ToolAPI

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

No annotations provided, and the description only states the basic operation. Missing details on handling invalid input, padding requirements, or error 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 single sentence is efficient and front-loaded with the action. No wasted words.

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

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

For a simple decode tool with no output schema and minimal parameters, the description adequately covers the purpose but lacks details on edge cases like padding or whitespace tolerance.

Complex tools with many parameters or behaviors need more documentation. 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 clarifies the input parameter 'text' as base64-encoded and the output as UTF-8, adding meaningful context beyond the schema.

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

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

The description clearly states the verb 'Base64-decode' and the resource (string), distinguishing it from sibling tools like base64_encode and base64url_decode.

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

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

No guidance on when to use this tool versus alternatives like base64url_decode for URL-safe base64. No context about prerequisites or restrictions.

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, and the description does not disclose any behavioral traits such as error handling, output format, or idempotency. The description only states the operation without any behavioral details.

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

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

The description is extremely concise (3 words), which is suitable for a simple tool but risks under-specification. It is front-loaded but lacks additional sentences that could clarify purpose or behavior.

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

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

Given the tool's simplicity (one parameter, no output schema, no nested objects), the description is minimally complete. However, it omits important context like output format (base64 string) or any limitations.

Complex tools with many parameters or behaviors need more documentation. 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 one parameter 'text' with a coverage of 0%, and the description does not add any semantic meaning beyond what the schema provides. It does not explain expected input format (e.g., valid strings) or edge cases.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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-encode) and the input format (UTF-8). However, it is very minimal and does not elaborate on the purpose or output. It distinguishes from siblings like base64_decode due to the naming, but lacks explicit differentiation.

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

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

No guidance on when to use this tool versus alternatives like base64url_encode or hex_encode. The description provides no context for selection or exclusion.

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

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

With no annotations, description only says it decodes to UTF-8. No mention of error handling, padding, or input validation. Adequate but not transparent beyond 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?

Extremely concise and front-loaded. Every word is necessary. No wasted space.

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

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

For a simple decode tool with one parameter and no output schema, the description is almost complete. It explains input and output format. Could mention padding or charset details 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?

Only parameter is 'text', and description does not explicitly describe it. Schema coverage is 0%, and the description offers little added meaning beyond the parameter name.

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

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

Clearly states the tool decodes base64url-encoded strings to UTF-8 text. Distinct 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 vs alternatives (e.g., base64_decode, hex_decode). Missed opportunity to clarify base64url-specific 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?

Adds valuable behavioral details (no padding, URL-safe) beyond the schema. No annotations provided, so description compensates well. Could mention 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: one sentence front-loaded with verb and key properties. 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?

Sufficient for a simple, single-parameter encoding tool with no output schema and no annotations. Covers essential behavioral traits.

Complex tools with many parameters or behaviors need more documentation. Simple tools 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%, but description implies text is UTF-8 encoded. Adds some meaning, though could clarify input expectations (e.g., string type). Baseline 3 due to single param.

Input schemas describe structure but not intent. Descriptions should explain 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 base64url-encodes a UTF-8 string with no padding and URL-safe. Distinguishes from siblings like base64_encode (standard base64) and base64url_decode.

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

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

No explicit guidance on when to use this vs. base64_encode or other tools. For a simple utility, purpose is obvious, but lacks alternative selection cues.

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?

Neither the description nor annotations disclose important behavioral traits of bcrypt, such as that it is a one-way function, includes a salt, or is intentionally slow to resist brute-force attacks. The description is silent on these critical security aspects.

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

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

The description is a single concise sentence, which avoids waste but lacks structure. It fails to front-load key details such as output format or usage context, making it minimally adequate.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence 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 must provide substantial context. However, it omits essential details like return value format, security considerations, and the effect of the 'rounds' parameter, leaving the tool severely under-described.

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

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

With 0% schema description coverage, the description should explain the role of the 'rounds' parameter (cost factor), but it does not. The description only mentions 'password' without adding any meaning beyond the parameter name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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 ('Bcrypt-hash a password') and the intended use ('for storage'), distinguishing it from related tools like bcrypt_verify (verification) and other hash functions (different algorithms).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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 bcrypt_verify or other hash tools. The description does not indicate that bcrypt is specifically for password hashing or mention scenarios where it is preferred.

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 carries full burden. It only states the action without disclosing return type (likely boolean), side effects, or error conditions. The name implies behavior but lacks explicit transparency.

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

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

The description is a single sentence with no wasted words. However, its extreme brevity sacrifices completeness for conciseness.

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

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

For a simple 2-parameter tool with no output schema, the description should at least hint at the return value and validation behavior. It fails to provide enough context for correct use.

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

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

Schema description coverage is 0%, yet the description adds no meaning to the two parameters 'password' and 'hash'. It does not clarify their roles, expected format, or relationship, leaving the agent to rely solely on parameter 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 clearly states the tool's function with a specific verb and resource: 'Verify password against bcrypt hash.' It effectively distinguishes from sibling tools like bcrypt_hash and other verification tools.

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

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

No guidance is provided on when to use this tool versus alternatives or any prerequisites. The agent must infer usage context from the name alone.

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

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 handling of malformed input, expected structure, or error behavior. The single sentence lacks behavioral context beyond the basic purpose.

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

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

The description is one concise sentence that front-loads the action and resource. Every word earns its place, and there is no extraneous information.

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

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

Given the lack of annotations and output schema, and only one parameter, the description is insufficient. It does not explain the output format ('version sections') or how the tool behaves with edge cases, making it incomplete for reliable use.

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

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

Schema description coverage is 0%; the description adds minimal value by mentioning 'markdown,' but does not explain the expected format or constraints for the 'text' parameter. More detail on input requirements is needed.

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

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

The description clearly states the action ('Parse') and resource ('Keep-a-Changelog style markdown') and specifies the output ('version sections'). It is specific and distinguishes from sibling tools like 'frontmatter_parse' or 'conventional_commit_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 Keep-a-Changelog markdown but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternative tools for other markdown parsing needs.

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 mentions computing network info but fails to describe side effects, permissions, error handling, or the exact format of the returned info. This is insufficient for a computation tool.

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

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

The description is extremely concise—one sentence of 10 words—and front-loads the key action and resource. No wasted words.

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

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

Given the single parameter and no output schema, the description is adequate but lacks details about the return structure. It lists some output fields but not comprehensively, leaving the agent uncertain about the full response format.

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

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

Schema coverage is 100% with one parameter, and the description adds meaning beyond the schema by listing 'hosts, broadcast, private' as examples of computed values. This helps the agent understand what kind of information is derived.

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

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

The description clearly states the verb 'Calculate' and the resource 'IPv4/IPv6 network info from CIDR', specifying examples like hosts, broadcast, private. This distinguishes it from sibling tools such as 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?

The description implies usage for calculating CIDR network info but provides no explicit guidance on when to use this tool versus siblings or when not to use it. No exclusions or alternatives are 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 provided, the description carries the full burden of behavioral disclosure but only states the basic purpose. It does not mention return type, error handling, input validation, or any side effects. The agent is left to assume it returns a boolean.

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

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

The description is a single sentence that communicates the purpose efficiently. However, given the lack of annotations and minimal parameter details, it may be too brief to be fully 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?

The tool has no output schema and no annotations, and the description does not explain how to interpret the result (e.g., returns boolean) or handle edge cases. This is insufficient for an agent to use the tool correctly without further context.

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

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

The input schema has 0% description coverage for parameters, and the tool description does not elaborate on the parameters beyond their names (ip, cidr). No format or constraints are added, so the description adds no 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?

The description clearly states the verb 'Check' and resource 'IP address falls within a CIDR range', making the purpose specific and distinguishable from sibling tools like cidr_calc, which likely focuses on 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 implies that this tool is for membership checking, but it does not explicitly state when to use it versus alternatives like cidr_calc, nor does it provide any usage constraints 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 are present, so the description must disclose behavioral traits. It only states the basic function without detailing behavior like handling multiple blocks, empty input, or error conditions.

