ToolAPI

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, but the description fails to disclose behavioral traits like error handling on invalid input, performance, or side effects. It only states the basic operation, which is insufficient 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (one sentence) but lacks structure. While it is not verbose, it omits important details that could be included without much length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is too minimal. It does not cover error cases, input validation, or return format, making it incomplete for a simple decode tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage for the 'text' parameter, and the description does not add any meaning to it. The parameter is simply named 'text' with no hint of expected format (e.g., a base64-encoded string).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (base64 decode) and the output encoding (UTF-8). It distinguishes from siblings like base64_encode and base64url_decode by specifying UTF-8 output, but could be clearer about input encoding assumptions.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool over alternatives such as base64url_decode. The description does not mention use cases or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description is too sparse; it doesn't disclose what happens with empty input, edge cases, or the return format.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

While the description is concise, it is under-specified and fails to provide necessary details, making it ineffective rather than efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with one parameter and no output schema or annotations, the description is far too minimal to be complete for correct selection and invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds no meaning beyond the input schema; with 0% schema description coverage, the parameter 'text' is not explained at all.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Base64-encode' and the resource 'UTF-8', which distinguishes it from siblings like base64_decode or base64url_encode.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives, or any context like typical use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description should disclose behaviors like error handling, input validation, or output format. It only states 'to UTF-8,' leaving out details such as padding handling or invalid input behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise: a single sentence that gets straight to the point with no wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool, the description is too minimal. It does not differentiate from sibling base64_decode, nor does it explain return value (no output schema). An agent needs more context to use it correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'text' has no description in the schema (0% coverage), and the tool description adds no additional meaning. The agent gets no hints about expected format, length constraints, or encoding requirements.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool decodes base64url to UTF-8, a specific verb+resource. It distinguishes from siblings like base64_decode and base64url_encode.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., base64_decode). The description does not explain the difference between base64url and standard base64 decoding.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 'no padding' and 'URL-safe' behavior, but does not mention potential edge cases (e.g., handling of non-UTF-8 input, output format) or error conditions. Adequate for a simple encoding tool but could be more thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the most critical information (encoding method, input encoding, and key characteristics). No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (one parameter, no output schema), the description is mostly complete. It covers the encoding specifics and input format. It could mention that the output is a string, but that is implied by the tool name. Missing details about error handling or empty input, but for a straightforward utility, this is acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage for the single 'text' parameter. The description adds that the input is UTF-8 encoded, which provides some context beyond the parameter name, but does not explain the parameter in detail (e.g., allowed types, maximum length, handling of special characters).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: base64url encoding with no padding and URL-safe characters, and specifies input encoding as UTF-8. This distinguishes it from siblings like base64_encode (standard base64) and base64url_decode (decoding).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for URL-safe encoding (by stating 'URL-safe') and notes the lack of padding, but does not explicitly state when to use this tool over alternatives like base64_encode or mention any prerequisites or limitations. There is no guidance on exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden but only states a one-way hash. It omits critical behavioral traits: computational cost, automatic salt generation, rounds parameter effect, output format (includes algorithm, cost, salt, hash).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (6 words), which lacks necessary detail. It is not verbose, but it sacrifices clarity and completeness for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, no annotations, and low complexity of the tool, the description is severely incomplete. It fails to describe output format, security implications, or relationship to bcrypt_verify.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must explain parameters. It only mentions 'password' implicitly; the 'rounds' parameter (cost factor) is completely ignored, leaving agents unaware of its existence or purpose.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action (Bcrypt-hash) and target (a password for storage). It distinguishes from siblings like bcrypt_verify and other hash tools, though it could more explicitly contrast with general hashes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use bcrypt_hash versus alternatives. It doesn't mention that bcrypt is specifically for passwords, slow, or that other hash tools are for speed-oriented scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, and the description fails to disclose behavioral traits. It does not state whether the tool has side effects, authentication requirements, or error conditions. A read-only verification tool should at least indicate it does not modify state.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

While extremely short (one sentence), the description sacrifices essential information for brevity. It omits parameter details, return value, and usage context, making it under-specified rather than concisely helpful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 2 required parameters, no output schema, and no parameter descriptions, the description is incomplete. It does not mention the return type (likely boolean) or any edge cases (e.g., invalid hash format). An agent cannot reliably use this tool based solely on the description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, and the tool description does not explain the parameters at all. It does not clarify the expected format of 'password' or 'hash', leaving the agent without necessary context for correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Verify password') and the resource ('against bcrypt hash'), making the tool's purpose immediately obvious. It distinguishes itself from sibling tools like bcrypt_hash (which creates hashes) and hash_compare (generic comparison).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No usage guidance is provided. The description does not specify when to use this tool over alternatives, e.g., when to use bcrypt_verify vs. bcrypt_hash or hash_compare. The agent is left to infer from the name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description must carry the full burden. It does not state behavioral traits such as error handling, output format, or what happens with invalid input. The description is too brief to be transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no wasted words. While it could benefit from more detail, it is appropriately concise for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the one-parameter schema and lack of output schema, the description is too vague. It does not explain what 'version sections' are, how the output is structured, or any edge cases. More context is needed for an agent to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description should compensate. It only mentions 'text' as input but adds no details about expected format, constraints, or examples. The parameter name itself is clear but insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Parse') and the resource ('Keep-a-Changelog style markdown') and the outcome ('into version sections'). It is specific and distinguishes from sibling tools like markdown_to_html or other parse tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, context, or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It lists three types of info but does not specify if those are exhaustive, what the return format is, or how edge cases (e.g., invalid CIDR) are handled. The description lacks sufficient behavioral detail for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that front-loads the verb and resource. Every word contributes meaning, with no superfluous information. It is appropriately sized for a simple tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity (one parameter, no output schema), the description covers the basic input and expected output types but does not describe the return format or structure. An agent might need more context on whether the output is a string or object with specific fields. Completeness is adequate but not thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides a good example for the cidr parameter. The description adds value by specifying IPv4/IPv6 support and the types of information calculated, which goes beyond the schema's example. This enhancement helps the agent understand the tool's capabilities better.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates network information from CIDR notation, specifying IPv4/IPv6 and three types of output (hosts, broadcast, private). The verb 'Calculate' is specific and the resource is well-defined, distinguishing it from sibling tools like cidr_contains.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like cidr_contains. The purpose implies usage for network calculation, but there is no mention of when not to use it or prerequisites. The differentiation from cidr_contains is implicit but not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention return type, validation behavior (e.g., case sensitivity, IP version support), error handling, or any side effects. For a simple containment check, the behavior is mostly inferred, but the description lacks explicit detail.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence with no unnecessary words. It is front-loaded and efficiently conveys the core purpose. