Server Quality Checklist

Tool Scores

• search_docsA
  4.1/5.0
  Behavior4/5

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

  Annotations indicate read-only and idempotent. Description adds that omitting version searches all versions and that results have a version field for use with get_docs. No contradictions.

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

  Conciseness5/5

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

  Three sentences, 57 words, front-loaded with purpose, then specific usage. Every sentence adds value with no redundancy.

  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 output schema exists and annotations are present, the description adequately covers usage. Mentions sibling tool get_docs for consistency, but could clarify relationship with other siblings.

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

  Parameters4/5

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

  Schema coverage is 100%, but description adds usage context for kind and clarifies that omitting version means all versions (not just 'latest' as schema implies). Provides extra value beyond schema.

  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 'Search Python documentation' with specific verb and resource. It provides details on kind values but does not explicitly differentiate from sibling tools like get_docs or list_versions.

  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?

  Explicit guidance on when to use each kind ('symbol' for API lookups, 'example' for code samples, 'auto' otherwise) and on version handling (omitting searches all versions, using version from hits for get_docs). No explicit when-not to use, 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.

• detect_python_versionA
  4.3/5.0
  Behavior4/5

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

  Annotations already indicate read-only, idempotent, and non-destructive. The description adds value by detailing what the tool returns (detected version, method of detection, and match status), providing context beyond annotations.

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

  Conciseness5/5

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

  Three sentences, front-loaded with the main purpose. Every sentence adds information without redundancy. Extremely efficient.

  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?

  With an output schema present, the description correctly avoids repeating return details. It covers the tool's core function and expected outputs, providing sufficient completeness for a simple detection tool.

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

  Parameters4/5

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

  No parameters exist (0 params, 100% schema coverage baseline). The description does not need to add parameter details, so a baseline of 4 is appropriate.

  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 it detects the Python version in the user's environment, which is a specific verb-resource pair. It distinguishes itself from sibling tools like list_versions or compare_versions by focusing on the local environment.

  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?

  No explicit guidance on when to use versus alternatives. While the purpose is clear, an agent could benefit from knowing this is for detecting the current environment's version, not for comparing or listing all versions.

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

• list_versionsA
  4.3/5.0
  Behavior3/5

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

  Annotations already declare readOnlyHint, destructiveHint, idempotentHint, and openWorldHint. The description adds minimal behavioral context by specifying the scope 'in this index', but does not disclose additional traits like return format or pagination.

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

  Conciseness5/5

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

  The description is a single sentence that is front-loaded with the action and resource. Every word is necessary and there is no redundancy.

  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 has no parameters, annotations cover safety, and an output schema exists, the description is complete enough. It states the core purpose without missing crucial information.

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

  Parameters4/5

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

  The tool has zero parameters, so schema coverage is 100%. The description adds no parameter-specific meaning beyond what the schema provides, but baseline is 4 for zero-parameter tools.

  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 uses a specific verb 'List' and identifies the resource 'Python documentation versions' with scope 'in this index'. It clearly distinguishes this tool from siblings like compare_versions or search_docs.

  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 implies usage when an agent needs to know available versions in this index, but does not explicitly state when to use or not use it versus alternatives. It provides clear 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.

• lookup_package_docsA
  4.3/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint, idempotentHint, etc. Description adds that it only queries PyPI's JSON API and returns official metadata and project URLs, providing behavioral context beyond annotations. No contradiction.

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

  Conciseness5/5

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

  Two short paragraphs, front-loaded with purpose, followed by clarifying scope. Every sentence adds value with no wasted words.

  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?

  With one simple parameter, high schema coverage, output schema exists, and annotations covering safety, the description provides all necessary context: what it does, its data source, and its limitations. Complete for the tool's 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 coverage is 100% and the schema already describes the 'package' parameter as 'PyPI package/project name'. The description does not add new meaning beyond what the schema provides, so baseline 3 is appropriate.

  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?

  Description clearly states it looks up package-declared docs/homepage/source URLs via official PyPI metadata, using specific verb 'look up' and resource 'package-declared URLs'. It distinguishes from generic web search and from siblings like search_docs by emphasizing it only queries PyPI's JSON API.

  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?

  Explicitly states it is not generic web search and only queries PyPI's JSON API, providing clear context on when not to use. While it does not explicitly name siblings as alternatives, the contrast with general search is sufficient.

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

• get_docsA
  4.4/5.0
  Behavior4/5

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

  Annotations already indicate readOnly, non-destructive, idempotent. The description adds behavioral context: anchor retrieval is 'much cheaper', and pagination is available via start_index. No contradictions.

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

  Conciseness5/5

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

  Two sentences, front-loaded with the main purpose, followed by two essential usage tips. Every sentence earns its place with no redundancy.

  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?

  With an output schema present and 100% schema coverage, the description doesn't need to cover return values. It adequately explains the key parameters and usage nuances (anchor, pagination). Slight omission: no mention of version default behavior, but that is in schema.

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

  Parameters4/5

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

  Schema coverage is 100%, so the description's value-add is limited. However, it explains the purpose of 'anchor' (section-only retrieval) and 'start_index' (pagination), which goes beyond the schema 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 action ('Retrieve') and the resource ('documentation page or specific section'), distinguishing it from siblings like search_docs and compare_versions. It also mentions key features: anchor for section-only retrieval and pagination.

  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 provides guidance on using anchor for cheaper section-only retrieval and mentions pagination via start_index. However, it does not explicitly state when not to use this tool or compare it with alternatives like search_docs.

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

• compare_versionsA
  4.5/5.0
  Behavior5/5

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

  The description goes beyond annotations by detailing the return structure (change type, optional fields) and error behavior for unindexed versions. This adds significant transparency for an AI agent, and there is no contradiction with annotations.

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

  Conciseness5/5

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

  The description is concise with two sentences. The first sentence immediately states the core purpose and output, and the second adds essential error handling info. Every sentence adds value with no wasted words.

  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 has an output schema and clear annotations, the description covers key aspects: core function, return fields, and error handling. It is complete for an AI agent to understand when and how to use the tool correctly.

  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 already provides clear descriptions for all three parameters (100% coverage). The description adds minimal extra context beyond stating the condition that versions must be indexed, which is a minor enhancement. Baseline score of 3 is appropriate.

  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 diffs a Python stdlib symbol between two indexed versions, using a specific verb and resource. It distinguishes itself from siblings (e.g., list_versions, detect_python_version) by focusing on comparing a single symbol across versions.

  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 a condition that both versions must be indexed and mentions actionable error messages, which implies proper usage context. However, it does not explicitly state when to use this tool over alternatives or provide negative examples.

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