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

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

The description is a single concise sentence, front-loaded with the action verb. It is efficient but lacks necessary details, making it slightly too terse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence 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, annotations, and parameter details, the description is insufficient for complete understanding. It omits information about return format, edge cases, and behavior for invalid input.

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

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

Schema description coverage is 0%, and the description does not explain the single 'text' parameter. It fails to add meaning beyond the schema, leaving the agent to infer that 'text' is markdown 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 tool extracts fenced code blocks from markdown, specifying both language and code. It uses a specific verb and resource, distinguishing it from sibling extraction tools like 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?

No guidance is provided on when to use this tool versus alternatives, such as other extraction tools. 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 full burden. It mentions AA/AAA compliance levels but does not clarify the return format (e.g., ratio value, pass/fail), error handling for invalid hex values, or other behavioral details. The description is insufficient for the agent to know exactly what to expect.

Agents need to know what a tool does to the world before calling 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 and front-loaded, conveying the essential purpose in a single sentence. 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?

Despite the tool's simplicity, the lack of output schema and param descriptions, combined with minimal behavioral transparency, leaves gaps. The agent may not know what the tool returns or how to provide valid input.

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

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

Schema description coverage is 0%, yet the description only states 'two hex colors' without specifying which parameter is foreground (fg) or background (bg), nor the expected hex format (e.g., with or without '#'). The parameters are not individually explained.

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

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

The description clearly states the tool computes WCAG contrast ratio between two hex colors, specifying AA/AAA levels. It distinguishes from sibling tools like color_convert, which handles color space conversion, not contrast ratio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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 indicates the tool is for WCAG contrast ratio for UI color pairs, providing clear context. However, it does not specify when not to use it or mention 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 are provided, and the description does not disclose any behavioral traits such as whether the operation is read-only, side-effect-free, or has any constraints. For a simple conversion tool, the description is minimal but lacks transparency about output format or error handling.

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

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

The description is a single concise sentence that efficiently conveys the tool's purpose without unnecessary words or repetition. It is well-structured for quick comprehension.

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

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

Given the tool's simplicity and the presence of a schema with an enum for to_format, the description covers the basic purpose. However, it omits explaining the output format or behavior when to_format defaults to 'all', leaving the agent to infer from the schema. This is adequate but not fully complete.

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

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

Schema description coverage is 50% (color parameter described, to_format only via enum). The description adds no semantics beyond the schema for either parameter; it merely restates the color format options already in the schema. It does not explain the meaning or effect of the to_format parameter.

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

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

The description clearly specifies the tool's function: converting colors between hex, rgb(), and hsl() formats. It uses a specific verb ('convert') and explicitly names the three supported formats, which distinguishes it from siblings like 'color_contrast'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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 color format conversion but provides no guidance on when to use this tool versus alternatives (e.g., no mention of color_contrast or other color-related tools). No exclusions or contextual cues 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?

No annotations provided. Description mentions 'validate' and 'flag' but lacks specifics on output format, error handling, or what flagging entails.

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

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

Single sentence, front-loaded with key actions, 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?

No output schema, no annotations, and minimal description. Missing details about return values or how flagged issues are presented, making it 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?

Only parameter 'text' (string) has no schema description. The description infers it's the YAML content, but adds minimal detail beyond the schema.

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

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

The description clearly states the tool validates docker-compose YAML and flags specific issues (privileged/host-network/secret env), distinguishing it from sibling validation tools.

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

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

No explicit guidance on when to use this tool vs alternatives like yaml_validate or json_validate, though the purpose is implied.

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, and the description only states the action without disclosing error handling, behavior on invalid input, side effects, or return format. Minimal transparency beyond the obvious.

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

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

Single-sentence description is appropriately concise for a simple parsing tool, front-loading the verb and outputs 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?

Tool has no output schema and no annotations. Description omits return value details (mime, charset, params structure) and error conditions, making it incomplete for an agent to know what to 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?

Schema coverage is 0% and description does not explain the 'header' parameter format (e.g., full header line vs value-only). Only mentions 'Content-Type header' in context, 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?

Description clearly states verb 'Parse' and resource 'Content-Type header', and specifies outputs 'mime/charset/params'. This distinguishes it from sibling tools that parse other things, though no explicit differentiation is made.

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

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

No guidance on when to use this tool versus alternative parsers like url_parse or user_agent_parse. No mention of prerequisites, typical 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?

No annotations are provided, so the description carries full burden for behavioral disclosure. It only states it 'lints' the message, but does not clarify the output format (e.g., returns pass/fail, errors list, or modified message). Without annotations, the agent cannot infer side effects or expected behavior beyond the vague term 'lint'.

Agents need to know what a tool does to the 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 one-sentence description that front-loads the core purpose. It efficiently conveys the tool's function without unnecessary verbosity. However, it could benefit from slightly more detail without becoming overly long.

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

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

Given the simplicity (one param, no output schema, no annotations), the description is minimal. It tells what the tool does but omits crucial details like return value format, error handling, and acceptance criteria. An agent would need to trial-and-error to understand the tool's full behavior.

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

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

Schema has a single required 'message' (string) with 0% description coverage. The description adds that the message should follow Conventional Commits format and lists example types, but does not explain the exact structure or requirements. For a single parameter, this provides some semantic value, but could be more explicit about expected format.

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

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

Description clearly states the tool 'Lint Conventional Commits message' with specific verb 'lint' and resource 'Conventional Commits message'. It further elaborates with example types (feat/fix/chore…), distinguishing it from sibling tools that are general-purpose encoders, parsers, and validators. This provides a precise purpose.

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

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

No guidance on when to use this tool versus alternatives. Among sibling tools, there are other linting and validation tools (e.g., dockerfile_lint, sql_danger_scan), but the description offers no context on when conventional_commit_lint is appropriate or when to use another tool. No exclusionary criteria or prerequisites are mentioned.

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

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

With no annotations, the description must fully disclose behavioral traits. It mentions the output is a 'name/value map' but does not detail how malformed headers are handled, whether the 'Cookie:' prefix is expected, or any limitations. No destructive or read-only hint is implied, leaving ambiguity.

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

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

The description is two sentences, but the second is redundant ('When: Parse Cookie request headers'). It is short but could be more concise by merging the two sentences. The structure is adequate but not efficient.

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

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

Given that there is no output schema, the description should clarify the return format beyond 'name/value map'. It does not address error handling, edge cases, or behavior with multiple cookies. For a simple parsing tool, it is minimally complete but lacks details needed for reliable 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 input schema has one parameter 'header' with no description and 0% schema coverage. The description does not elaborate on the expected format (e.g., should it include the 'Cookie:' label or just the value?), leaving the agent to guess. No enums or examples are provided.

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

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

The description clearly states it parses a Cookie request header into a name/value map, which is a specific verb and resource. It distinguishes itself from sibling tools like http_headers_parse that parse all headers, but could be more explicit about its unique purpose.

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

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

The 'When: Parse Cookie request headers' line essentially repeats the purpose without providing guidance on when to use this tool versus alternatives, such as using a general HTTP header parser or cookies from a parsed request object. No exclusions or context are given.

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

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

With no annotations, the description must carry the full burden. It states the tool checks for 'unsafe combinations' but does not explain what constitutes unsafe, what output format is returned, or any side effects. This is insufficient for full behavioral understanding.

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

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

The description is a single, front-loaded sentence that conveys the core action without any wasted words. It is highly concise and structured.

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

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

Given no annotations, no output schema, and 0% param coverage, the description is minimal. It lacks details on return values, error handling, and specific unsafe combinations, making it incomplete for an agent to use confidently.

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

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

Schema coverage is 0%, so the description must add meaning. It explains 'allow_origin' and 'allow_credentials' are compared, but 'origin' is not explained. This partially compensates but leaves a gap, warranting a 3.

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

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

The description uses a specific verb 'Check' and clearly identifies the resource as 'CORS Allow-Origin vs credentials' for unsafe combinations. This distinguishes it from all sibling tools, none of which focus on CORS.