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of annotations, output schema, and parameter descriptions, the description is insufficient. It does not explain the return value shape (likely boolean), how invalid inputs are handled, or support for edge cases. For a tool with no supplementary metadata, more context is needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must compensate. It identifies the semantic roles of the two parameters ('IP' and 'CIDR range'), but does not specify expected formats (e.g., IPv4 vs IPv6, proper CIDR notation like '192.168.1.0/24') or constraints. The added meaning is minimal beyond what the parameter names imply.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: checking if an IP address falls within a CIDR range. It uses a specific verb ('Check') and resource ('IP address...CIDR range'), and it distinguishes itself from the sibling tool 'cidr_calc' which likely performs CIDR calculations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives, such as 'cidr_calc'. It does not mention any preconditions, typical use cases, or exclusions. The usage context is entirely implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It explains the operation but not details like whether it returns all blocks or just the first, or how it handles malformed input. Adequate for a simple tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that conveys everything needed: the action, resource, and what is extracted. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter tool with no output schema, the description is sufficient. It explains what input is expected and what is extracted. Slightly more detail on output structure would be ideal but not critical.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description adds essential context: the 'text' parameter should be markdown content. It clarifies the input format, going beyond the bare type declaration.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (extract) and the resource (fenced code blocks from markdown) and distinguishes it from sibling tools like markdown_toc or markdown_link_extract.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied usage: use when you need to extract code blocks from markdown. No explicit guidance on when not to use or alternatives, but the purpose is clear enough for typical scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. Description does not disclose behavioral traits (e.g., non-destructive, return format). For a simple calculation, transparency is adequate but limited.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences, front-loaded with purpose. No fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, and description fails to explain return value (ratio, pass/fail) or handle edge cases (invalid colors). With many siblings but no direct contrast tool, more detail needed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage 0%, no parameter descriptions. Description says 'hex colors' adding format hint, but does not specify exact format (e.g., with/without #) or that fg=foreground, bg=background.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it calculates WCAG contrast ratio between two hex colors, mentioning AA/AAA levels. Distinguishes from sibling color_convert which handles conversion.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides usage context 'When: WCAG contrast ratio for UI color pairs.' Implies when to use, but does not explicitly mention when not to use or alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided; description is minimal and does not disclose potential error handling, input validation, or output format assumptions. However, for a straightforward conversion tool, the lack of behavioral detail is acceptable but not exemplary.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, perfectly concise. No unnecessary words, front-loaded with action and resource.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and lack of output schema, the description is mostly complete. It could mention that the default 'to_format' is 'all', but this is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only 'color' has a description). The description adds no extra meaning for the 'to_format' parameter, which has an enum but no explanation of its purpose. The description should clarify that 'to_format' controls output format and that 'all' returns conversions to all formats.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'Convert color between hex, rgb(), and hsl()', giving a specific verb and resource. It clearly distinguishes from sibling tools, 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.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives, but since there are no sibling color tools, the context implies it is the correct choice for color format conversion. No exclusions or when-not-to-use mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description clarifies that the tool performs validation and flags issues, suggesting a non-destructive read operation; however, it lacks details about output format or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, clear sentence that efficiently conveys the tool's purpose and key behaviors.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description is largely complete; however, it could mention the return format (e.g., list of issues) for full clarity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and only one parameter exists; the description implies 'text' is the YAML content but adds minimal meaning beyond the schema's type definition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool validates docker-compose YAML and specifically flags privileged/host-network/secret env issues, making it distinct from siblings like dockerfile_lint.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for docker-compose YAML validation but provides no explicit guidance on when to use versus alternatives, nor 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, and the description fails to disclose behavioral traits such as error handling, case sensitivity, or handling of malformed headers. It is minimal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, concise and front-loaded. No extraneous words, though it could benefit from additional details without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple one-param nature and absence of output schema, the description mentions output components (mime/charset/params), which is adequate. However, it lacks differentiation from sibling parse tools and does not specify return format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The parameter 'header' has no schema description (0% coverage). The description adds that it is a Content-Type header string, providing basic context beyond the raw 'string' type, but no format details or examples.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Parse' and the resource 'Content-Type header', specifying the output components 'mime/charset/params'. This distinguishes it from other parsing tools among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives, nor any prerequisites or exclusions. It does not mention 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry full weight. It only says 'Lint' but doesn't disclose what the output looks like, whether it returns a boolean or detailed errors, or any side effects. For a validation tool, this is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

At 10 words, the description is very concise and gets the point across immediately. It avoids fluff and is front-loaded. However, it may be too minimal, missing key details that could fit without harming conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one param, no output schema), the description is still incomplete. It fails to describe the return value, error handling, or any behavioral details. The agent would need to invoke it blindly or rely on schema which provides no description.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and description adds no extra meaning beyond the parameter name 'message'. It does not explain format expectations, allowed characters, or provide examples. The description only repeats the purpose, not the parameter details.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: to lint Conventional Commits messages. It gives examples of commit types (feat/fix/chore) which helps the agent understand the scope. It distinguishes itself from siblings like base64_decode or html_to_markdown by being uniquely about commit message validation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, when not to use it, or provide comparison with sibling tools like semantic versioning or changelog parsers. An agent would have no context on appropriate use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 states the basic function but does not disclose potential errors, input format expectations (e.g., the header string must be a valid Cookie header), or any side effects. This is insufficient for contexts where the agent needs to anticipate failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short (two sentences, one of which is redundant) and wastes no words. However, the redundancy ('Parse Cookie request header... When: Parse Cookie request headers') suggests an opportunity to replace the second sentence with more informative content. Still, it remains concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (1 parameter, no output schema), the description provides a basic understanding: it returns a name/value map. However, it does not specify the structure of that map (e.g., object with string keys and values) or mention edge cases like malformed headers. This is adequate but not complete for all usage scenarios.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 1 parameter ('header') with 0% description coverage. The description references 'Cookie request header' but does not add semantic details like expected format (semicolon-separated key=value pairs) or constraints. The schema does not provide descriptions either, so the agent lacks guidance on how to construct valid inputs.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: parse Cookie request headers into a name/value map. The verb 'Parse' and the resource 'Cookie request header' are specific, and it distinguishes itself from sibling parse tools like content_type_parse or url_parse by focusing on Cookie headers.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives a brief 'When: Parse Cookie request headers' which implies appropriate usage but does not specify when not to use it or mention alternative tools. There is no explicit guidance on preconditions or postconditions, leaving the agent with only implied context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It mentions checking for unsafe combinations but does not define 'unsafe', the output format, or any side effects. The agent lacks crucial context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that front-loads the purpose. While brief, it conveys the core functionality without extraneous detail.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, no annotations, and 3 parameters with 0% schema description coverage, the description is insufficient. It does not explain output, error conditions, or what constitutes an unsafe combination, leaving the agent guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description hints at 'Allow-Origin vs credentials' correlating with parameters allow_origin and allow_credentials, but does not explain their meaning, constraints, or interaction. The parameter 'origin' is not mentioned.