide exclusions. For example, it does not say 'use this for hex conversion instead of base64'. The guidance is implicit rather than explicit, making it adequate but not highly informative.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 'Generate a UUID v4' and does not mention the random nature, security implications, or any side effects. There is no added context beyond what the tool name conveys.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with zero 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has a simple function with one optional parameter, and the schema fully covers that parameter. The return value (a UUID string) is implicit from the description. No output schema exists, but the description implies the output clearly enough. Slight lack of context around behavior like count limits or error handling, but for this tool it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100% for the single 'count' parameter, so the baseline is 3. The description itself does not add parameter-specific details, but the schema fully documents the parameter's meaning and default behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Generate a UUID v4' uses a specific verb ('Generate') and a specific resource ('UUID v4'), clearly distinguishing it from sibling tools like nanoid or random_string. It is concise and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The usage context is implied by the tool's purpose: if you need a UUID v4, use this tool. However, there is no explicit guidance on when not to use it or when to prefer an alternative (e.g., nanoid for short IDs). The description does not mention any conditions or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 mentions the input format and the encryption algorithm, but omits output format, error handling, key requirements, and any side effects. This is minimal disclosure for a decryption tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with a PRO usage note, front-loaded with the purpose. It contains no unnecessary words and is easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, and the schema covers parameters, but there is no output schema or annotations. The description does not state the return value or failure behavior, which is a notable gap. It is adequate for a basic tool but incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with both 'key' and 'encrypted' having clear descriptions. The description adds no new parameter semantics beyond what the schema already states, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Decrypt AES-256-CBC encrypted text.' It specifies the algorithm and mode, and 'Expects hex-encoded input from aes_encrypt' ties it to its sibling tool, distinguishing it from other crypto utilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use it by stating that input comes from aes_encrypt, providing a clear prerequisite. It does not explicitly mention alternatives or when not to use it, but the counterpart relationship is evident from the sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of explaining behavior. It only states the conversion action and formats, but does not disclose what the output looks like (single or multiple formats), how invalid inputs are handled, or whether the input format is auto-detected. This is a notable gap for a tool without 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that immediately states the action and involved formats. It is concise, front-loaded, and contains no filler or redundant details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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 output schema), the description is adequate but not fully complete. It omits any mention of the return format or whether the conversion returns all formats, which would be helpful for a complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the single 'color' parameter with concrete format examples, achieving 100% coverage. The description adds no further semantic value beyond implying the parameter accepts any of the listed formats, so the baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Convert' with a clear resource 'colors' and explicitly names the formats involved ('hex, RGB, and HSL'). This fully distinguishes the tool from its sibling utilities, none of which deal with color conversion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the tool is for converting between color formats. While it doesn't explicitly mention alternatives or exclusions, the context is obvious and no sibling tool competes for the same task, so this suffices.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the core behavior (explain in plain English and show next 5 run times) but lacks additional context such as timezone handling, error behavior for invalid expressions, or whether the next run times are relative to the current time. These are notable but not critical gaps for a simple utility.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, compact sentence that conveys both the primary action and the expected output. It is front-loaded and contains no filler or redundant information, making it highly efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool with no output schema or annotations, the description provides most of the needed context: what it does and what it returns. Missing details like timezone and error handling are minor for typical use, so it is nearly 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.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage for the only parameter, describing it as 'Cron expression (5 fields: minute hour day month weekday)'. The description adds no further information about the parameter, so the baseline score of 3 applies when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Explain a cron expression in plain English and show the next 5 run times'. It uses a specific verb ('explain') and resource ('cron expression'), and the 'show next 5 run times' adds concrete scope, distinguishing it from sibling utilities which focus on other unrelated operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used for interpreting cron expressions, but provides no explicit guidance on when to use it versus alternatives, nor any conditions or exclusions. It does not mention related tools or scenarios where it would not be appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 it shows specific timezones (UTC, US Eastern, US Pacific, Europe/London, Asia/Singapore), which is useful. However, it does not disclose output format, error handling, or any side effects, and the leading '[PRO — 3 trial uses left]' is a billing notice rather than 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single, focused sentence that is easy to parse. However, the '[PRO — 3 trial uses left]' prefix is extraneous and not directly relevant to the tool's purpose, slightly reducing structural quality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with two optional parameters and no output schema. The description explains what it does and mentions output timezones, but does not describe the exact return format or behavior with empty input (though the schema hints at empty for current time). Given the lack of an output schema, more detail on return structure would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 minimal extra meaning beyond the schema: it clarifies the value parameter can be epoch seconds, milliseconds, or ISO date, and mentions the default timezones shown, but the schema already documents both parameters well. No significant semantic lift.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Convert') and identifies the resource (epoch milliseconds/seconds and human-readable dates) and scope (multiple timezones). It clearly distinguishes from siblings like 'timestamp' by emphasizing multi-timezone conversion and specific timezone outputs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context about when to use this tool: for converting epoch time to/from human-readable dates and viewing multiple timezones. However, it does not explicitly mention when not to use it or mention alternative sibling tools, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 correctly states the two modes (format/minify) but does not disclose error handling for invalid JSON, default behavior beyond schema defaults, or other edge cases. The behavior is clear but not rich in detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One short sentence, immediately front-loaded, with zero wasted words. It communicates the essential functionality efficiently and 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.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple, and the combination of description and full schema coverage provides enough information for an agent to invoke it correctly. No output schema exists, but the return value (formatted/minified string) is obvious from the purpose. The only minor gap is the lack of explicit error behavior for invalid JSON.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all three parameters fully described. The description adds no parameter-specific information 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.