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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 used when you need to check CORS configurations, but it does not explicitly state when to use it vs alternatives, nor does it provide any exclusions or prerequisites.

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

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

No annotations provided, so the description carries full burden. It mentions the output is a human-readable description in EN and ZH, but lacks details on language selection, error handling, or return format. Minimal behavioral disclosure beyond the basic output.

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

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

The description is a single, clear sentence that conveys the essential information without any unnecessary words. It is front-loaded and efficient.

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

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

Given the low complexity and absence of output schema, the description provides a basic understanding but lacks explanation of return values or language options. For a tool with many siblings, more context would be beneficial.

Complex tools with many parameters or behaviors need more documentation. Simple 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% (no description for the 'expr' parameter). The tool description does not add any additional meaning about the parameter beyond 'cron expression', which is already implied by the parameter name. It does not compensate for the lack of schema descriptions.

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

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

The description clearly states the tool's purpose: to provide a human-readable natural language description of a cron expression, supporting English and Chinese. It uses a specific verb and resource, and distinguishes it from sibling tools like cron_parse, cron_validate, 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 its siblings (e.g., cron_matches, cron_next_runs). The context is implied by the description, but there is no direct comparison or when-not-to-use advice.

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 full burden of behavioral disclosure. It does not mention the return type (e.g., boolean), the expected cron expression format (e.g., 5-field or 6-field), how invalid expressions are handled, or timezone interpretation. This is insufficient for a tool with no annotations.

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

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

The description is a single sentence that efficiently conveys the tool's core functionality. No unnecessary words, and it is front-loaded.

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

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

Given the tool has 3 parameters, no output schema, and no annotations, the description is too minimal. It fails to document the return value, cron expression format, timezone handling, or error behavior, making it incomplete for an agent to use correctly.

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

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

The description adds little beyond the input schema. It repeats the ISO-8601 mention for at_time (already in schema) and provides no additional meaning for expr or timezone. With only 33% schema description coverage, the description should compensate by explaining these parameters further.

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

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

The description clearly states the tool's purpose: checking if a cron expression matches a specific datetime. It uses a specific verb 'check' and resource 'cron expression matches a specific datetime', which distinguishes it from sibling tools like cron_next_runs or 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_next_runs or cron_validate. Given the many sibling tools related to cron, the description should explicitly mention when to choose this tool and when not to.

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 should disclose side effects, read-only nature, or constraints. It only says 'preview,' implying no modification, but does not explicitly state that the tool is safe and non-destructive. It also fails to mention timezone handling, error cases, or the 5-field constraint.

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

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

The description is a single sentence with no waste, making it easy to parse. However, it is perhaps too concise; it could include a brief note about the count default or timezone behavior without sacrificing clarity. It front-loads the core action but misses ancillary details.

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

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

Given the tool has 4 parameters, no output schema, and many sibling cron tools, the description is incomplete. It does not explain the return format (timestamps?), error handling for invalid expressions, or behavior when from_time is provided. Users would need to infer or test these aspects.

Complex tools with many parameters or behaviors need more documentation. Simple 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 25% (only from_time has a description). The tool description hints at 'N' (matching count) and '5-field cron expression' (matching expr), but does not detail defaults or constraints for count and timezone. It adds modest value by emphasizing the 5-field limitation, but overall does not compensate for the low schema coverage.

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

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

The description clearly states the tool's purpose: 'Preview next N execution times for a 5-field cron expression.' It specifies a specific verb (preview) and resource (execution times), and the 'N' parameter implies configurability. This distinguishes it from sibling tools like cron_describe (which describes format) and cron_parse (which parses components).

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

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

The description provides no guidance on when to use this tool versus alternatives like cron_describe or cron_matches. It does not mention prerequisites, typical use cases, or that it is intended for checking future runs rather than describing syntax or checking matches.

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 only states the parsing action but does not mention whether input validation occurs, error handling, or return format. This is insufficient transparency.

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

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

The description is a single, front-loaded sentence with no redundancy. Every word adds value. Ideal conciseness.

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

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

Given one parameter and no output schema, the description is adequate but incomplete. It fails to mention the expected output structure (e.g., object with minute/hour/etc. fields), which would help the agent know what to 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 0% coverage, so the description partly compensates by specifying '5-field cron' format. However, it doesn't provide an example or specify allowed characters (e.g., wildcards, ranges). Minimal 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 verb 'Parse' and the resource '5-field cron into named fields'. It distinguishes itself from siblings like cron_validate or cron_describe by focusing solely on 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?

No guidance is provided on when to use this tool versus alternative cron tools (e.g., cron_describe, cron_validate). The description lacks context about prerequisites or when parsing is preferred.

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 fails to disclose behavior on validation failure (error or boolean return), side effects (none expected), or return format. 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 wasted words. Front-loaded with key action and scope.

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

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

Given no output schema and minimal description, the tool's return value (boolean? error object?) is not described. Missing details like whether it accepts seconds field or just standard cron. Incomplete guidance for an AI agent to predict behavior.

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

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

Adds some meaning to the 'expr' parameter by specifying expected value ranges (minute 0-59, hour 0-23, etc.), but does not fully describe standard cron expression syntax (e.g., 5 or 6 fields, special characters like '*' '/', ','). Schema has 0% coverage, so description partially compensates.

Input schemas describe structure but not intent. Descriptions should explain 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 validates cron field syntax and value ranges, but lacks differentiation from sibling tools like cron_validate and cron_validate_batch, which likely have overlapping purposes.

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

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

No guidance on when to use this tool versus alternatives (e.g., cron_validate, cron_validate_batch). No context for appropriate usage or exclusions.

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

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

With no annotations, the description must fully convey behavior. It only states what the tool checks but doesn't disclose return format (e.g., boolean, error messages), edge cases, or side effects. This leaves significant ambiguity.

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

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

The description is a single sentence with no unnecessary words. However, it is too brief to be fully helpful, sacrificing completeness for brevity. A balance would be better.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence 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 output schema and annotations, the description should cover output expectations and behavioral details. It does neither, leaving the agent with insufficient information to use the tool 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?

The schema has 0% coverage for parameter descriptions, and the tool description adds only that the parameter is a 'cron string.' This adds minimal value beyond the parameter name 'expr' and fails to explain expected format or constraints (e.g., allowed separators).

Input schemas describe structure but not intent. Descriptions should explain non-obvious 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 'Check cron string has exactly five fields,' clearly indicating the tool's purpose: validating a cron expression format. This distinguishes it from sibling tools like 'cron_describe' or 'cron_parse' that have different functions.

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

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

No guidance is given on when to use this tool versus alternatives such as 'cron_semantic_validate' or 'cron_validate_batch'. The agent receives no help in choosing among similar cron-related 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 carry the full burden. It only says 'batch semantic validate' but does not disclose whether it is read-only, what happens on validation failure, or any side effects. This is insufficient for safe invocation.

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

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

The description is highly concise (one sentence) but lacks structure and additional context. While every word earns its place, the terseness leaves gaps that require inference.

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

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

Given the lack of output schema and annotations, and the presence of similar sibling tools, the description is incomplete. It does not explain what 'semantic validate' means, what the output looks like, or when batch validation is appropriate over single validation.

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

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

The single parameter 'expressions' has no schema description (0% coverage). The description only states '5-field cron expressions' but gives no details on format, valid values, or examples. The tool name implies 5-field, but more explicit semantics are needed.

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

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

The description clearly states the tool validates cron expressions in batch, specifying 'semantic' and '5-field'. This distinguishes it from siblings like cron_validate (non-semantic or single) and cron_semantic_validate (likely single). However, it could explicitly contrast with those siblings.

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

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

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

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

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

Without annotations, the description carries the burden of disclosing behavior. It mentions parsing and flagging unsafe directives but does not explain what 'flag' means (e.g., return format), whether it throws errors on invalid input, or if it has side effects. 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?

A single concise sentence that effectively communicates the tool's purpose without unnecessary words. Well front-loaded.

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

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

The tool has no output schema, yet the description does not explain what the output contains (e.g., parsed directives, list of unsafe ones). For a simple tool, this omission reduces usefulness for an AI agent.