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: checking CORS Allow-Origin vs credentials for unsafe combinations. It is specific and distinguishes from numerous sibling utilities that perform encoding, parsing, hashing, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives. However, the sibling tools are unrelated to security checks, so context is implied but not elaborated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, and the description does not disclose output format, input constraints, or any behavioral traits (e.g., whether it handles extended cron syntax, timezone handling). The tool appears read-only but lacks transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no unnecessary words, but it is too terse and omits essential details about input format and output structure.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool with no output schema, the description should define input format and output expectations. It mentions 'EN + ZH' but does not specify if the output is a single string containing both languages or separate fields. Incomplete for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'expr' is of type string with no schema description (0% coverage). The description does not clarify expected cron expression format (e.g., 5-field vs 6-field) or provide examples, leaving ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: providing a human-readable natural language description of a cron expression in English and Chinese. It distinguishes itself from sibling tools like cron_parse and cron_validate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives such as cron_parse for components or cron_validate for syntax checking. The agent has no context for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It does not disclose any behavioral traits such as read-only nature, error handling, side effects, or response format (e.g., returns boolean).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the core purpose. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, the description provides the essential purpose but lacks details like return type, error behavior, and parameter constraints. It is minimally complete but could be improved.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 33% (only 'at_time' has a description), and the tool description adds no further parameter meaning. 'expr' and 'timezone' lack any explanation beyond their types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool checks if a cron expression matches a specific datetime, which is a distinct purpose from sibling tools like 'cron_validate' or 'cron_next_runs'. The verb 'check if' and resource are clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives, no prerequisites, and no context for appropriate use cases. The description is a single sentence without any usage direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description bears full responsibility for disclosing behavioral traits. It states only that the tool previews execution times, but omits essential information such as whether the operation is read-only (non-destructive), any authentication or rate-limiting constraints, and what happens with invalid cron expressions. This is insufficient for an agent to safely infer behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with no superfluous words. It is appropriately sized for its purpose. However, it could be slightly expanded to include critical parameter or behavioral details without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given that the tool has 4 parameters, no output schema, and no annotations, the description is incomplete. It does not describe the return format (e.g., list of timestamps), error handling for invalid expressions, timezone behavior, or any edge cases. This lack of completeness could lead to incorrect tool usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is only 25% (one out of four parameters described). The description adds value by clarifying that 'expr' should be a '5-field cron expression', but it does not explain the semantics of 'count', 'timezone', or 'from_time' beyond what the schema already provides. For a tool with low schema coverage, the description should compensate more.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the action ('Preview') and the resource ('next N execution times for a 5-field cron expression'). It is distinct from sibling tools like cron_describe or cron_validate, which focus on describing or validating cron expressions rather than generating future execution times.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives (e.g., cron_describe, cron_matches). It does not mention any prerequisites, context, or exclusion criteria. An agent would need to infer usage context from the tool name alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full burden for behavioral disclosure, but it only states the basic function. It does not mention error handling, input format requirements (e.g., 5 fields), or whether invalid expressions cause errors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (one short sentence) and front-loaded with essential information. It could be slightly expanded for clarity, but it is not verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should hint at the return format. Saying 'named fields' is vague; the agent might expect an object with keys like 'minute', 'hour', etc., but this is not confirmed. The description is incomplete for an agent to reliably invoke and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. However, it only says '5-field cron' without specifying the exact format of the 'expr' parameter (e.g., space-separated, no comments). This is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Parse', the resource '5-field cron', and the output 'named fields (minute hour dom month dow)'. It distinguishes from sibling tools like cron_validate, cron_describe, etc., which have different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies the tool is for decomposing a cron expression into fields. While it doesn't explicitly state when to use vs. alternatives, the context of sibling tools makes the purpose clear. A minor improvement would be to mention that it does not validate or describe.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It only mentions validation of syntax and ranges, omitting details like whether it returns a boolean or error messages, or any side effects. Minimal transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single, concise sentence with no filler. Efficiently communicates the core function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should clarify return behavior (e.g., boolean, error array). It also fails to explain how this differs from cron_validate, leaving the tool's role unclear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds 'cron field syntax and value ranges (minute 0-59, hour 0-23, etc.)' over the schema, which only lists 'expr' as a string. However, it does not specify the expected cron format (e.g., 5 or 6 fields) or provide full range details, leaving ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it validates cron field syntax and value ranges, which aligns with the tool name. However, it does not differentiate from the sibling cron_validate, so the purpose is somewhat ambiguous regarding the 'semantic' aspect.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives like cron_validate or cron_parse. The description lacks context for appropriate usage scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It only mentions the check but does not state the return value (e.g., boolean), error behavior, or any side effects. This is insufficient for an agent to understand the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, no wasted words. It is appropriately front-loaded. However, the conciseness comes at the cost of completeness, so it is not a model of efficient information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the low complexity (1 parameter, no output schema) and many sibling tools, the description is incomplete. It does not explain return values, error handling, or validation rules beyond field count. This leaves gaps for an agent using the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. The description implies the 'expr' parameter is a cron string, which adds slight meaning but does not specify expected format, allowed characters, or any constraints beyond five fields. More detail is needed.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the verb 'check' and the resource 'cron string', making it clear that the tool validates a cron expression. It distinguishes from siblings like 'cron_parse' or 'cron_semantic_validate' by specifying the focus on field count. However, it could further clarify what constitutes a valid field.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool over alternatives such as cron_parse or cron_semantic_validate. There is no mention of contexts or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description must disclose behavior. It mentions 'semantic validate' but does not explain what semantic checks are performed, return format, error handling, or side effects. The minimal description leaves the agent uncertain about the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that directly states the tool's purpose. It is front-loaded and contains no filler. However, it could be slightly expanded without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a batch validation tool with no output schema and sibling tools that perform related tasks, the description is incomplete. It does not explain what 'semantic validate' entails, how results are returned, or how it differs from cron_validate or cron_semantic_validate. The agent lacks critical context for proper usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'expressions' is an array of strings with max 30 items. Schema coverage is 0% (no parameter descriptions in schema). The description adds no additional meaning, such as expected format of each expression (e.g., 'minute hour day month weekday'). The agent must infer from the tool name, which is insufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it performs batch semantic validation of 5-field cron expressions. The verb 'validate' and resource 'cron expressions' are specific, and it distinguishes itself from siblings like 'cron_validate' (likely single) and 'cron_parse' (syntactic vs semantic).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The name 'batch' implies use for multiple expressions, but no explicit guidance on when to use vs alternatives like cron_validate or cron_semantic_validate. The description lacks exclusions or context for choosing this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It states parsing and flagging unsafe directives, which implies a read-only analysis. However, it does not explain what 'flag' means or any side effects, so transparency is adequate but not thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two concise sentences with no redundant information. It is front-loaded with the main action and includes the key differentiator of flagging unsafe directives.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description covers the input and the primary action. It does not describe the output format but given the tool's simplicity, it is sufficiently complete for an agent to infer the return value.