Server Quality Checklist

Tool Scores

• build_codefactor_promptC
  2.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description must fully disclose behavior. It only states the output is a prompt, but does not explain how it uses the URL, HTML, or other parameters. There is no mention of side effects, data fetching, or any disclaimers.

  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?

  A single sentence, front-loaded with the verb and resource. No wasted words, but could benefit from slightly more detail without becoming verbose.

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

  Completeness2/5

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

  With no output schema and 9 parameters, the description is too brief. It does not explain the prompt structure, how parameters affect output, or the interaction between url and html. This leaves agents with insufficient context.

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

  Parameters3/5

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

  Schema description coverage is 100%, so each parameter already has a description. The tool description adds no extra meaning beyond what the schema provides, meeting the baseline.

  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 has a specific verb 'Build' and resource 'AI-facing prompt', clarifying the output. It distinguishes from sibling tools like 'fetch_codefactor_issues' which fetch raw data, and 'summarize_codefactor_issues' which presumably produce summaries. However, 'AI-facing prompt' is somewhat ambiguous.

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

  Usage Guidelines2/5

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

  No guidance on when to use this tool versus siblings. The description does not indicate prerequisites, such as needing to fetch issues first, or when a prompt is needed instead of raw issues.

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

• summarize_codefactor_issuesC
  2.9/5.0
  Behavior2/5

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

  Without annotations, the description does not disclose behavioral traits such as network requests, authentication needs (cookie), or the impact of parameters like allPages or maxPages. It only states the 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.

  Conciseness4/5

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

  The description is a single sentence that is front-loaded and to the point. It is concise, though it could be slightly expanded to improve clarity.

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

  Completeness2/5

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

  Given the complexity (9 parameters, no output schema, no annotations), the description is incomplete. It does not explain the return structure or how parameters influence the summary, leaving agents with insufficient context.

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

  Parameters3/5

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

  The input schema has 100% parameter description coverage, so the schema itself explains each parameter. The tool description adds no additional semantic value beyond 'compact Markdown summary', which is adequate but not enhanced.

  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 indicates the tool returns a compact Markdown summary of CodeFactor issues, distinguishing it from sibling tools that fetch raw data or parse HTML. However, it could be more specific about the nature of the summary.

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives like fetch_codefactor_issues or parse_codefactor_html. It lacks explicit context for selection.

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

• parse_codefactor_htmlB
  3.1/5.0
  Behavior2/5

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

  No annotations are provided, so the description bears full responsibility. It only says 'parse and return normalized issues' without disclosing behavior like input validation, error handling, side effects, or output format details (e.g., what 'normalized' means).

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

  Conciseness4/5

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

  The description is a single sentence with 12 words, very concise. It is front-loaded with the primary action. However, it could benefit from slightly more structure (e.g., mentioning output or usage hint).

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

  Completeness2/5

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

  With 5 parameters, no output schema, and no annotations, the description is too sparse. It omits return value details, error scenarios, and how to effectively use optional filters like category or filePathIncludes. Inadequate for a tool of this complexity.

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

  Parameters3/5

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

  Schema description coverage is 100%, so baseline is 3. The description does not add extra meaning beyond the schema. It does not explain how parameters like category affect output or the relationship between input and output.

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

  Purpose5/5

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

  The description clearly states the tool's action ('Parse') and resource ('CodeFactor repository issues HTML response'), with a specific output ('return normalized issues'). It distinguishes from siblings like fetch_codefactor_issues (fetching) and summarize_codefactor_issues (summarizing).

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

  Usage Guidelines2/5

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

  The description provides no guidance on when to use this tool versus alternatives (e.g., after fetch_codefactor_issues, before summarize_codefactor_issues). No explicit context 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.

• fetch_codefactor_issuesB
  3.3/5.0
  Behavior2/5

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

  No annotations are provided, so the description must fully disclose behavior, but it only mentions fetching and normalization. It omits authentication, rate limits, error handling, pagination, and other behavioral traits, leaving 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.

  Conciseness4/5

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

  The description is a single concise sentence, front-loaded with the core action. It is efficient but could be slightly more informative without becoming verbose, hence a 4.

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

  Completeness2/5

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

  With eight parameters, no output schema, and no annotations, the description is insufficient. It fails to explain how parameters interact (e.g., maxPages with allPages), what 'normalized issue data' means, or provide an overall workflow context.

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

  Parameters3/5

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

  The input schema has 100% description coverage, so the baseline is 3. The description adds no extra parameter context beyond the schema, which already documents all eight parameters with descriptions.

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

  Purpose5/5

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

  The description clearly states the verb 'Fetch', the resource 'CodeFactor repository issues', and includes 'normalized issue data', distinguishing it from sibling tools like build_codefactor_prompt, parse_codefactor_html, and summarize_codefactor_issues.

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

  Usage Guidelines3/5

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

  The description implies usage as a fetch tool but provides no explicit guidance on when to use it versus alternatives, nor does it mention prerequisites or when not to use it.

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