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

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

The description adds context that the single 'header' parameter is a Content-Security-Policy header, which helps beyond the schema (0% coverage). However, it does not specify expected format or 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 parses a Content-Security-Policy header and flags unsafe directives, using a specific verb and resource. It distinguishes from sibling tools, none of which specialize in CSP 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?

No guidance is provided on when to use this tool versus alternatives, nor when not to use it. The description only states what it does, without context for appropriate invocation.

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

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 key behaviors such as whether the first CSV row is treated as header, delimiter defaults, or handling of quoting/escaping. The minimal description leaves significant behavioral gaps.

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

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

The description is short with two sentences, but the second sentence largely repeats the first ('Convert CSV rows → JSON array of objects'). It is concise but not optimally structured, with some redundancy reducing efficiency.

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

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

Given the tool's simplicity (one parameter, no output schema), the description is incomplete. It fails to specify input format details (e.g., header row assumed, delimiter default) or output structure beyond 'row objects'. This leaves the agent with insufficient information for reliable 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 input schema has 0% description coverage for the 'text' parameter, and the tool description only mentions 'CSV text' without explaining the expected format, delimiter, or special cases. The description adds little meaning beyond the parameter name.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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 CSV text to a JSON array of row objects, using a specific verb and resource. However, it does not explicitly differentiate from sibling tools like 'csv_validate' or the reverse 'json_to_csv', so it lacks distinct sibling differentiation.

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

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

The description provides 'When: Convert CSV rows → JSON array of objects' which implies the usage context but offers no guidance on when not to use this tool or alternatives. There is no mention of prerequisites or exclusions, leaving the agent without clear decision criteria.

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

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

No annotations are provided, so the description should carry the burden of behavioral disclosure. It says 'Validate' but does not describe return behavior (e.g., boolean, error messages, or side effects). The lack of detail on what constitutes 'consistent' or what happens on failure reduces transparency.

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

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

The description is extremely concise with two short sentences, containing no redundant information. Every word adds value.

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

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

The tool has three parameters with no schema descriptions and no output schema. The description only covers the basic purpose, leaving out crucial details about input format requirements, validation outcomes, error handling, and return data. For a validation tool, this is insufficient.

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

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

Schema description coverage is 0%, so the description must compensate. However, it does not mention any of the three parameters (text, delimiter, has_header) or their roles. The schema provides names and defaults, but the description adds no meaning beyond what the tool name implies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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 CSV structure, focusing on consistent column counts and header. It distinguishes itself from sibling tools like csv_to_json and csv_validate_batch, and uses specific verbs 'Validate' and '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 a 'When' clause specifying to use the tool before import for column consistency checks. It does not explicitly mention when not to use it, but the context is clear.

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

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

Without annotations, the description should explain behavioral traits (e.g., rate update frequency, error handling for invalid currencies, API limits). It only mentions using ECB rates, omitting other 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?

A single concise sentence that conveys the core purpose efficiently. However, it could be slightly more structured but remains front-loaded and clear.

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

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

For a tool with 3 required parameters, no output schema, and no annotations, the description provides insufficient guidance. Missing information on output format, error states, and usage 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 has 3 parameters with 0% description coverage. The description does not add meaning beyond parameter names, e.g., no mention of ISO 4217 format, amount constraints, or required precision.

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

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

Description clearly states verb 'Convert', resource 'amount between currencies', and data source 'latest ECB rates', distinguishing it from sibling tools like currency_list and 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?

No guidance on when to use this tool versus alternatives (e.g., currency_list for listing currencies, currency_rates for rates only). The description does not specify prerequisites or exclusion conditions.

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?

Discloses data source and authentication requirement (no API key). No annotations provided, but description adequately covers behavior 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?

Single sentence, no wasted words. Front-loaded with purpose.

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

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

For a zero-parameter list tool with no output schema, the description is complete and sufficient.

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

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

Schema has 0 parameters (100% coverage), description adds value by specifying source and no API key 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?

Description clearly states verb 'List', resource 'supported fiat currencies', and adds context 'Frankfurter/ECB, no API key'. Distinguishes from siblings like currency_convert and 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?

Implies use for listing currencies, not converting or rates. No explicit exclusions, but context is clear given 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 carries full burden. It only mentions 'no API key' and the data source, but omits critical details like rate update frequency, whether rates are real-time, response format, error handling, or rate limits. For an external data fetch tool, this is insufficient.

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

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

The description is concise (one sentence) and front-loaded with key purpose and data source. However, it sacrifices some necessary detail for brevity. Overall, it is effective but could include more 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 and no annotations, the description leaves many gaps. It does not explain the return format, how to handle errors, or the scope of available currencies. For a simple tool this might be borderline, but for an agent to invoke it correctly, more details are 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 description does not mention any parameters. The input schema has two parameters (base and symbols) with only symbols having a description. The base parameter lacks documentation even in the schema. The description adds no value beyond what the schema provides.

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

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

The description clearly states the tool provides 'latest exchange rates' with a specific data source (Frankfurter ECB) and highlights no API key is required. This distinguishes it from siblings like currency_convert (which converts amounts) and currency_list (which lists available 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?

No explicit guidance on when to use this tool versus alternatives. For example, if a user needs to convert currencies, they should use currency_convert; if they need a list of available currencies, use currency_list. The description does not provide such 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?

The description explains the core transformation, but with no annotations, it fails to disclose error handling, accepted input variations (e.g., numeric strings vs. numeric), or whether it validates input. It implies a safe read operation but is not explicit.

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

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

The description is one short sentence, no wasted words, and front-loaded with the verb 'Parse'. It could benefit from a bit more detail without becoming verbose.

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

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

For a tool with no output schema, the description is insufficient. It mentions 'into UTC ISO + unix' but does not specify the return format (e.g., JSON object with keys, or something else). This leaves the agent uncertain about how to use 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?

With 0% schema coverage, the description adds basic meaning: value should be a Unix timestamp or ISO-8601 string. However, it does not specify the exact format (e.g., expected string representation of Unix timestamp, timezone handling in ISO-8601), 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 parses Unix timestamp or ISO-8601 into UTC ISO + unix, indicating a specific conversion action. However, it does not explicitly say it returns both formats, and it could be more detailed about the output structure.

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

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

No guidance on when to use this tool vs. sibling tools like time_convert or timezone_convert. Agent is left to infer 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 only mentions 'best-effort' to signal potential parse failures. It lacks details on output format, error behavior, or limitations for different ecosystem specifications.

Agents need to know what a tool does to the 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 with repetition ('Extract name@version' appears twice). Could be condensed and front-loaded with the 'When:' context.

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

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

The tool has no annotations nor output schema, and the description omits return format, error handling, and parameter details. This leaves the agent underinformed 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 description does not explain the 'text' or 'ecosystem' parameters. Given 0% schema coverage, this is a critical gap—the agent has no guidance on what text to provide or how ecosystem affects extraction.

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

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

The description clearly states the tool extracts name@version from specific file types (requirements/lockfile/go.mod/Cargo). This verb+resource combo is unique among siblings, though the phrase 'best-effort' is vague.

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

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

The description provides a 'When:' clause indicating suitable snippets, but lacks any when-not-to-use guidance or mention of alternative approaches.

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 such as network dependency, rate limits, error handling, or required permissions. The fact that it performs a network lookup is implied but not stated.

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

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

Description is a single concise sentence with no wasted words. It is front-loaded with 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 two parameters with 0% schema description coverage, no output schema, and no annotations, the description is incomplete. It does not describe the return format (e.g., record type, TTL, value), error cases (e.g., invalid domain, no records), or any additional context 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%. The description lists the record types but does not explain their meanings or how they affect the lookup. For example, doesn't clarify that 'ANY' may return all types. The enum values are self-explanatory for DNS-savvy users, but the description adds minimal value beyond the schema.

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

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

Description clearly states the tool performs DNS lookup for a domain and lists supported record types. However, it does not explicitly distinguish from related siblings like 'reverse_dns' or 'whois_lookup', though the specific record types provide implicit differentiation.