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must clarify the parameter. The description specifies the header parameter as the 'Content-Security-Policy header', adding meaning beyond the bare schema. This helps the agent understand the expected input, though format details are omitted.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Parse' and the resource 'Content-Security-Policy header', and adds the specific action 'flag unsafe directives'. This distinguishes it from sibling tools like http_headers_parse and content_type_parse.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (for CSP header analysis) but provides no explicit guidance on when not to use or alternatives. No exclusions or comparisons to sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must explain behavior fully. It fails to specify delimiter, header handling, quoting, or error behavior. The tool's inner workings are opaque.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences long and front-loaded with the main action. The second sentence is redundant but not harmful. It is reasonably concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (CSV parsing with default assumptions), the description is incomplete. It does not specify the delimiter, presence of headers, or escape characters, leaving the agent to guess or experiment.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The only parameter 'text' is not described beyond its name. Schema description coverage is 0%, and the description adds no context about the expected format (e.g., that it should be a CSV string).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Convert CSV text to JSON array of row objects', specifying the verb and resource. It distinguishes from sibling tools like csv_validate and json_to_csv, though no explicit differentiation is provided.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'When: Convert CSV rows → JSON array of objects', indicating the use case, but lacks guidance on when not to use or mention of alternatives. Usage is implied rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It only mentions validation of structure, implying read-only and non-destructive actions, but does not explicitly state this or mention other behavioral traits like error handling or resource requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise, consisting of two short sentences. The first sentence is front-loaded with the core action and scope, and the second sentence adds usage context. No unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has three parameters (one required) and no output schema, the description should cover what the tool returns, how errors are reported, and details about each parameter. It lacks this information, making it incomplete for an agent to use effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate by explaining parameters like 'text', 'delimiter', and 'has_header'. The description only mentions 'header' in the context of validation, not as a parameter. No parameter semantics are added beyond the schema property names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool validates CSV structure for consistent column counts and header. It clearly indicates 'Validate CSV structure — consistent column counts / header.' This is specific to CSV row structure, but does not differentiate from sibling tools like csv_to_json, which also deals with CSV structure.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'When: Check CSV column consistency before import,' which provides a clear use case. However, it gives no guidance on when not to use or alternatives, leaving the agent to infer from context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden for behavioral disclosure. It mentions using the latest ECB rates but does not disclose update frequency, precision, rounding, error handling for unsupported currencies, or the output format. The behavior is partially clear (a simple conversion) but important traits are omitted.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one sentence with 8 words, making it very concise. It front-loads the verb and resource. While efficient, it could include a bit more useful detail (like currency code format) without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the related siblings (currency_rates, currency_list), the description correctly indicates this tool performs conversion. However, with no output schema, the return format is not described. For a simple tool, the description is minimally adequate but lacks completeness in describing the output.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must add meaning. It mentions 'amount', 'from_currency', and 'to_currency' but does not specify that currencies should be 3-letter ISO codes. The description adds no format, constraints, or examples beyond the schema's basic type information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Convert' and the resource 'amount between currencies' with a specific data source 'latest ECB rates'. This distinguishes it from sibling tools like 'currency_rates' (which likely fetches rates without conversion) and 'currency_list' (which lists supported currencies).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for converting amounts between currencies but provides no explicit guidance on when to use this tool vs alternatives. It fails to mention when not to use it, such as for just fetching rates (currency_rates) or listing currencies (currency_list). No exclusions or alternative suggestions are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 data source and authorization requirement (no API key), but does not mention any other behavioral traits like return format, performance characteristics, or potential limitations (e.g., rate limits, static vs dynamic list). Adequate for a simple list tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that is front-loaded with the primary purpose. Every word adds value: 'List', 'supported fiat currencies', 'Frankfurter/ECB', 'no API key'. No unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters, no output schema, and a simple function (listing currencies), the description is complete. It tells the agent what the tool does, what data it retrieves, and any access requirements (no API key). No further information is needed for correct invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has no parameters, so schema description coverage is 100%. The description adds context beyond the schema by specifying the type of currencies (fiat) and the source (Frankfurter/ECB), which helps the agent understand the scope. Baseline is 4 for zero-parameter tools with added context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List supported fiat currencies' and distinguishes it by specifying the data source (Frankfurter/ECB) and the no-API-key requirement. This differentiates it from sibling tools like currency_convert or currency_rates.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for listing fiat currencies but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives among the many sibling tools. The context is clear but lacks exclusions or comparisons.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries behavioral disclosure. It reveals data source and absence of API key, but misses details like update frequency, response structure, or error handling, offering moderate transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with key information (data source, authentication) front-loaded; no unnecessary words, making it highly concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given two parameters and no output schema, the description covers purpose and source but lacks details on response format, rate update frequency, or error conditions, resulting in incomplete context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only symbols has description). The description adds source context but does not explain the base parameter beyond its default, leaving semantic gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool returns latest exchange rates, specifies data source (Frankfurter ECB) and authentication requirement (no API key), distinguishing it from siblings like currency_convert and currency_list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Description implies usage for fetching rates but does not explicitly state when to use this tool versus alternatives such as currency_convert or currency_list, nor provide exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral transparency. It discloses basic behavior (parsing input to UTC ISO and Unix) but lacks detail on error handling, input validation (e.g., handling of malformed strings, timezone assumptions), and whether the Unix timestamp is expected in seconds or milliseconds. The description is too brief to fully inform an agent about edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with zero superfluous words, immediately stating the action, input types, and output. It is efficiently front-loaded and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description provides the essential input-output mapping but omits output structure details (e.g., whether the result is an object with keys like 'utcIso' and 'unix'). Given no output schema, the agent would need to infer the format, making the description incomplete but minimally adequate.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must compensate. It adds meaning by specifying that 'value' can be either a Unix timestamp or ISO-8601 string, which is not evident from the schema alone. However, it does not clarify the expected format for Unix timestamps (e.g., seconds vs. milliseconds) or permissible ISO-8601 variations, limiting the added value.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: parsing either a Unix timestamp or ISO-8601 string and converting it to both UTC ISO and Unix formats. It uses specific verbs and resources ('Parse', 'unix timestamp', 'ISO-8601', 'UTC ISO', 'unix'), distinguishing it from siblings like 'time_convert' or 'duration_parse'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a datetime string needs parsing, but provides no explicit guidance on when to use this tool versus others, nor does it mention any prerequisites, limitations, or exclusion criteria. The usage context is implied rather than explicitly stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It mentions 'best-effort', hinting at uncertainty, but lacks details on behavior for invalid input, edge cases, or what happens if extraction fails. No mention of side effects or permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, but the second is essentially repetition of the first. The description could be more concise without losing clarity. Front-loads purpose but wastes space on redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, so description should explain return format or what the extracted data looks like. It does not. Combined with 0% parameter coverage, the description leaves significant gaps for a tool with 2 parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, meaning description does not mention parameters at all. It does not explain what 'text' represents or how 'ecosystem' influences extraction. Description fails to add any meaning beyond the raw schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it extracts name@version from dependency files like requirements/lockfile/go.mod/Cargo. It distinguishes itself from siblings like requirements_audit by focusing specifically on extraction. However, the second sentence is somewhat redundant.