Purpose5/5
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 format (pretty-print) or minify JSON. This is a specific verb+resource combination that clearly distinguishes it from sibling tools like json_diff or sql_format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (formatting/minifying JSON) but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives. It is adequate for a simple utility but lacks proactive differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It does mention the analysis criteria (entropy, length, character diversity, common patterns), which indicates non-destructive analysis, but it does not describe the return format, edge cases, or whether it checks against actual breached password lists. This is partial transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence and is front-loaded with the core purpose. However, the leading '[PRO — 3 trial uses left]' is administrative metadata that adds noise and is unrelated to the tool's functionality, slightly detracting from conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
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, so the description should ideally explain what the user gets back. It does not mention the return value or whether the output is a score, label, or detailed report. While the purpose is clear, this missing information makes the description less complete than it could be for a standalone tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the 'password' parameter ('Password to analyze'), which is tautological but does define the parameter. The description does not add extra meaning beyond the schema, such as constraints or format expectations. Baseline 3 is appropriate when schema covers the parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze password strength — calculates entropy, checks length, character diversity, and common patterns'. It uses a specific verb ('Analyze') and identifies the resource ('password strength'), and the specificity (entropy, length, diversity, patterns) distinguishes it from sibling utility tools like hash or random_string.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is used when you need to assess password strength, and the listed checks make the context clear. However, it does not explicitly state exclusions or alternatives, though no sibling tool directly competes with this functionality.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It mentions support for capture groups in the replacement, which adds useful detail, but it does not disclose default behavior (e.g., global replacement) or mention error handling (e.g., invalid patterns). The schema provides some of this, but the description could be richer.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is two concise sentences, but the leading '[PRO — 3 trial uses left]' is unrelated to tool behavior and could confuse an AI agent looking for selection criteria. This unnecessary prefix detracts from the otherwise efficient structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple string manipulation tool, the description covers purpose and a key feature (capture groups), and the schema fully documents parameters. The output is not described, but for a replace operation it is implicitly the modified string. The missing default-behavior note is slightly incomplete but compensated by the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters. The description's mention of capture groups is redundant with the replacement parameter's description. No additional parameter semantics are added beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Find and replace') and names the resource ('text') with a clear mechanism ('using a regular expression'). It distinguishes the tool from sibling 'regex_test' by implying this one performs replacement, not just testing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly states the tool's use case (find and replace using regex) and gives a context cue (replacement strings with capture groups). However, it does not explicitly mention alternatives or when not to use it, which is acceptable for a well-scoped utility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses a usage constraint ('[PRO — 3 trial uses left]') and states the counting behavior, but does not mention edge-case handling (e.g., empty text, whitespace, word definitions), leaving some transparency gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the core function. The PRO trial note is a useful extra constraint, and every word earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 no output schema, the description states the input and the counting dimensions, but does not explicitly describe the return value structure. This is a minor gap for a straightforward counting utility, making it fairly complete overall.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 analyze'. The description adds no additional parameter semantics beyond what the schema already provides, warranting the baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description states the specific verb 'Count' and the resources: characters, words, lines, and bytes. This clearly distinguishes it from sibling tools like byte_count (counts only bytes) and char_info (character info).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
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 you need counts of text elements) but does not provide explicit alternative names or exclude scenarios. It lacks context on when not to use it, such as 'use byte_count if only bytes are needed'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole behavioral signal. It discloses that CSV→JSON produces an array of objects and JSON→CSV expects an array of objects, which is useful. However, it does not address delimiter behavior, malformed input, or any edge cases. For a stateless conversion tool this is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The functional description is concise, using two sentences to explain the two conversion directions. However, the "[PRO — 3 trial uses left]" prefix is irrelevant to tool operation and adds noise, though it does not significantly harm readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with three parameters and no output schema, the description covers the conversion directions and return expectations (e.g., array of objects for CSV→JSON). It lacks usage guidance versus siblings, but given low complexity, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents all parameters (100% coverage), but the description adds meaningful semantics: it specifies that JSON input must be an array of objects ("JSON→CSV converts an array of objects to CSV"), which is not explicitly stated in the schema's input description. This goes beyond the schema and helps the agent construct valid input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: "Convert between CSV and JSON." It further details both directions (CSV→JSON and JSON→CSV), which distinguishes it from sibling tools like yaml_json. The phrasing is unambiguous and action-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by explaining what the tool does, but does not explicitly state when to use this tool versus alternatives like yaml_json or json_format. There are no exclusions or comparisons to siblings, so the agent must infer usage from the purpose alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without any annotations, the description must carry the full burden of behavioral transparency. It only says 'Show', which implies a read-only operation, but it does not disclose whether calling this tool consumes trial uses, makes network requests, or has any side effects. Given that 'remaining trial uses' is part of the output, it is especially important to clarify whether the status check itself counts as a trial use.