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

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

No guidance on when to use this tool versus alternatives. No prerequisites, exclusions, or contextual cues for selection among many sibling tools.

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

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

No annotations are provided, so the description must carry the full burden. It mentions what issues it checks for but does not disclose the output format, whether it modifies anything, or any other behavioral traits. This is insufficient for a linter tool.

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

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

The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the tool's purpose and scope.

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

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

Given the lack of output schema and annotations, the description should describe the return value of the lint operation. It does not, leaving the agent uncertain about how to interpret the result. This is a significant gap for a tool with a single parameter.

Complex tools with many parameters or behaviors need more documentation. Simple tools need 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 must compensate. It implies the 'text' parameter is the Dockerfile content, but does not elaborate on expected format or constraints. This is adequate but not rich.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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 'Lint' and the resource 'Dockerfile', and lists specific issue categories (root user, curl|sh, secrets). It effectively distinguishes from sibling tools that target other file types like GitHub Actions or Nginx configs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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 context is clear: use this tool when you need to lint a Dockerfile for security/style issues. Although no explicit exclusions or alternatives are provided, the sibling tools are for different file types, making the usage straightforward.

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 mentions 'best-effort eTLD', hinting at potential inaccuracies, but fails to disclose error handling (e.g., invalid input), return format, or whether the tool is idempotent.

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

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

The description is concise with two sentences, front-loading the verb and resource. However, the second sentence restates the first partially, adding slight redundancy. Overall efficient.

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

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

Given the tool's simplicity (one param, no output schema, no annotations), the description is incomplete. It does not specify the output structure (e.g., JSON fields), error behavior for invalid domains, or edge cases. An agent would need to infer expectations.

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

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

The input schema has 0% description coverage, and the tool description does not clarify the expected format of the 'domain' parameter (e.g., whether to include scheme, port, or just the domain itself). The word 'domain' gives minimal meaning, but no examples or constraints are provided.

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

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

The description clearly states the tool parses a domain into components like labels, TLD, registrable domain, and subdomain. It distinguishes the tool from sibling url_parse which handles full URLs, though it does not explicitly differentiate from other domain-related tools.

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

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

The description provides a 'When' clause indicating the tool should be used to split a domain, but it lacks guidance on when not to use it or alternative tools (e.g., url_parse for full URLs). It implies the context but no 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. It informs users that the tool accepts two input formats and returns seconds. However, it does not disclose error handling (e.g., behavior on invalid input), output precision, or any constraints like maximum duration length. This is adequate for a simple parser but could be more 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 short (two sentences) and front-loaded with the purpose and examples. The second sentence ('When: ...') is somewhat redundant, but the overall structure is efficient and easy to scan.

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

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

Given the tool's simplicity (1 parameter, no output schema, no nested objects), the description provides sufficient context: input format, output unit, and usage scenario. It does not elaborate on the exact return value, but for a parsing tool that returns a number of seconds, this is likely sufficient for an AI agent.

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

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

The schema has 0% description coverage for the single parameter 'value', so the description is essential. It adds critical meaning by explaining that the string can be ISO-8601 ('PnDTnHnMnS') or human-readable formats ('1h30m', '90s'), which is not conveyed by the schema alone.

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

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

The description clearly states the tool's purpose: parsing ISO-8601 and human-readable durations (with examples like '1h30m', '90s') to seconds. It distinguishes this tool from its siblings (none of which handle duration parsing), making it easy for an agent to select it for duration conversion tasks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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: Parse ISO-8601 / human durations to seconds.' line provides explicit context for when to use the tool. Although it does not mention when not to use it or suggest alternatives, the sibling tools are all different parsing/encoding utilities, so the usage scope is well-defined.

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 behavior. It only says 'validate syntax and common keys' but does not specify return format (e.g., boolean, error list), side effects, or behavior on invalid input. 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?

Very concise single sentence, front-loaded with the action. However, it is too brief and omits important details that could be included without harming conciseness (e.g., what 'common keys' means).

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

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

Given the simplicity of the tool (1 param, no output schema, no annotations), the description should at least mention what the output is (e.g., validation success/failure) and perhaps note what 'common keys' are validated. It does not, 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?

Schema description coverage is 0% for the single parameter 'text'. The description does not explain what the parameter represents (e.g., content of .editorconfig file as string), nor any constraints or format. It adds minimal value beyond the schema.

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

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

Description clearly states it validates .editorconfig syntax and common keys. The verb 'validate' and resource '.editorconfig' are specific and unambiguous. No sibling tool covers editorconfig, so differentiation is inherent.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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, no prerequisites, no exclusions. The description lacks any context about typical use cases or limitations.

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 must fully disclose behavior. It only states 'Validate email address format' and 'Syntax-check', but does not specify what validation entails (e.g., format rules), how results are returned, or responses for invalid inputs. This is insufficient for an agent to predict behavior reliably.

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

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

The description is extremely concise with one sentence containing the essential information. It avoids unnecessary words, earning high marks for conciseness. However, it could be slightly more structured (e.g., separating different aspects) without increasing length significantly.

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

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

Given the low complexity (one string parameter, no output schema), the description provides the basic purpose but lacks details about return format, error handling, or validation scope. It is sufficient for a trivial tool but could be more informative for an agent to handle edge cases.

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

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

The schema has 0% description coverage, and the description adds no extra meaning beyond the parameter name 'email'. The phrase 'single email address' merely restates the obvious. The description fails to compensate for the missing schema descriptions, offering no additional semantic value.

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

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

The description clearly states the verb 'Validate' and the resource 'email address format', and specifies the scope as a single email address. This distinguishes it from sibling tools like 'extract_emails' or other validation tools, making its purpose unambiguous.

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

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

The description includes a 'When:' clause indicating it is for syntax-checking a single email address. While it lacks explicit when-not-to-use instructions or alternatives, the context (no similar sibling for email validation) makes the usage clear.

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 burden. It states the output categories but does not disclose whether it parses .env format (key=value) or treats lines as strings, nor does it describe the output structure or handling of comments/blanks.

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

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

The description is concise at two sentences, but the second sentence 'When: ...' is redundant and could be integrated into the first. No uninformative 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 output schema, the description lists the types of differences (only_in_a, only_in_b, changed) but lacks specifics on the return format (e.g., array of objects, key-value mapping) and does not cover edge cases like keys missing in both files or malformed lines.

Complex tools with many parameters or behaviors need more documentation. Simple 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 implies that parameters 'a' and 'b' are .env file contents, but does not clarify whether they are file paths or raw strings. No additional parameter details are provided beyond the parameter 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?

Clearly states the verb 'Diff' and the specific resource '.env files'. Lists the output categories (only_in_a, only_in_b, changed values), which differentiates it from general text diff tools like text_diff.

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

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

No explicit guidance on when to use this tool versus alternatives (e.g., text_diff or env_parse). The 'When:' phrase merely restates the purpose rather than providing contextual usage advice.

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 behavior. It states a safe, read-only action (parsing) but does not detail handling of comments, multiline values, or edge cases. Basic transparency is present but not rich.

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

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

The description is a single, well-structured sentence with no wasted words. It conveys the essential information efficiently.

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

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

For a simple parsing tool with one parameter and no output schema, the description adequately explains input and output. However, it could be more complete by explicitly stating the return format (e.g., 'returns an object with key-value pairs').

Complex tools with many parameters or behaviors need more documentation. 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 0% schema description coverage, but the description adds meaning by specifying the expected format (.env/dotenv text). This compensates somewhat, though format details (syntax, comments) are missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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 '.env / dotenv text', with the outcome 'key-value variables'. This distinguishes it from sibling tools that parse other formats like INI or properties files.

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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., ini_parse, properties_parse). It does not mention when not to use it or any prerequisites.

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

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

No annotations provided. The description only says 'check' but doesn't specify return type (boolean? error?), error handling for missing keys, or whether it validates formatting of the text. Insufficient disclosure beyond basic purpose.