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs. alternatives. The description says 'When: Extract name@version...' which is just restating purpose, not providing usage context or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and description only lists record types without disclosing behaviors like network dependence, latency, caching, or error conditions. Minimal transparency beyond the basic function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded, no redundancy. Efficient and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Tool is simple with two params. Description covers core function and supported record types, but lacks output format details and error scenarios. Adequate but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description adds no parameter-level details beyond the schema's enum for record_type. It does not explain domain format or default behavior for invalid input.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it performs DNS lookups for a domain, listing specific record types (A, AAAA, MX, TXT, NS, CNAME, SOA). This distinguishes it from siblings like reverse_dns or whois_lookup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives such as reverse_dns or whois_lookup. The description does not state prerequisites or typical use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description must fully disclose behavior. It only mentions 'lint' and example issues but does not describe output format, side effects, or potential errors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no unnecessary words. It is concise and directly communicates the tool's purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of annotations and output schema, the description is insufficient. It does not explain what the tool returns or how results are presented, which is critical for a linter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter 'text' with no description. The description implies 'text' is the Dockerfile content but does not explicitly state this, leaving ambiguity about format and constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lints Dockerfiles for common security and style issues with examples. It distinguishes itself from sibling linting tools by specifying the resource type (Dockerfile).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, context, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions 'best-effort eTLD', which is a valuable caveat about potential inaccuracies in TLD extraction. However, it lacks information about error handling or return format, which would further enhance transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exceptionally concise, consisting of just two sentences. The first sentence states the purpose, and the second provides a usage guideline. Every word earns its place, with no redundancy or unnecessary information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema, no nested objects), the description is fairly complete. It covers the core functionality and adds a usage guideline. However, it does not explicitly mention the return structure, which might be inferred but could be clarified. Overall, it provides sufficient context for an agent to understand when and how to use it.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It adds meaning by specifying that the parameter is a domain to parse, but it does not elaborate on the expected format (e.g., with or without protocol, port, path). The parameter name 'domain' is self-explanatory, and the description confirms its role, but more detail would be beneficial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: parsing a domain into its components (labels, TLD, registrable domain, subdomain). The verb 'Parse' and resource 'domain' are specific, and the tool is well-distinguished from sibling parse tools by focusing solely on domain parsing.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes a 'When:' clause that explicitly indicates the appropriate use case: splitting a domain into its structural parts. While it provides clear context, it does not mention when not to use this tool or suggest alternative tools, which would be beneficial given the large number of sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description bears the full burden. It specifies input format and output unit (seconds) but does not disclose behavior on invalid input, error handling, or edge cases like negative durations. This is adequate but incomplete for full transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two short sentences. The first sentence states the action and input/output, and the second reinforces usage. No unnecessary words, and it front-loads the key information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool with no output schema, the description is fairly complete: it explains input format and output unit. However, it does not explicitly state the output type (e.g., integer/float) or behavior on failure. Minor gaps but still good coverage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must explain the sole parameter. It does so effectively, detailing that 'value' accepts ISO-8601 or human-readable duration strings (e.g., '1h30m', '90s'), adding essential meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool parses duration strings (ISO-8601 and human-readable like '1h30m' or '90s') into seconds. This distinctly separates it from sibling tools that parse other formats (e.g., cron, JSON, YAML).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'When: Parse ISO-8601 / human durations to seconds,' providing explicit context for when to use it. It could be stronger by stating when not to use it or mentioning alternatives, but the guidance is clear enough for a utility tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are set, so the description carries the full burden. It does not disclose what happens on invalid input (e.g., error messages, return value), nor does it state whether the tool is read-only or has side effects. The behavioral model is opaque.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-formed sentence that directly states the tool's purpose with no superfluous words. It is appropriately concise for a simple validation tool.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and annotations, and a single parameter with no description, the description is insufficient. It omits critical details like return format, error behavior, and what 'common keys' means. For validation, return behavior is essential.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the parameter 'text' (type string) is undescribed. The description does not explain what 'text' should contain (e.g., file content or path). The tool's purpose implies it's content, but no clarification is given.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Validate .editorconfig syntax and common keys' has a specific verb ('Validate'), a clear resource ('.editorconfig'), and scope ('syntax and common keys'). It effectively distinguishes this tool from the many siblings in the list, none of which are similar.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives (none obvious) or any conditions. The description is purely declarative, lacking any usage context or recommendations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full responsibility. It states 'Validate' and 'Syntax-check,' implying a non-destructive read operation. This is adequate for a simple tool but does not disclose details like dependencies, rate limits, or error handling beyond the basic operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exceptionally concise: two short sentences, no redundant words, and front-loaded with the core action. Every word serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple validation tool with one parameter and no output schema, the description covers the essential purpose and usage context. However, it omits details about return values (e.g., boolean or corrected email), which would enhance completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description adds crucial meaning: it clarifies the 'email' parameter is a single email address to be syntax-checked. This compensates for the schema's lack of description, though it could explicitly state allowed formats or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Validate email address format' and 'Syntax-check a single email address,' indicating a specific verb and resource. It distinguishes from generic validation tools but does not explicitly differentiate from related siblings like 'extract_emails' or 'identifier_validate.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'When:' phrase specifies 'Syntax-check a single email address,' implying a singular use case. However, it lacks guidance on when not to use this tool, alternatives, or batch processing scenarios, leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 describes the diff operation without mentioning safety, side effects, or return behavior, which is insufficient for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two sentences) and front-loaded, with no fluff. However, it could include more detail without significant length increase.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (two string parameters, no output schema), the description covers the basic purpose and usage scenario. It lacks details on output format or case sensitivity, which would be helpful for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description only implies that parameters 'a' and 'b' are .env files. It does not specify whether they are file paths or contents, nor any format expectations, adding minimal meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Diff two .env files' and lists the output categories (only_in_a, only_in_b, changed values). It distinguishes itself from sibling tools like env_parse and env_required_check.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'When: Diff two .env files for missing/changed keys,' which provides a clear usage scenario. It does not explicitly mention when not to use or alternatives, but the context is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, and the description does not disclose behavioral traits such as handling of comments, quoting, or special characters. For a parsing tool, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one sentence with no unnecessary words. It front-loads the purpose. However, it could include brief behavioral notes without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has one simple parameter and no output schema, so the description is reasonably complete for basic understanding. But it lacks details on output format (e.g., nested keys, type coercion) and edge cases, which would help in complex usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'text' (string) is described by the tool's purpose as '... dotenv text', which adds some meaning beyond the schema type. However, no details on expected format, syntax, or edge cases are provided. With 0% schema description coverage, the description partially compensates but could be more explicit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states what the tool does: parse .env/dotenv text into key-value variables. It uses specific verb 'parse' and resource 'env/dotenv text', which distinguishes it from sibling tools that do encoding, decoding, or other transformations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, expected input formats, or exclusions. The description simply states the function without usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavior. It only states the check criteria but does not indicate return type, output format (boolean, list, error), or side effects. This is insufficient transparency for a mutation-like check tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, front-loaded with action and resource, no filler. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple two-param tool with no nested objects or output schema, the description covers the main purpose. However, it lacks description of return value (boolean? list of missing keys?) and error conditions, which would improve completeness. Adequate but with gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description adds minimal meaning: it confirms 'text' is .env content and 'required' is keys list, and mentions non-empty values. It does not specify the expected format of 'text' (e.g., KEY=value lines) or that 'required' is an array of strings beyond schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'Check' and resource '.env text', specifying it checks for required keys with non-empty values. It distinguishes from siblings like env_parse and env_diff which have different purposes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied by the purpose: verify .env file completeness. However, no explicit alternatives or when-not-to-use guidance is provided. The context of sibling tools (e.g., env_parse, env_diff) suggests distinct use cases but not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden. It does not disclose behavioral traits such as duplicate handling, validation status, or return format. The description adds no value beyond the basic extraction claim.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise with two brief clauses. It is front-loaded and wastes no words. However, it is arguably too short, sacrificing completeness for brevity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no output schema and one parameter, the description should explain return behavior, such as format or handling of no matches. It does not, leaving important gaps for a utility tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must compensate. It only reiterates that the input is text, adding no additional meaning about expected format or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool extracts email addresses from text, specifying the resource (email addresses) and verb (extract). However, it does not distinguish from similar sibling tools like extract_urls, which also extracts patterns from text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear use case: 'Pull email addresses from free text / logs.' This tells the agent when to use it, but it lacks exclusions or mentions of alternatives, such as when to use a dedicated email validator.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It does not specify case sensitivity, handling of duplicates, support for relative URLs, malformed URLs, or what protocols are included. The description is too minimal to guide correct invocation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is front-loaded and contains no redundant words. Every word contributes to the purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the absence of an output schema, the description should hint at the return format (e.g., a list of strings). It does not mention what is returned, how duplicates are handled, or behavior in edge cases like no URLs found. The tool is simple, but the description lacks completeness for reliable AI invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'text' is described only as 'arbitrary text' in the tool description. This adds minimal meaning beyond the input schema, which lacks any description (0% coverage). The description implies the text is a string to search for URLs, but lacks details on expected format, encoding, or length limits.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (extract), the resource (HTTP/HTTPS URLs), and the source (arbitrary text). It is specific and distinguishes from sibling tools like extract_emails, url_parse, or regex_replace by focusing on extraction of URLs from free-form text.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives such as url_parse for single URLs or regex_replace for custom patterns. There is no mention of when not to use it or any prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It states the basic action (splitting frontmatter from body) but does not detail return format, error behavior (e.g., what happens if no frontmatter is found), or any side effects. This is insufficient for a tool with no other behavioral cues.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Very concise with two sentences that cover the core purpose and usage. No redundant information, but could be slightly more structured with explicit sections. Nonetheless, it is efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity of the tool (one parameter, no output schema), the description provides the essential context for use. However, it lacks details on return value structure and edge cases, which may be needed for an agent to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Only one parameter 'text' with a string type and 0% schema coverage. The description implies that 'text' is markdown content containing frontmatter, adding minimal context beyond the schema. However, it does not specify the format or any constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it parses YAML frontmatter from markdown with the delimiter pattern. It has a specific verb and resource, but does not explicitly differentiate from sibling tools like changelog_parse or markdown_link_extract, though the function is distinct enough.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Includes a 'When' clause that says when to use it: to split YAML frontmatter from the markdown body. This provides clear context, though it does not 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It mentions specific checks (triggers, unpinned actions, curl|bash), giving some insight, but does not disclose return format, side effects, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence with no superfluous words. It efficiently conveys the tool's purpose and specific checks.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description covers the core functionality but lacks information about the return format (e.g., list of issues or pass/fail). This omission affects completeness for an agent invoking the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one 'text' parameter with no description. The description implies that 'text' is the YAML content, but does not specify format or constraints beyond what the schema provides. With 0% schema coverage, the description should add more clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action (lint) and resource (GitHub Actions workflow YAML), and lists specific checks (triggers, unpinned actions, curl|bash), distinguishing it from sibling utilities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The usage context is implied by the tool name and description, but no explicit guidance on when to use or alternatives is provided. Since siblings are all other utilities, the context is somewhat clear but lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description states the tool checks for common missing ignores, which is transparent for a read-only check. However, it does not disclose what the output looks like (e.g., list of missing items) or how errors are handled, though annotations are absent, so the description carries full burden.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that front-loads the core purpose. It is efficient but could benefit from clarifying the parameter or output format without adding significant length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple check tool with no output schema, the description adequately conveys the tool's purpose but omits the return format and does not enumerate all checked items beyond the three examples, leaving some gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has one parameter 'text' with zero schema description coverage. The description implies this is the .gitignore content, but does not explicitly confirm the parameter's meaning, leaving ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool reviews .gitignore files for common missing entries like .env, node_modules, keys. This is a specific verb+resource scope and distinguishes it from the sibling 'gitignore_match', which likely does pattern matching rather than checking for missing ignores.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a user has a .gitignore file and wants to check for missing common patterns, but it does not explicitly mention when to use this tool over alternatives like 'gitignore_match' or other linters among siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description bears full burden. It discloses 'best-effort' compliance and handles negation, but fails to mention return format or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, front-loaded with the purpose, no redundant information. Efficient and to the point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with no output schema, the description covers the core behavior but omits parameter explanations and return details. Adequate but with gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explicitly define the parameters. While 'paths' and 'gitignore' are inferable from context, the description should clarify their roles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it matches paths against .gitignore rules, mentioning ignore/negate semantics. However, it does not differentiate from the sibling tool 'gitignore_check', so not a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'When:' clause suggests usage for testing .gitignore rules, but lacks explicit instructions on when not to use or alternatives. With siblings like gitignore_check, guidance would be helpful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It does not explicitly state that the tool is read-only or side-effect-free, which is critical for a parsing tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with minimal waste, but the second sentence partly repeats the first. Could be integrated more tightly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, and the description only mentions the output components without specifying the structure. It partially explains the return format but is insufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds some context about the expected URL format (ssh/https), but does not provide full details or examples for the 'url' parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Parse' and the specific resource 'git remote URL (ssh/https)', and lists the output components 'host/owner/repo'. This distinguishes it from general URL parsers like url_parse.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'When:' clause gives explicit context for when to use the tool (for git@ and https remotes), but does not explicitly name alternatives or state 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.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It mentions gitignore-style matching but does not disclose output format, behavior on mismatches, or edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise at one sentence, but structure is flat and lacks information. It is appropriately sized for simple tools but lacks depth.