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that lists the three pieces of information shown. It is concise, front-loaded with the verb, and contains no unnecessary words or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple status tool with no parameters and no output schema, the description covers the main purpose but lacks details about the return format (e.g., structured JSON vs. plain text) and any potential side effects. Since there is no output schema, the description should at least indicate the nature of the response, but it only says 'Show' rather than specifying what the caller receives.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty with 100% coverage (vacuously). According to the rubric, a tool with no parameters gets a baseline of 4, and the description correctly does not attempt to add parameter meaning where none exists.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Show' and identifies the exact resources: license status, available tools, and remaining trial uses. This clearly distinguishes the tool from its sibling utility tools, which all perform specific data transformations rather than providing meta-status information.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the clear use case: call this tool when you need to check license status, see what tools are available, or check remaining trial uses. It does not explicitly mention alternatives or exclusions, but the context is clear enough for this status-checking tool, especially given the distinct purpose compared to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses key behaviors: shows keys, detects missing values, duplicate keys, and invalid lines. This is informative, though it does not specify output format or error handling, which would make it more complete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The main description is a single concise sentence that packs relevant information. However, the '[PRO — 3 trial uses left]' prefix is extraneous noise that does not serve the agent and slightly hurts structure.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter utility with no output schema or annotations, the description is reasonably complete: it explains the parse/validate behavior and the types of issues detected. It could be more explicit about return structure, but it is not critically incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema describes the only parameter 'content' with 100% coverage. The description adds no new parameter-specific details beyond restating that it parses .env content, so it does not elevate the 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Parse and validate .env file contents' with specific outputs like 'shows keys, detects issues like missing values, duplicate keys, or invalid lines.' This is a specific verb+resource that distinguishes it from the other utility siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for parsing .env files but does not explicitly state when to use it versus alternatives, nor does it mention any exclusions. The '[PRO — 3 trial uses left]' prefix hints at a usage limitation but does not provide clear guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the core behavior (showing added/removed/changed keys) but does not specify the output format, order of results, or error handling for invalid JSON. This adds some transparency but lacks comprehensive behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with two sentences: one for purpose and one for use cases. However, the leading '[PRO — 3 trial uses left]' is extraneous clutter that slightly detracts from the focus on tool functionality.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two string parameters and no output schema, the description is fairly complete. It covers purpose, use cases, and output categories. It could mention the exact output format, but given the simplicity, it is adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers both parameters fully with simple descriptions ('First JSON string', 'Second JSON string'). The description reinforces that these strings represent JSON objects to be compared, but adds little beyond what the schema already conveys, such as validation requirements or parsing behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Compare two JSON objects and show the differences — added, removed, and changed keys.' This is a specific verb+resource with distinct scope, and it differentiates from siblings like generic 'diff' or 'json_format' by focusing on the categorization of differences.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: 'Useful for debugging API responses, config changes, and state diffs.' This gives concrete use cases but 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It explains path syntax with examples, which is useful, but it doesn't disclose return format, error behavior for invalid JSON or missing paths, or whether wildcards are fully supported.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the main verb, but the '[PRO — 3 trial uses left]' prefix adds unrelated operational information that muddies the core message. Still, it is short and informative.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter tool with no output schema, the description adequately covers purpose, syntax, and a use case. However, it could improve by stating the return type or what happens on failure, which is relevant for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and includes examples for the path parameter, so the schema already provides strong guidance. The description's examples are redundant with the schema, adding no additional meaning beyond what the schema already contains.