Server Quality Checklist

Tool Scores

• generate_commit_messageA
  3.8/5.0
  Behavior5/5

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

  With no annotations provided, the description carries the full burden. It includes a dedicated 'Behavioral Transparency' section covering read-only operation, no side effects, deterministic output, rate limits, error handling, idempotency, and data privacy. This is comprehensive.

  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-organized with sections and bullet points, but contains redundancy (e.g., 'Behavior' paragraph overlaps with 'Behavioral Transparency') and a verbose 'Args' section that provides no useful information. Could be more concise.

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

  Completeness3/5

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

  The behavioral aspects are well-covered, but the lack of parameter explanation is a significant gap. The output schema exists, so return value details are not required, but the description could mention the output format. Overall, incomplete due to poor parameter semantics.

  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 description coverage is 0%. The 'Args' section merely restates parameter names and types without adding meaning (e.g., 'changes_description (str): The changes description to analyze or process.'). This adds no value over the schema.

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

  Purpose5/5

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

  The description clearly states the tool generates a conventional commit message from a description, with auto-detection of type, scope, and breaking changes. This distinguishes it from siblings like 'analyze_diff' or 'suggest_type'.

  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, advising use for structured analysis and cautioning against production use without human review. However, it does not directly compare to sibling tools.

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

• validate_conventionalA
  3.8/5.0
  Behavior5/5

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

  With no annotations, the description carries full burden and excels: details side effects (none), authentication, rate limits, error handling, idempotency, and data privacy. This is comprehensive and meets the highest standard.

  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?

  Well-structured with clear sections, but repetitive (e.g., Behavior and Behavioral Transparency overlap). Could be more concise while retaining completeness. Still, it is organized and front-loaded.

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

  Completeness4/5

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

  Given the presence of an output schema, description covers purpose, usage, behavior, and parameters adequately. No major gaps. Could mention expected output format briefly, but output schema presumably handles that.

  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 coverage is 0%, so description must compensate. The Args section is minimal: 'message: The message to analyze or process.' and 'api_key: The api key to analyze or process.' Adds little beyond the parameter names. No format, constraints, or defaults explained.

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

  Purpose4/5

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

  The description clearly states the tool validates commit messages against the Conventional Commits spec. It specifies the verb (validate) and resource (commit message) and reports issues. However, it does not explicitly differentiate from sibling tools like analyze_diff or generate_commit_message, though the purpose is distinct enough.

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

  Usage Guidelines4/5

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

  Provides explicit 'When to use' and 'When NOT to use' sections, advising use for structured analysis against standards and cautioning against real-time production decisions without human review. Lacks reference to alternative tools but gives good context.

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

• analyze_diffA
  4.1/5.0
  Behavior5/5

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

  With no annotations provided, the description excels by covering side effects (read-only, no external modifications), authentication (none for basic, API key for pro), rate limits (10/day free, unlimited pro with header details), error handling (structured errors), idempotency (fully idempotent), and data privacy (no storage/logging). This is exceptionally thorough.

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

  Conciseness4/5

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

  The description is well-structured with clear sections (Behavior, When to use, When NOT to use, Args, Behavioral Transparency). The purpose is front-loaded. However, there is some redundancy between the 'Behavior' and 'Behavioral Transparency' sections, making it slightly less concise than ideal.

  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?

  Given the tool's moderate complexity (2 parameters, 1 required), the presence of an output schema (so return values are covered), and the comprehensive behavioral transparency section, the description is nearly complete. It covers purpose, usage, side effects, auth, rate limits, error handling, idempotency, and privacy, leaving no major gaps.

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

  Parameters3/5

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

  Schema description coverage is 0%, so the description must compensate. It lists parameters in the 'Args' section but only repeats names and types without adding meaningful semantics. The main description clarifies diff_text's purpose, and api_key is partly explained in the Behavioral Transparency section. Overall, compensation is partial but not complete, warranting a 3.

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

  Purpose4/5

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

  The description clearly states it parses a git diff and produces a structured summary with specific outputs (files changed, additions, deletions, suggested commit type). The 'When to use' section is generic and does not explicitly distinguish from sibling tools like suggest_type, which also deals with commit types, but the main purpose is well-defined with a specific verb and resource.

  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, providing guidance on appropriate contexts and cautioning against real-time production use without human review. However, it does not mention alternatives or explicitly contrast with sibling tools, so a 4 is appropriate.

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

• suggest_typeA
  4.1/5.0
  Behavior5/5

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

  Without annotations, the description carries full burden and excels: it declares read-only, stateless, idempotent, no side effects, authentication requirements (none for basic, key for Pro), rate limits (10/day free, unlimited Pro), error handling (structured errors), and data privacy. This comprehensive disclosure exceeds typical requirements.

  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 labeled sections but excessively verbose. The 'Behavioral Transparency' section repeats information from earlier 'Behavior' section. Approximately 50% of the text could be trimmed without losing meaning, making it less efficient for an AI agent to parse.

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

  Completeness4/5

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

  Given the presence of an output schema (not shown), the description appropriately avoids detailing return values. It covers purpose, usage, parameters, and extensive behavioral details. Minor gap: rate limits and authentication details are split between sections. Still, it provides a complete picture for a tool of moderate complexity.

  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 provides minimal descriptions: 'description (str): The description to analyze or process' and 'api_key (str): The api key to analyze or process.' Given 0% schema description coverage, these are insufficient—they don't clarify expected format, how the key is used, or that Pro requires an environment variable (not the parameter). The parameter meaning is ambiguous.

  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: 'Suggest the best conventional commit type for a change description with confidence scoring.' This distinctively identifies the tool's purpose and differentiates it from siblings like analyze_diff, generate_commit_message, and validate_conventional, which cover other aspects of commit analysis.

  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 'When to use' and 'When NOT to use' sections, providing context: use for structured analysis/classification, not for real-time production decisions without human review. However, it does not explicitly contrast with siblings, leaving some ambiguity about when to prefer this over analyze_diff or validate_conventional.

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