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple schema with two array parameters and no output schema, the description missing critical details like return value leaves the tool incomplete for an agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description does not explain the 'paths' and 'patterns' parameters beyond their names, leaving their semantics ambiguous.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool matches paths against glob patterns using gitignore-style fnmatch, with a specific verb and resource. It distinguishes from siblings like gitignore_match by implying batch operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like gitignore_match or similar. No context on prerequisites or appropriateness.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the burden. It mentions 'best-effort', which is an important behavioral trait suggesting incomplete or approximate results. However, it does not disclose other potential behaviors (e.g., no mention of permissions, side effects, or error handling).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is exceptionally concise at two sentences. Every word serves a purpose: the first sentence states the action and resource, the second provides usage guidance. No redundancy or unnecessary details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description is mostly adequate but lacks details about the output format (e.g., structure of listed names) and any prerequisites for the input document. The 'best-effort' qualifier is useful but does not fully cover what the agent can expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 1 required parameter 'text' with 0% description coverage. The description does not explain what 'text' represents (e.g., a GraphQL document string, file path, etc.) or its expected format, leaving the agent to infer its semantics from the context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists GraphQL query/mutation/subscription names and type definitions from a document. It is specific about the resource (GraphQL operations and types) and the action (list), distinguishing it from sibling tools like graphql_validate or graphql_schema_diff.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description includes 'When: List GraphQL ops/types from a document' which provides usage context. However, it does not explicitly state when not to use this tool or mention alternatives, leaving some ambiguity about when another sibling might be more appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden but only states it diffs for removed types/fields. It does not clarify if it also detects additions or modifications, nor does it specify expected input format (e.g., SDL, introspection JSON). The behavior is under-disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that immediately conveys the core purpose. While brief, it is front-loaded and efficient. However, it could include structured detail without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, no annotations, and low parameter documentation, the description is incomplete. It does not mention output format, error handling, or prerequisites like valid GraphQL schemas. The tool's simple nature somewhat mitigates, but information gaps remain.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description does not add meaningful context beyond parameter names. It does not specify data types (e.g., SDL string, introspection JSON) or constraints. The description fails to compensate for the lack of schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'diff', the resource 'GraphQL schemas', and the specific scope 'for removed types/fields (breaking changes)'. It distinguishes itself from sibling tools like graphql_validate or generic diff tools by focusing on GraphQL-specific breaking changes detection.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a user wants to find breaking changes between two GraphQL schema versions, but it does not explicitly state when not to use it, nor does it mention alternatives like graphql_validate or semantic versioning tools. The guidance is minimal.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses the key behavioral trait that it only performs syntax validation ('parse only'), which is crucial. However, without annotations, it fails to mention whether the tool requires network access, authentication, or any side effects, and does not specify the return format (e.g., success/error indication).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one sentence of 10 words, front-loaded with the main action 'Validate', and contains no redundant information. Every word contributes to meaning.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simplicity (1 param, no output schema), the description provides the core purpose and limitation (parse only). However, it omits details about return values (e.g., success/error messages) and input format specifics, 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.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'text' has no description in the schema (0% coverage), and the tool description does not explicitly state that the input should be a GraphQL query or schema SDL string. While this is implied, the parameter name 'text' is generic, and the lack of explicit documentation forces the agent to infer meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'validates GraphQL query or schema SDL syntax (parse only).' It specifies both the resource (GraphQL query/schema) and the scope (syntax validation only), distinguishing it from semantic validators and other sibling tools like json_validate.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool vs alternatives. With many sibling tools for validation (e.g., json_validate, yaml_validate), explicit context about when to choose graphql_validate would help. The description only states what it does, not when to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must carry the burden. It notes case-insensitivity but omits the return value type (e.g., boolean for match) and error conditions. Incomplete for agent decision-making.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single focused sentence, no filler. However, it could include additional details (like return type) without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and minimal input schema descriptions, the tool description should explain the return value and behavior on mismatch, but it does not. Only provides basic purpose.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 0% description coverage and the description says 'hash digests' but adds no constraints, format hints, or examples for the two string parameters. Limited added value over the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states the verb 'compare' and the resource 'hash digests', with the specific behavior 'case-insensitive'. This distinguishes it from sibling tools like hash_md5 which generate hashes.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for comparing hashes but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions. For a simple tool, this is acceptable but minimal.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden. It states it computes a hash, which is a read operation, but does not disclose additional traits like synchronous execution or return format. Acceptable for a simple hash function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no fluff: first states the action, second provides usage context. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter hash tool, the description is adequate: it explains purpose and usage context. It does not mention output format (hex string), but the name implies it, and there is no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Despite 0% schema description coverage, the description adds 'UTF-8 text' clarifying encoding for the single 'text' parameter, compensating for the lack of parameter documentation in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it produces MD5 hex digest of UTF-8 text, and distinguishes from sibling hash functions (SHA-256, SHA-512) by specifying the algorithm.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit guidance on when to use ('non-crypto integrity / legacy checksums'), but does not explicitly mention alternatives or when not to use, though siblings imply other algorithms.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and the description does not disclose any behavioral traits (e.g., side effects, determinism, input size limits). The burden is fully on the description, which is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise at 4 words, front-loaded. However, might be too terse; a bit more context would not hurt.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple hash tool with one parameter and no output schema, the description does not explain input format, output case (lower/upper), or edge cases. Lacks completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% and the description adds no extra meaning for the single parameter 'text'. It only describes the algorithm, not the parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'SHA256 hex digest' clearly states the tool computes a SHA256 hash and outputs a hex string. It's specific and not a tautology, but does not differentiate from sibling hash functions beyond the algorithm name.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like hash_md5 or hash_sha512. No context on prerequisites or use cases.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description must carry the full burden. It does not disclose behavioral traits such as the output being a hex string, that hashing is one-way, or any edge-case handling (e.g., empty string), leaving the agent underinformed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