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool extracts values from a JSON object using dot-notation paths, with specific examples. This is a distinct action from sibling tools like json_format or json_diff, so it is well differentiated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says 'Useful for quickly inspecting nested API responses,' providing clear context for when to use it. It doesn't mention alternatives or exclusions, but the use case is enough to guide the AI agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 reveals the output format (PEM) and the generation action, implying a safe, non-destructive operation. However, it does not describe the exact return structure (e.g., whether public and private keys are returned separately) or note any side effects or prerequisites beyond the trial limit hint.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core purpose. The '[PRO — 3 trial uses left]' prefix adds non-functional context but does not obscure the meaning. Every other word serves the purpose and usage guidance, making it efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one well-documented parameter, the description provides clear purpose and usage context. It could specify the exact output structure (public/private key separation) since there is no output schema, but overall it is complete enough for an agent to select and invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the 'bits' parameter is fully documented in the schema. The description adds no extra parameter-specific semantics beyond saying the key is RSA or PEM, which is already implied. Baseline 3 is appropriate when the schema handles parameter documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Generate') and resource ('RSA key pair') and specifies the output format (PEM). This clearly distinguishes it from sibling tools like uuid or aes_encrypt, which are unrelated cryptographic or generation utilities.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly names appropriate contexts: 'testing, dev environments, and learning,' which tells an agent when to use this tool. It does not explicitly state when not to use it or mention alternative tools, but the guidance is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral burden. It discloses the formatting behavior (indentation and keyword capitalization) and constrains the supported query types, providing meaningful context. It does not mention edge cases like invalid SQL handling, but for a formatter 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is two short sentences, clear and front-loaded. However, the prefix '[PRO — 3 trial uses left]' is unrelated to the tool's function and adds noise, reducing conciseness. Otherwise it would be a 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (2 params, no output schema) and the description covers the supported query types and behavior. It does not explain return values or error handling, but these are reasonably inferable for a formatter. The description complete enough given the low complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 the notion of 'keyword capitalization' which mirrors the uppercase parameter but does not add new meaning beyond the schema. Baseline 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Format') and resource ('a SQL query') with detailed behavior ('proper indentation and keyword capitalization'). It also lists supported query types, distinguishing it from sibling formatters like json_format. 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.
Usage Guidelines3/5
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 you need to format SQL) and which query types are supported, but it does not explicitly state when not to use it or mention alternatives. The context is clear but lacks exclusions or alternative tool references.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It discloses the encryption algorithm, the output format (hex-encoded IV + ciphertext), and the key hashing behavior. It does not mention potential errors or side effects, but covers the key functional behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded with the core verb and resource. However, the '[PRO — 3 trial uses left]' prefix is extraneous promotional content that does not help an agent understand the tool's purpose or usage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description explicitly states the return format (hex-encoded IV + ciphertext), which is sufficient for this two-parameter tool. The algorithm and key handling are explained, making the description complete for a simple encryption utility.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so schema already documents both parameters. The description adds only a minor usage tip ('Use a strong key') and restates the key derivation behavior, providing limited additional semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Encrypt') and precise resource ('text using AES-256-CBC'), clearly distinguishing it from sibling tools like aes_decrypt and hash. The algorithm and output format are explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage context is implied by the tool's name and encryption purpose, and it includes a practical tip about key strength. However, it does not explicitly contrast with sibling tools (e.g., aes_decrypt) or state when not to use this tool, making the guidance implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry the burden. It discloses the encodings and utility but does not mention edge cases, output format, or limitations (e.g., invalid UTF-8 handling). The PRO trial note is present but doesn't add 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, and no redundant wording. The trial-use prefix is minor but doesn't undermine overall conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool, the description covers purpose and use cases well. However, without an output schema, it doesn't state how results are returned (e.g., single number vs. per-encoding object), which is a slight gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents the single parameter with 'Text to measure' (100% coverage). The description adds no additional parameter-specific detail, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool counts byte length of a string and enumerates three encodings (UTF-8, UTF-16, ASCII). This specific verb+resource distinguishes it from sibling tools like word_count and char_info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides concrete use cases: 'checking API payload sizes and database field limits.' While it doesn't explicitly compare against sibling tools, the context is clear and actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 discloses the key behavioral trait that signature verification is skipped and only the payload is decoded, but it does not mention how malformed tokens are handled or the exact 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no waste. It efficiently conveys the primary action and the key caveat in a compact format.