Server Quality Checklist

Tool Scores

• analyze_repositoryA
  4.2/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, so the description doesn't need to cover safety. It adds value by specifying exactly what the tool returns and that it computes a dependency graph, providing useful behavioral context beyond the annotation.

  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 action and output, followed by a usage recommendation. Every word earns its place, with no redundancy or fluff.

  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?

  The description includes a comprehensive list of returned summary items, serving as a form of output documentation since no output schema exists. It also gives usage context. It could mention limitations (e.g., language support or scalability) or explicitly contrast with sibling tools, but overall it is sufficiently 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% for the single 'directory' parameter, so the schema already documents it fully. The description does not add any parameter-specific details beyond what is in the schema, matching the baseline for full coverage.

  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 'Builds a dependency graph for a codebase' and lists specific outputs (file count, import edges, entry points, circular dependencies, most complex modules). This distinguishes it from sibling tools that focus on individual analyses, making the purpose unambiguous.

  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 usage guidance: 'Use this instead of reading every file when you need architectural context.' This tells the agent when to invoke it, though it does not explicitly mention alternatives or when not to use it. The guidance is clear but lacks exclusions.

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

• find_circular_dependenciesA
  4.2/5.0
  Behavior4/5

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

  Annotations already declare the tool as read-only, so the description does not need to restate that. It adds valuable behavioral context by specifying the algorithm (Tarjan's) and the return behavior (each cycle with severity based on module span), which goes 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.

  Conciseness5/5

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

  The description is only two sentences, front-loaded with the main action ('Detects import cycles') and includes essential details without filler. Every clause adds value.

  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?

  The tool has one well-documented parameter, clear return behavior despite no output schema, and read-only annotations. The description is sufficient for an agent to understand what it does and what it returns. Minor caveats about performance or input structure are not critical for this simple tool.

  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 schema covers the single parameter 'directory' with 100% description coverage, so the schema already provides the needed meaning. The description does not add extra parameter semantics beyond what the schema states, making the baseline 3 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 uses a specific verb 'Detects' with a clear resource 'import cycles', and it distinguishes itself from siblings like find_entry_points and most_complex_files by focusing on dependency cycles, not general analysis or complexity.

  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 clearly implies when to use this tool (to detect circular imports), but it does not explicitly state alternatives or when not to use it. The context is clear enough for an agent to select it appropriately among sibling tools.

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

• most_complex_filesA
  4.2/5.0
  Behavior4/5

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

  The description discloses the core behavioral trait: ranking modules by cyclomatic complexity. Annotations already mark it as read-only, so no safety contradictions exist. While it does not detail traversal or filtering behavior, the metric and ranking intent are clearly stated, which is sufficient for a simple read-only analysis tool.

  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 of 15 words, front-loaded with the action verb. It efficiently conveys both the operation and the motivation without unnecessary repetition or filler.

  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?

  The tool is straightforward, and the description, combined with the well-documented schema and read-only annotation, gives enough context. There is no output schema, but the ranking nature implies the return format, and the description's 'ranks' likely implies an ordered list. No major gaps are evident 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?

  The input schema already provides descriptions for both parameters (directory and limit) with 100% coverage. The description itself does not add any additional meaning about parameters, so it meets the baseline of 3 without exceeding it.

  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 ('Ranks') and resource ('modules') and identifies the exact metric (cyclomatic complexity) and purpose (finding refactoring targets). This clearly distinguishes it from sibling tools like find_entry_points or find_circular_dependencies, which focus on different aspects of code 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 phrase 'so you can find refactoring targets' provides a clear context for when to use the tool. However, it does not explicitly mention alternatives or when not to use it, though the specificity of complexity ranking implicitly separates it from siblings.

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

• find_entry_pointsA
  4.3/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, and the description adds the core selection criterion (modules not imported) and the interpretation of entry points. This goes beyond the annotations, though it does not describe return format or edge cases, so not a 5.

  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 two short sentences, front-loaded with the core behavior and followed by a practical use case. Every word earns its place with 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?

  For a simple read-only tool with one well-documented parameter and strong annotations, the description is complete. It explains what the tool outputs (a list of modules) and when to use it, which is sufficient without an output schema.

  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%, with the `directory` parameter fully documented. The tool description adds no parameter-level detail, so the baseline of 3 is appropriate since the schema carries the load.

  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 lists modules that nothing else imports, identifying entry points where execution starts. This specific verb+resource distinguishes it from sibling tools like find_circular_dependencies and most_complex_files.

  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 a clear use case: 'Useful for orienting in an unfamiliar codebase before reading any source.' It does not explicitly mention alternatives or when not to use it, but the context is clear enough for an agent to decide appropriately.

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