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

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

Single sentence, no fluff, efficiently conveys the core action and requirement (non-empty values).

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

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

While the tool is simple, the description omits output specification (e.g., returns boolean, list of missing keys, or throws error), which is important for an AI agent to know how to handle results. Adequate for basic understanding but incomplete.

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

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

Schema description coverage is 0%, so description must compensate. It implies 'text' is .env content and 'required' is key list, but doesn't specify the expected format of the text (e.g., key=value lines, newline separation) or constraints on keys. Lacks detail.

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

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

The description clearly states the tool checks a .env text for required keys with non-empty values. It differentiates from siblings like env_parse (which parses) and env_diff (diffs).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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 env_parse or manual checking. No context on prerequisites or typical use cases.

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

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

No annotations are provided, so the description must disclose behaviors. It only states extraction but does not mention return format, handling of invalid input, or limits. This leaves significant behavioral gaps.

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

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

Two sentences with no wasted words. The first sentence states purpose, the second gives usage context. Highly concise and front-loaded.

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

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

With no output schema and 0% schema coverage, the description should explain the return value and edge cases. It does not mention output format, such as whether it returns a list of strings or handles duplicates, leaving the tool underspecified.

Complex tools with many parameters or behaviors need more documentation. 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, and the description only implies that 'text' is the input. It does not specify encoding, size limits, or expected format, failing to add value beyond the schema.

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

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

The description clearly states 'Extract email addresses from text', which is a specific verb-resource combination. It distinguishes from sibling tools like 'email_validate' (validation) and 'extract_urls' (URL extraction).

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

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

The description provides a clear usage scenario: 'When: Pull email addresses from free text / logs.' It does not explicitly mention when not to use or list alternatives, but the context is adequate.

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. The description does not disclose behavioral details such as output format, handling of malformed URLs, or performance characteristics. The agent has minimal insight into what to expect beyond extraction.

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

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

The description is extremely concise with one sentence that front-loads the key information. 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 simple nature (one parameter, no output schema), the description is adequate but leaves gaps: no indication of output format (array vs line-separated) or how multiple URLs are handled. Slightly incomplete.

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

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

Schema description coverage is 0%. The description only adds 'arbitrary' to 'text', providing very little additional meaning beyond the schema 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 extracts HTTP/HTTPS URLs from text, specifying the protocol and resource. It distinguishes itself from sibling tools like url_parse which parses single URLs, and other extraction tools like extract_emails.

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

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

No guidance on when to use this tool vs. alternatives like regex or other extraction tools. No mention of 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 disclose all behavioral traits. It only states the basic operation, omitting details about return format, error handling, or what happens if the input has no frontmatter. This is insufficient for a tool with no output schema.

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

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

While the description is very short and front-loaded, it is under-specified for the task. Conciseness should not sacrifice necessary information; the description fails to provide essential details, making it more deficient than concise.

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

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

Given the simple input schema and lack of output schema, the description should still cover return format and error scenarios. The current text is incomplete, leaving gaps that may confuse an agent about expected outputs.

Complex tools with many parameters or behaviors need more documentation. 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 'text' has no description in the schema (0% coverage), and the tool description adds no additional semantic meaning, leaving the agent without guidance on expected input 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?

The description clearly states the action ('Parse YAML frontmatter from markdown') and specifies the delimiter format (--- ... ---), making the tool's purpose unambiguous and distinguishing it from 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?

The description includes a 'When' clause that explicitly indicates the tool's use case ('Split YAML frontmatter from markdown body'), providing clear guidance on when to invoke it, though it does not mention when not to use it or alternatives.

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

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

Description discloses specific checks performed (triggers, unpinned actions, curl|bash), but no annotations are provided. It does not state whether the tool modifies data, what the output format is, or any safety considerations. With no annotations, more detail is expected.

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

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

Extremely concise single sentence with no unnecessary words. Every part adds 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?

Tool has no output schema and description does not mention return format or behavior (e.g., error handling, output structure). For a linting tool, users need to know what the output looks like (list of issues, success indicator). Missing essential 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?

Only parameter 'text' has no description in schema (0% coverage) and description does not explain what the parameter expects (e.g., file content, path, URL). Description adds no semantic value beyond the schema.

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

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

Description clearly states it lints GitHub Actions workflow YAML and specifies what it checks (triggers, unpinned actions, curl|bash). This distinguishes it from sibling tools like yaml_validate which only validate YAML syntax.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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 yaml_validate or other linting tools. Does not mention prerequisites or 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 provided, and the description lacks details on how it performs the review (e.g., parsing, pattern matching), what happens on success/failure, or side effects. Minimal behavioral disclosure.

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

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

Single sentence, front-loaded with key information. No unnecessary words or repetition. Efficient.

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

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

Given the simple structure (one parameter, no output schema), the description is minimally adequate. It explains the tool's purpose but omits output format and possible results (e.g., list of missing ignores).

Complex tools with many parameters or behaviors need more documentation. Simple tools need 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% with no description for 'text'. The main description implies 'text' is the .gitignore content, adding some meaning. However, it does not specify format or constraints (e.g., multiline string). Baseline 3 with partial compensation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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 'Review' and the resource '.gitignore' along with specific missing ignores (.env, node_modules, keys). It distinguishes from sibling tools like gitignore_match, which checks pattern matching.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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 gitignore_match, or context like verifying a .gitignore file before committing.

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 fully. It only mentions 'best-effort' and handles ignore/negate, but omits return format, error behavior, or limitations (e.g., partial rule support).

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

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

The description is extremely concise—two short sentences. It is front-loaded with the core action and avoids unnecessary words. Every sentence is informative.

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

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

Despite simple inputs, no output schema exists, so the description should indicate the return type (e.g., boolean, list of matches). It does not. The 'best-effort' hint is vague. Description is incomplete for full agent understanding.

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

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

Schema coverage is 0% (no descriptions in schema). The description names 'paths' and 'gitignore' but offers no detail on format (e.g., gitignore string as lines, paths relative paths). Baseline is low; description adds minimal 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 matches paths against .gitignore rules, specifying 'ignore / negate' which adds nuance. However, it does not differentiate from sibling 'gitignore_check', leaving ambiguity about when to use which.

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

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

The description includes a 'When:' clause but only says 'Test paths against .gitignore rules (best-effort).' It provides no guidance on when not to use, what alternatives exist (e.g., gitignore_check), 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?

With no annotations provided, the description carries full burden but only states the parsing action. It does not disclose error handling, validation behavior, or whether network calls are made, leaving significant behavioral gaps.

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

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

The description is short (two sentences) but contains redundancy: the second sentence ('When: Parse git@ / https remotes into owner/repo') essentially repeats the first. More efficient consolidation would improve conciseness.

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

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

The tool has one parameter and no output schema. The description covers the core functionality and output format (host/owner/repo) but does not specify the return structure (object vs. string) or provide examples, leaving some ambiguity 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 description coverage is 0%, so the description must compensate. It specifies that the URL is a git remote in ssh/https format, adding meaning beyond the raw schema. However, it could be more explicit about expected formats (e.g., full URL vs. partial) and does not describe all potential 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 parses git remote URLs (ssh/https) into host/owner/repo. It distinguishes from sibling tools like url_parse by specifying 'git remote URL', making the purpose specific and unambiguous.

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

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

The description implicitly guides usage by saying 'When: Parse git@ / https remotes into owner/repo,' but it lacks explicit when-not-to-use conditions or alternatives among siblings (e.g., url_parse for non-git URLs).

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 behavioral traits. It only mentions 'gitignore-style fnmatch' hinting at pattern syntax but omits details like case sensitivity, path format, output behavior, or side effects. A more transparent description would explain what happens with no matches or how paths are resolved.

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

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

The description is a single, concise sentence front-loading the key action. However, it could benefit from additional structure (e.g., separating purpose and returns), but it remains efficient.

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

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

Given no output schema, the description should explain return values. It does not. The tool's behavior (e.g., returning matches or booleans) is unspecified. For a batch tool, this is a significant 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 0%, so the description must compensate. It names 'paths' and 'patterns' but adds no semantic detail (e.g., whether paths are absolute/relative, pattern syntax variants). The parameter names are self-explanatory but insufficient for correct usage.

