Server Quality Checklist

Tool Scores

• generate_badgesB
  3.4/5.0
  Behavior5/5

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

  No annotations are provided, so the description carries full burden. It extensively covers side effects (none), authentication (no auth required for basic, pro tier needs API key), rate limits (10/day free), error handling, idempotency, and data privacy. This is comprehensive and exceeds typical detail.

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

  Conciseness2/5

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

  The description is verbose and contains redundancy. The 'Behavior' section at the top largely overlaps with the later 'Behavioral Transparency' section. The 'Args' section is a repetitive list with generic descriptions. The structure could be much more concise and front-loaded with only essential info.

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

  Completeness2/5

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

  While behavioral transparency is well covered, the description fails to explain parameter semantics and does not mention that the output is markdown (even though output schema exists). For a tool with 6 parameters and 0% schema coverage, the description does not provide sufficient context for an agent to correctly invoke it.

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

  Parameters1/5

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

  Schema coverage is 0% (no descriptions in input schema). The description's 'Args' section merely restates parameter names with the generic phrase 'The ... to analyze or process,' which adds no meaning. It fails to explain what each parameter means in the context of badge generation (e.g., owner as GitHub owner).

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

  Purpose5/5

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

  The description clearly states the tool's purpose: 'Generate shield.io badge markdown for a GitHub repository.' This is a specific verb+resource combination that distinguishes it from sibling tools (analyze_project, generate_readme, suggest_sections) which focus on analysis or other generation tasks.

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

  Usage Guidelines3/5

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

  The description includes 'When to use' and 'When NOT to use' sections, but the usage guidance is generic and misaligned with the actual tool. It suggests using for 'structured analysis or classification of inputs against established frameworks,' which does not match badge generation. No alternatives are discussed relative to siblings.

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

• generate_readmeA
  4/5.0
  Behavior5/5

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

  With no annotations provided, the description carries full burden and exceeds expectations. It details side effects (read-only, no external modification), authentication (none for basic, api_key for higher tiers), rate limits (10/day free, unlimited pro), error handling (structured errors), idempotency (fully idempotent), and data privacy (no storage). No contradictions with annotations since none exist.

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

  Conciseness3/5

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

  The description is well-structured with clear sections, but contains redundant content. The 'Behavior:' and 'Behavioral Transparency:' sections overlap significantly, and the 'Args' section is repetitive. It could be trimmed by merging the behavioral sections and removing the generic 'Args' descriptions, which add no value.

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

  Completeness3/5

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

  While behavioral transparency is thorough, parameter semantics are weak. The output schema exists but the description does not explain the return format (e.g., plain markdown, structured object). Given the tool's purpose, the description is moderately complete but lacks clarity on what the output looks like and how parameters shape it.

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

  Parameters2/5

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

  Schema description coverage is 0%, so the description must compensate. The 'Args' section only repeats parameter names and types, adding generic phrases like 'The ... to analyze or process.' This adds no meaningful context beyond the schema. For example, 'project_name' is not explained as the name of the project for which the README is generated. This is a significant gap.

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

  Purpose5/5

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

  The description clearly states 'Generate a complete README.md from project metadata including sections for install, usage, API, and contributing.' This is a specific verb+resource combination that distinguishes it from sibling tools like analyze_project, generate_badges, and suggest_sections, which focus on analysis or partial generation.

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

  Usage Guidelines4/5

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

  The description includes explicit 'When to use' and 'When NOT to use' sections. It advises using the tool for structured analysis or classification against standards, and warns against real-time production decision-making without review. However, it does not directly compare to siblings, leaving some ambiguity about when to choose this over alternatives.

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

• suggest_sectionsA
  4.3/5.0
  Behavior5/5

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

  With no annotations provided, the description fully covers side effects (read-only, no side effects), authentication, rate limits, error handling, idempotency, and data privacy, exceeding the typical burden.

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

  Conciseness4/5

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

  Well-structured with clear headings (Behavior, When to use, etc.), but the behavioral transparency section repeats some information from the Behavior section, making it slightly verbose.

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

  Completeness5/5

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

  Covers all necessary aspects: input semantics (though weakly), behavior, authentication, rate limits, error handling, idempotency, and data privacy. The presence of an output schema reduces the need for return value descriptions.

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

  Parameters2/5

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

  The 'Args' section merely repeats parameter names with generic phrases like 'The ... to analyze or process,' adding no meaningful information beyond what the input schema provides. With 0% schema coverage, the description fails to compensate.

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

  Purpose5/5

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

  The description clearly states the tool suggests README sections based on project type and capabilities, distinguishing it from sibling tools like generate_readme (which generates full README) and generate_badges.

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

  Usage Guidelines4/5

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

  Includes explicit 'When to use' and 'When NOT to use' sections, providing context for appropriate usage. However, it does not directly contrast with the sibling tools, which would strengthen guidance.

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

• analyze_projectA
  4.4/5.0
  Behavior5/5

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

  No annotations are provided, so the description fully covers behavioral traits: read-only/stateless, authentication requirements, rate limits, error handling, idempotency, and data privacy. This is comprehensive beyond typical annotations.

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

  Conciseness3/5

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

  The description is well-structured with sections, but it is verbose and redundant: the 'Args' section repeats schema info, and the 'Behavioral Transparency' section partially duplicates the 'Behavior' section. Each sentence could be more focused.

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

  Completeness5/5

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

  Despite the weak parameter semantics, the description comprehensively covers purpose, usage, side effects, and behavioral details. With an output schema present, return values don't need explanation. The tool's complexity (3 params, 1 required) is adequately addressed.

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

  Parameters2/5

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

  Schema description coverage is 0% and the description's 'Args' section merely restates parameter names with generic phrases ('The file list to analyze or process'), adding no meaningful constraints, formats, or examples. Given the lack of schema descriptions, the description fails to compensate.

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

  Purpose5/5

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

  The description clearly states the tool's purpose: analyze project structure from a file list to recommend README sections and detect project type. This specific verb+resource distinguishes it from sibling tools like generate_readme, which focus on generation.

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

  Usage Guidelines5/5

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

  Explicit 'When to use' and 'When NOT to use' sections provide clear guidance: use for structured analysis, not for real-time decisions without human review. This helps the agent decide between siblings.

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