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter utility with no output schema, the description sufficiently covers the tool's purpose and main caveat. It is brief but adequate for selecting and invoking the tool, though it could optionally mention return value structure or error behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already provides 100% description coverage for the 'token' parameter ('JWT token to decode'). The description adds no additional parameter-level meaning beyond what the schema states, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Decode'), the resource ('JWT token'), and the scope ('just decode the payload'). It also distinguishes this tool from siblings like jwt_create by specifying that signature verification is not performed.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context that this tool is for decoding without verification, implying it should be used when signature validation is not needed. However, it does not explicitly name alternative tools or provide comprehensive 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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosure. It adds the auto-detection behavior, which is useful, but it does not mention error handling, invalid input behavior, or the exact output format. The description partly overlaps with the schema's direction enum default.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence, front-loaded with the primary purpose, and contains no filler or redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple conversion tool with full schema coverage, the description adequately covers the primary use case and auto-detection. It is missing edge-case behavior or return format details, but these are largely implied by the tool's purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all three parameters (input, indent, direction) with descriptions, so the baseline is 3. The description's mention of the direction param adds no new semantic detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool converts between YAML and JSON, with a specific verb and resource pair. This distinguishes it from sibling tools like csv_json and json_format.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on how to use the tool, mentioning auto-detection and the direction parameter for explicit control. It does not explicitly list alternatives, but the guidance is sufficient for a straightforward conversion tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 explicitly indicates this is a read-only info operation, lists exactly what information is returned, and notes that it processes each character in the input. It does not discuss error handling or rate limits, but for a simple info tool, this is adequate and adds 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose and output. The leading '[PRO — 3 trial uses left]' is extraneous to the tool's function but does not significantly detract from clarity, meriting a 4.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 covers all relevant aspects: what the tool does, what information it returns, and that it operates per character. The input length is documented in the schema, and there are no undocumented side effects, making it sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides a complete description of the single 'text' parameter, including its type and length constraint (1-20 chars). The description does not add any additional semantic details about the parameter itself, so the baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Get' and clearly identifies the resource as 'Unicode character info' with a defined scope ('for each character in the input'). It enumerates the specific data fields (codepoint, name category, UTF-8 bytes, HTML entity), which distinguishes it from any sibling tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: whenever a user needs Unicode character details. It does not explicitly name alternatives or exclusions, but the sibling tools (e.g., base64, hash, uuid) have no functional overlap, making the intended usage unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must communicate the tool's side-effect profile. 'Convert' implies a pure, non-destructive calculation rather than a filesystem chmod operation, and the bidirectional example clarifies the transformation. However, it does not address behavior for invalid or ambiguous inputs (e.g. 'u+x' or partial modes).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single concise sentence with a helpful example, but it is prefixed by '[PRO — 3 trial uses left]', which is unrelated to the tool's semantics. Apart from that small bit of noise, the structure is efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter pure conversion utility, the combination of description and schema fully specifies what the agent needs for invocation: the accepted input format(s) and the conversion action. The output is inferred from the bidirectional arrow; no output schema exists, but the result is obvious. Edge cases like special mode bits are not covered, but they are unlikely to be required for normal selection.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already documents the single 'permission' parameter with 100% coverage, so the description adds only the bidirectional conversion example and Unix context. This is a small increment over the schema's 'Numeric ... or symbolic ...' explanation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Convert') with a clear resource ('numeric and symbolic Unix file permissions') and a concrete bidirectional example ('755 ↔ rwxr-xr-x'). It unambiguously identifies the tool's function and differentiates it from sibling utility tools like number_base or color_convert.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The statement 'Convert between numeric and symbolic Unix file permissions' establishes a clear use case: whenever a user needs to translate between these two representation formats. It does not explicitly name alternatives or exclusions, but the tool's unique function among the siblings makes this sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It clearly states the informational nature of the tool (parse/analyze and show properties) and even includes a usage limit note ('[PRO — 3 trial uses left]'), which is an additional behavioral disclosure. It does not explicitly confirm it is read-only, but this is strongly implied.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, information-dense sentence. The PRO trial note is extra context but does not bloat the description. Every phrase contributes to understanding the tool's function and constraints.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