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

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

The description clearly states 'Match paths against glob patterns (gitignore-style fnmatch),' specifying the verb (Match), resource (paths against glob patterns), and the pattern style. This distinguishes it from sibling tools like gitignore_match or gitignore_check, which are gitignore-specific.

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

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

No guidance on when to use this tool vs alternatives, such as gitignore_match. No mention of when not to use it, performance considerations, or batch size limits. The description is purely functional.

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 includes the term 'best-effort', implying potential incompleteness, which is a behavioral trait. However, it does not disclose other traits like performance, limits, or side effects.

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

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

The description is two sentences, front-loaded with the action and resource. It is concise and to the point. Could be slightly expanded to explain the parameter, but overall 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 one parameter and no output schema, the description is fairly complete. It specifies the input as a document and caveats with 'best-effort'. It does not detail output format or size considerations, but for a list tool, it covers essential aspects.

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

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

The input schema provides no description for the 'text' parameter (0% coverage). The description implies that 'text' is a GraphQL document by stating 'List GraphQL ops/types from a document', adding minimal meaning beyond the schema. More explicit guidance would improve.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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 'List' and the resource 'GraphQL query/mutation/subscription names and type defs'. It distinguishes itself from sibling tools like graphql_validate or graphql_schema_diff by focusing on listing operations from a document.

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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 indicating the context for use (listing GraphQL ops/types from a document). It does not explicitly mention when not to use or provide alternatives, but the context is clear enough for 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?

Without annotations, description notes focus on breaking changes (removals) but does not clarify if it detects other changes, output format, error handling, or behavior with invalid schemas.

Agents need to know what a tool does to the 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, 11 words, front-loaded 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?

No output schema and no description of return format. For a diff tool, missing output details (text, object, list of changes) is a significant gap. No annotations to compensate.

Complex tools with many parameters or behaviors need more documentation. Simple 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 'old' and 'new' with no descriptions; description implies they are schemas but does not specify format (string, file, URL) or provide examples. Schema coverage 0%, minimal 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?

Description clearly states verb 'diff', specific resource ('two GraphQL schemas'), and purpose ('removed types/fields (breaking changes)'). Distinguishes from siblings like graphql_validate and graphql_operations_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?

Implies usage when comparing GraphQL schemas for breaking changes, but no explicit guidance on when to use vs alternatives, prerequisites, or exclusion 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?

The description clarifies it performs parse-only validation, implying no side effects or network calls. With no annotations, this is adequate disclosure. However, it could mention that it does not execute the query or that invalid syntax triggers 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, front-loads the action and resource scope, with no extraneous words. It is highly concise and structured effectively.

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

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

For a one-parameter tool with no output schema, the description covers the basic purpose and scope. It could be improved by hinting at the output (e.g., returns whether valid or throws error). Otherwise, it is mostly 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%, so the description must compensate but only says 'Validate GraphQL query or schema SDL syntax.' It does not describe the 'text' parameter explicitly (e.g., expected content, format). The parameter remains unclear.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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, with a specific verb (validate) and resource. It distinguishes from sibling tools like graphql_operations_list or graphql_schema_diff by focusing on parsing/validation.

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

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

The description implies use for syntax checking ('parse only') but does not explicitly state when to use this tool versus alternatives like graphql_schema_diff for schema comparison or graphql_operations_list for operation extraction. No guidance on prerequisites or exclusions.

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

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

No annotations are provided, so the description must disclose all behavioral traits. It mentions case-insensitivity but omits critical details such as the return type (likely boolean), behavior on invalid inputs, or any side effects. This leaves significant ambiguity.

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

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

The description is a single, efficient sentence (6 words) with no filler or redundancy. It front-loads the core purpose.

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

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

Given the tool's simplicity (2 string params, no output schema), the description is too minimal. It fails to explain the output, input format expectations, or any edge cases, leaving the agent underinformed.

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

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

Schema coverage is 0%, placing full burden on the description. It identifies the parameters as 'hash digests' but provides no additional meaning about format, algorithm, or constraints beyond the generic 'string' type from the schema.

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

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

The description clearly states the action ('compare') and the resource ('two hash digests'), with a specific behavior ('case-insensitive'). This distinguishes it from sibling tools like hash_md5 or hash_sha256 which generate hashes, not compare 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?

The description implies the use case (comparing two hash digests) but does not explicitly state when to use this tool versus alternatives like hash verification tools, nor does it mention prerequisites or exclusions.

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

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

No annotations provided, so description shoulders burden. It describes the operation but does not disclose behavior beyond purpose (e.g., output format, empty string 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?

Two short, front-loaded sentences with no filler. Every word adds value.

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

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

For a simple one-parameter tool with no output schema, description covers purpose and usage context sufficiently. Could mention return format, but not necessary.

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

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

Schema has 1 param with 0% description coverage. Description adds 'UTF-8 text' clarifying encoding, which is helpful. However, most meaning is clear from parameter name.

Input schemas describe structure but not intent. Descriptions should explain 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 (hash), resource (text), and output (MD5 hex digest). Distinguishes from sibling hash tools by specifying non-crypto use case.

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

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

Explicitly states when to use: 'MD5 digest (non-crypto integrity / legacy checksums)', implying not for security. No alternative named but context is clear.

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. It does not disclose any behavioral traits such as handling of empty strings, encoding assumptions, or determinism. Minimal information beyond the name.

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

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

Extremely concise at three words. No unnecessary information. Front-loads the purpose. Could be considered too brief, but appropriate for a simple hash 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 one-parameter tool with no output schema, the description minimally covers what it does. However, given the lack of annotations and parameter descriptions, it should provide more context about input limits or output format confirmation.

Complex tools with many parameters or behaviors need more documentation. Simple 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 one parameter 'text' with 0% description coverage. The description adds no additional meaning beyond the parameter name and type. Fails to compensate for missing schema descriptions.

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

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

The description 'SHA256 hex digest' is highly specific, stating the algorithm (SHA256) and output format (hex digest). It clearly distinguishes from sibling tools like hash_md5 and hash_sha512.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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 bcrypt_hash or hash_compare. No mention of use cases, constraints, or when to choose a different hash algorithm.

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 only mentions 'hex digest' implying output format. No annotations exist, so the description should disclose behavioral traits like algorithm properties or security implications. It does not, leaving the agent to infer behavior from the algorithm name alone.

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

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

The description is extremely concise (3 words), which is good for brevity but lacks essential detail. It front-loads the algorithm but is too terse to be fully informative.

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

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

Given the tool's simplicity and lack of annotations or output schema, the description should at least confirm the output format and any constraints. It only partially does so, leaving gaps about expected input format and output representation.

Complex tools with many parameters or behaviors need more documentation. 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 compensate by explaining the 'text' parameter. It does not; the parameter's purpose is only inferred from the tool name. The description adds no value 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 'SHA512 hex digest' clearly states the tool computes a SHA-512 hash and outputs a hexadecimal string. It is specific to the hash function and distinguishes it from siblings like hash_md5 or hash_sha256 by naming the algorithm. However, it could be more explicit about the action.

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

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

No guidance is provided on when to use this tool versus other hash functions (e.g., when security or speed considerations matter). The description lacks context for selection 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. The description only states the transformation but lacks details on error handling (e.g., invalid hex input), case sensitivity, whitespace handling, or whether UTF-8 encoding is strict.

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

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

Very concise single phrase. Front-loaded but overly minimal; leaves out important details that would improve usability without adding much length.

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

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

For a simple single-parameter tool, the description covers the basic input-output relationship. However, no output schema exists, and the description only implies the output format. Lacks completeness for robust use.

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

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

Schema description coverage is 0%, and the description does not explain the input parameter 'text' (e.g., its format as a hex string). Adds no 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 'Hex string to UTF-8 text' clearly states the tool's function: converting a hex string to UTF-8 text. It distinguishes from the sibling hex_encode (which does the reverse).