At three words, the description is extremely concise, but it sacrifices completeness. It is front-loaded with the core concept, but could include more detail without becoming verbose. Not ideal balance between brevity and informativeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (single parameter, no output schema, no annotations), the description is incomplete. It omits the output format, any mention of data types, and potential constraints like text length limitations, leaving gaps for the agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description only adds 'hex digest' context, which does not detail the parameter beyond the schema's 'text' string. It does not explain valid inputs, encoding expectations, or constraints, failing to compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it produces a SHA512 hex digest, which identifies the specific algorithm and output format. It distinguishes from siblings like hash_md5 and hash_sha256 by naming the algorithm explicitly, though it does not explicitly contrast them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use SHA512 versus other hash functions (e.g., hash_md5, hash_sha256) or alternatives. The description lacks any context about typical use cases or when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description should disclose behavioral traits like error handling (e.g., invalid hex input), case sensitivity, or whitespace handling. No such details are provided, leaving the agent uninformed about edge cases.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise, but this brevity comes at the cost of completeness. It front-loads the core purpose but omits necessary details, making it minimally acceptable.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (single param, no output schema, no annotations), a complete description should cover input format, output spec, and error behavior. This description only states the conversion direction, leaving significant gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The single parameter 'text' is implied to be the hex string, but the description does not elaborate on expected format (e.g., prefix '0x', allowed characters, spaces). With 0% schema coverage, the description should compensate but falls short.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool converts a hex string to UTF-8 text, which is a specific operation distinct from encoding or other decoding formats. However, it does not explicitly mention the input and output types beyond the conversion direction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to use this tool versus alternatives like base64_decode or hex_encode. The description lacks any context about prerequisites, preferred use cases, or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Lacks annotations, so description must carry full burden. It does not disclose output format (case, prefix, delimiters) or behavior on empty input. Minimal transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no fluff. Front-loaded and efficiently communicates the core function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description is adequate but could specify output format (e.g., 'returns lowercase hex string without 0x prefix') for completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. The phrase 'UTF-8 text' adds meaning that input should be a UTF-8 string, but no details on encoding or error handling.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'UTF-8 text to hex string' clearly states the verb (encode) and resource (text to hex). It distinguishes from siblings like hex_decode and other encoding tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as base64 encoding or hex_decode. Usage must be inferred from the name and sibling list.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description outlines the core behavior—signing with HMAC—but does not disclose potential behavioral traits such as handling of invalid keys, idempotency, or security implications. With no annotations, the description carries the full burden, which it only partially meets.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence of 13 words, efficiently communicating the essential purpose and options without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 4 parameters, no output schema, and a cryptographic operation, the description covers the core functionality but omits details like output format, error handling, and edge cases, making it minimally complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description is the sole source of parameter meaning. It clarifies that 'message' is the data to sign, 'secret' is the key, 'encoding' outputs hex/base64, and 'algorithm' supports sha1/sha256/sha512, significantly adding value over the plain schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'HMAC sign' and the resource 'message', and specifies supported algorithms (sha1/sha256/sha512) and output formats (hex or base64), distinguishing it from sibling tools like hmac_verify.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives such as hmac_verify or other cryptographic tools. The description lacks context about prerequisites or exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries the burden. It discloses that the signature can be hex or base64 encoded, which is useful. However, it omits what the output is (e.g., boolean) and how failures are handled. For a verification tool, agents need to know whether it returns true/false or throws an error.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, which is concise but lacks any structure. It front-loads the verb but packs format info in parentheses. It could be improved by separating the purpose from format details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description is insufficient. It does not explain the return value, behavior on invalid signatures, or algorithm versatility. Agents cannot confidently use this tool without more context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so description must compensate. It only hints that the 'signature' parameter can be hex or base64. It does not explain 'message', 'secret', or 'algorithm' (which has a default of 'sha256'). This leaves significant gaps for agents to understand parameter roles.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states verb 'verify' and resource 'HMAC signature', and mentions supported formats (hex or base64). It distinguishes from the sibling hmac_sign which does the opposite operation, but could be more explicit about the return value (boolean or something).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like hmac_sign, jwt_verify, or hash_compare. Agents are left to infer context from the verb and resource alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, and the description omits behavioral details such as handling of comments, blank lines, malformed entries, or error behavior. It does not disclose any side effects or safety considerations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is short (two sentences) but lacks structure and depth. It is not verbose, but it could be more informative without added length.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, no annotations, and the description covers only the basic purpose. It does not explain the output format, error handling, or edge cases (e.g., multiple IPs, aliases), leaving significant gaps for a first-time user.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description must explain the parameter 'text', but it does not mention the parameter at all. It fails to add meaning beyond the schema, leaving the agent to guess that 'text' is the file content.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb (Parse) and the resource ('/etc/hosts style file') and specifies the output structure 'IP → hostnames entries'. It is distinct from sibling tools like csv_parse or ini_parse, which target different formats.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'When:' clause merely repeats the purpose ('Parse /etc/hosts style IP→hostname maps') and provides no guidance on when to use this tool versus alternatives, when not to use it, or any prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. The description is accurate but does not disclose edge cases or behavior with invalid input.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise, front-loaded, and every word is necessary.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with one parameter and no output schema, the description is minimally complete but lacks usage context and parameter details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description does not explain the 'text' parameter, adding no meaning beyond the type declaration.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it unescapes HTML entities, which is specific and distinguishes it from siblings like html_encode.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives, such as html_encode or other decoding tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It does not disclose behavior such as error handling, returned encoding format, or assumptions. Minimal transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (one sentence) but under-specified. While brevity is good, it sacrifices useful context. Front-loading is fine, but it lacks completeness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with no output schema, the description should at least indicate the return value (e.g., encoded string). It does not, leaving the agent to guess the output format.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, and the description does not add any meaning beyond the parameter name and type. No explanation of what the 'text' parameter expects or constraints.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Escape HTML entities.' clearly states the tool's action and resource. It is specific enough to distinguish it from siblings like html_decode, but could be more explicit about which entities are escaped.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like html_decode or other encoding tools. The description lacks context on appropriate use cases or prerequisites.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description carries full burden. It discloses the heuristic, best-effort nature and that it's not a full parser. However, it doesn't describe the return format, error behavior, or any side effects. Adequate but not comprehensive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, each concise and front-loaded. First sentence states purpose, second adds critical caveat. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and description does not explain what the tool returns (e.g., list of findings, severity). For a heuristic scanner, this output information is essential for an agent to use the result correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and description only implies the parameter is HTML text. No details on expected encoding, size limits, or format. Description adds minimal value beyond the schema's type declaration.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb (Scan) and resource (HTML) and lists exact patterns (XSS-prone: javascript: URLs, inline handlers, eval). It clearly distinguishes from sibling scanning tools which target different content types (e.g., secrets_scan, sql_danger_scan).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives like secrets_scan or sql_danger_scan. The description mentions it's heuristic but does not provide decision criteria for tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description should disclose behavioral traits. It lacks any mention of side effects, performance characteristics, error handling, or limitations. The description is too brief to inform the agent of behavioral nuances.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two short sentences, front-loading the core purpose. Every word contributes meaning; no redundancy or fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the lack of output schema and parameter details, the description is incomplete. It does not specify the output format or any edge cases, leaving the agent uninformed about what the tool returns or how to handle complex inputs.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The sole parameter 'html' has no description in the schema (0% coverage), and the tool description fails to explain what kind of HTML string is expected (e.g., full document or fragment, encoding, size limits). No value is added beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Convert HTML to Markdown text' with a specific verb and resource. It distinguishes from sibling tools like 'markdown_to_html' by specifying the direction and usage context 'for docs the agent edits.'

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a usage context ('When: Convert HTML → markdown for docs the agent edits'), implying when to use it. However, it does not explicitly exclude other scenarios or mention alternatives beyond the directionality.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.