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 no output schema, the description lists the key computed properties (type, class, private/public/loopback/link-local) which gives the agent a clear picture of expected results. It does not specify response format, but that is acceptable given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides full coverage (100%) with a type and example for the 'ip' parameter. The description adds context about the analysis performed (type, class, etc.) without changing parameter semantics. This meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Parse and analyze') with a clear resource ('an IP address') and enumerates distinct output properties (type, class, private/public/loopback/link-local). This makes it clearly distinguishable from sibling tools like cidr.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description makes the tool's purpose obvious and implies when to use it (whenever IP address analysis is needed). However, it does not explicitly mention alternatives or when not to use it, though no sibling tool clearly competes with this function.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of transparency. It discloses key behavioral traits: IDs are compact, URL-safe, and customizable in length and alphabet. It does not detail randomness source or potential side effects, but for a simple generation tool this 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The core description is a single concise sentence that efficiently conveys purpose. However, the promotional prefix '[PRO — 3 trial uses left]' is extraneous and not tool-related, slightly detracting from structural cleanliness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with full schema documentation, and the description adequately explains what it does and its customization options. Though the 'count' parameter is not mentioned in the text, the schema covers it, making the overall description complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All three parameters have descriptions in the schema, and the description reinforces length and alphabet customization. Since the schema already covers parameter meaning at 100%, the description adds marginal semantic value beyond that.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate compact, URL-safe unique IDs' with a specific verb and resource, and differentiates from the sibling 'uuid' tool by noting 'like UUID but shorter'. This makes the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrasing 'like UUID but shorter' provides a clear use case comparison, implying when to use this over a standard UUID generator. However, it does not explicitly mention alternatives or state when not to use the tool, so it falls short of full guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
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 algorithm, output format (hex-encoded salt+hash), and intended purpose. It does not mention the one-way nature or computational cost, but these are reasonably implied by password hashing context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded, with two sentences containing only relevant information. The PRO trial note is extra but does not dilute clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers core functionality, output format, and use case. It would benefit from clarifying the exact concatenation format of salt and hash, but for a simple tool with fully described parameters, it is mostly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with clear descriptions for both password and salt. The description adds the output format but does not provide additional parameter semantics beyond what the schema already documents, 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool hashes a password using Node.js scrypt (RFC 7914) and returns hex-encoded salt + hash. This specific verb+resource distinguishes it from generic hash tools and other cryptographic siblings like hmac.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context by stating 'for secure password storage', indicating when to use this tool. However, it does not explicitly mention alternatives or exclusions, though the context effectively implies its intended use case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description's 'look up' implies a read-only, non-destructive operation. It adds valuable context by revealing the output categories (meaning, category, usage). For such a simple lookup tool, no further behavioral disclosure is necessary.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no redundant words. Every phrase ('meaning', 'category', 'common usage') adds value and collectively communicates the tool's functionality efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one well-documented parameter and no output schema, the description is sufficient. It states the purpose and the kind of result the user can expect, making it complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents the single 'code' parameter with an example, achieving 100% coverage. The tool description does not add any additional parameter-level detail 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'look up' with the resource 'HTTP status code' and explicitly lists the provided information (meaning, category, common usage). This clearly identifies the tool's function and distinguishes it from all sibling tools, which handle unrelated data types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies the tool is for retrieving details about HTTP status codes, which is a distinct use case among siblings. However, it does not explicitly state when to prefer this tool or mention any exclusions, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the signing algorithm (HS256) and practical use cases. It does not mention error conditions or the output format, but the core behavior is clear and no contradictions exist with 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence (excluding the PRO trial notice) that front-loads the action. Every word contributes value, with no redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with fully documented parameters and no output schema, the description is complete. It explains what the tool does, the algorithm, and when to use it, covering all necessary context for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
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 mentions 'signed with HS256' but does not add parameter-specific details beyond what the schema already provides. Thus, it scores at the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Create a JWT token signed with HS256' which is a specific verb+resource, clearly distinguishing it from jwt_decode. It also lists concrete use cases, making the tool's purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context: 'Useful for testing APIs, mocking auth, and generating test tokens.' It does not explicitly name alternatives or state when not to use it, but the use cases are sufficient for an agent to select this tool appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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