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

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

No usage guidance provided. Does not specify when to use this tool vs alternatives (e.g., base64_decode, hex_encode). No when-to-use or when-not-to-use information.

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

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

No annotations provided, so description carries full burden. It describes the core transformation but omits details like output format (e.g., lowercase/uppercase, presence of 0x prefix) and error handling for invalid UTF-8 input. Adequate for a simple pure function.

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

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

A single, clear sentence with no unnecessary words. Efficiently communicates the tool's function.

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

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

For a simple transformation with one parameter and no output schema, the description is mostly sufficient but could specify the exact output format (e.g., continuous hex string, case) and error behavior. Adequate but not thorough.

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

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

Schema description coverage is 0%, so description must add value. It specifies 'text' parameter expects UTF-8 input, but does not clarify case sensitivity, length limits, or allowed characters. Baseline 3 for a single required 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 'UTF-8 text to hex string' clearly states the verb (convert), resource (UTF-8 text), and result (hex string). It distinguishes from siblings like hex_decode (reverse) and base64_encode (different encoding).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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 base64_encode or hex_decode. Missing context such as preferred use cases or avoided 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, the description partially discloses behavior by listing algorithms and output encoding, but omits details like deterministic nature, potential errors (e.g., invalid algorithm), or security considerations (e.g., secret handling). It adds moderate context beyond the schema.

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

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

The description is a single concise sentence that front-loads purpose and key details. While efficient, it could be slightly expanded to cover parameter semantics without becoming verbose.

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

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

For a simple cryptographic tool with no output schema or annotations, the description covers essential aspects (algorithm, output format) but lacks detail on error handling, default behavior, and return format, making it adequate but not comprehensive.

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

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

Schema description coverage is 0%, so the description must compensate. It explains 'algorithm' and 'encoding' via the listed options but does not clarify 'secret' (the key) or 'message' (the data) beyond their names, leaving half the parameters underdocumented.

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

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

The description clearly states the tool performs HMAC signing on a message, specifies supported algorithms (sha1/sha256/sha512) and output formats (hex/base64), distinguishing it from sibling tools like hmac_verify (verification) and hash functions (no secret).

Agents choose between tools based on descriptions. A clear purpose with a specific verb 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 hmac_verify, jwt_sign, or simple hashing. It lacks explicit conditions, exclusions, or references 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 provided, and the description omits behavioral details such as return value (e.g., boolean or error), side effects, or algorithm support beyond default sha256.

Agents need to know what a tool does to the world before calling it. Descriptions 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 under-specified for a verification tool; lacks key details needed for correct usage.

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

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

Given no output schema, no annotations, and 4 parameters at 0% coverage, the description is grossly incomplete; an agent lacks essential information on output, algorithm variations, and error handling.

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

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

With 0% schema coverage, the description only clarifies the signature format (hex or base64) but fails to explain secret, message, or algorithm parameters, leaving them opaque.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and 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: 'Verify HMAC signature' and specifies input formats (hex or base64), distinguishing it from sibling hmac_sign.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource 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 hmac_sign or jwt_verify. The description only states what it does without 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 provided, so description must carry burden. Only states basic parse action; lacks details on handling comments, blank lines, multiple hostnames, error handling, or return format. Significant gaps.

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

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

Two short sentences with no redundancies. Efficiently conveys the core purpose 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 annotations, no output schema, and 0% schema description coverage, description is too sparse. Missing information about return structure, valid input, and edge cases. Incomplete 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?

Single parameter 'text' with no schema description. Description does not elaborate on expected input format (e.g., content of hosts file, required structure). Parameter semantics are vague.

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

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

Clearly states the tool parses /etc/hosts style files into IP and hostname entries. This distinguishes it from sibling parsing tools like ini_parse or csv_to_json by specifying the exact format and output.

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

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

Implied usage when dealing with /etc/hosts style files, but no explicit when-not-to-use or alternative tools. Siblings include many parsers but no direct comparison.

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 cover behavior. It only says 'Unescape HTML entities' without details on supported entity types, error handling, or output format.

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

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

The description is a single concise sentence with no wasted words. It is front-loaded and efficient, though slightly under-specified.

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

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

Given no output schema and no annotations, the description lacks details on return value, edge cases, and supported entities. It minimally conveys the core purpose but is incomplete for a robust tool.

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

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

Schema coverage is 0%, and the description does not elaborate on the 'text' parameter beyond its name. No added value over the schema for a single string 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 'Unescape HTML entities' clearly states the verb (unescape) and resource (HTML entities), effectively distinguishing it from sibling tools like html_encode and html_security_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 explicit guidance on when to use this tool versus alternatives. The purpose is implied but not explicitly stated; for a simple tool, it's acceptable but could mention it is the inverse of html_encode.

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 gives a basic statement. It does not disclose what characters are escaped, edge cases, or the behavior for invalid input.

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

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

The description is very concise with a single sentence, but it is too brief for a utility tool. It could include a bit more detail without becoming verbose.

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

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

Given the tool has one parameter and no output schema, the description lacks completeness. It does not mention the return value, encoding specifics, or how it compares to similar tools.

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

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

Schema description coverage is 0%, and the description adds no additional meaning beyond the parameter name 'text'. It does not explain the expected format or content of the 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?

The description 'Escape HTML entities' clearly states the tool's function with a specific verb and resource. It distinguishes itself from sibling tools like html_decode and html_security_scan by focusing on escaping.

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

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

No guidance is provided on when to use this tool versus alternatives like html_decode or html_security_scan. There is no context about prerequisites or exclusions.

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

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

With no annotations, the description carries full responsibility. It discloses the heuristic nature and mentions patterns, but critically omits what the tool returns (e.g., matched patterns, a boolean, or a report). The output behavior is unclear, which is a significant gap for a scanning 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 two concise sentences with no superfluous words. It front-loads the core purpose and adds an important caveat. Every word earns its place.

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

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

Given the tool's simplicity (one param, no output schema), the description covers purpose, patterns, and limitations. However, the lack of output specification makes it incomplete for an agent to fully understand the tool's behavior. It is minimally complete but has a notable 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?

The single parameter 'text' has 0% schema description coverage. The tool description implicitly clarifies that 'text' is the HTML to scan, adding minimal semantics. However, no details on encoding, limits, or allowed characters are provided. This is adequate but not thorough.

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

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

The description clearly states 'Scan HTML for XSS-prone patterns', listing specific patterns like javascript: URLs, inline handlers, and eval. It distinguishes from sibling tools such as html_encode or html_to_markdown by focusing on security scanning. The verb 'scan' and resource 'HTML' are specific, and the heuristic note adds nuance.

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

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

The description does not provide explicit guidance on when to use this tool versus alternatives like sql_danger_scan. It only implies usage for XSS scanning. No exclusions or context about prerequisites are given, leaving the agent to infer appropriate usage from the tool name alone.

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

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

No annotations provided. Description only states the conversion action without detailing safety, side effects, handling of malformed HTML, output format, or any limitations. Agent has no awareness of behavior beyond the basic operation.

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

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

Extremely concise (two sentences) and front-loaded with purpose. Every sentence earns its place, but could benefit from a more structured breakdown of parameters or behavior.

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

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

Given the simplicity of the tool (one parameter, no output schema), the description is minimally adequate. It covers purpose and usage context, but lacks parameter details and behavior transparency, leaving gaps for an agent to fill.

Complex tools with many parameters or behaviors need more documentation. Simple 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% coverage for parameter descriptions. The tool description does not elaborate on the 'html' parameter, leaving the agent with only the type (string) and no additional context about format, encoding, or constraints.

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

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

Clearly states conversion from HTML to Markdown with a specific usage context ('for docs the agent edits'). Distinguishes from reverse sibling markdown_to_html, but does not explicitly differentiate from other sibling tools like html_decode.

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

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

Provides a clear 'When' clause indicating use case for converting HTML to Markdown for agent-edited docs. Lacks explicit when-not-to-use or alternatives, but context is sufficient for basic guidance.

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