Server Quality Checklist

Tool Scores

• pass_to_ai_for_requirementsA
  3.8/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It does disclose the output destination, implying a file write, but it doesn't mention whether it overwrites existing files, requires specific permissions, or any side effects. The behavior is partially transparent but has gaps.

  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, compact sentence that front-loads the core purpose and adds the output path. Every word earns its place, with no filler or redundancy.

  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 absence of annotations and an output schema, the description is too thin. It doesn't explain the process (e.g., that it creates a file, how the AI is invoked, or what the expected result is). Essential context for successful invocation is missing.

  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%, so baseline is 3. The description repeats the default output path already documented in the schema, adding no extra semantic value beyond what the schema provides.

  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 explicitly states the tool passes user requirements to AI to produce a requirements definition document, and identifies it as the first step of the workflow. This clearly distinguishes it from sibling tools like pass_to_ai_for_design or pass_to_ai_for_implementation.

  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 'workflow first step' provides clear context for when to use this tool. However, it does not explicitly mention alternatives or when not to use it, so it's a bit short of a perfect score.

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

• verify_spec_commentsA
  3.9/5.0
  Behavior3/5

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

  With no annotations provided, the description must fully convey behavior. It states the tool verifies/checks markers, implying a read-only operation, but does not explicitly disclose side effects, permission requirements, or output/return format. More could be said about whether it fails on missing markers or what results are produced.

  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 sentences, front-loaded with the core purpose, and includes a practical usage hint. Every sentence is informative with no redundancy or fluff.

  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 tool is simple (one parameter, no output schema), and the description covers what and when. However, it lacks information on the return/exit behavior or how to interpret results, which is important for a verification tool 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% for the only parameter (target_files), and the description adds no additional parameter semantics beyond what the schema already states. The baseline of 3 is appropriate since the schema carries the burden.

  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 'verify whether the @spec-impl marker is placed in files,' using a specific verb (verify) and resource (@spec-impl marker). It distinguishes itself from the sibling 'pass_to_ai_for_*' tools by being a verification tool rather than a generation/passing tool.

  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 instructs to use 'after executing pass_to_ai_for_comments' and to confirm markers are added to all files. This provides clear when-to-use context, though it does not mention when-not-to-use or alternative tools beyond the sibling list.

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

• pass_to_ai_for_commentsA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description must carry the transparency burden. It does disclose that the tool can add comments to existing files or create new files, which are key behavioral traits. However, it omits details about whether existing comments are overwritten or how file modifications are handled, leaving some ambiguity.

  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 concise sentences effectively convey the tool's purpose, workflow step, and capabilities. Every sentence contributes meaningful information without 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?

  The description is well-suited to its workflow context, with sibling tools and step numbering providing additional context. Parameter details are fully covered in the schema. However, it lacks information about output format or prerequisites, which would enhance completeness.

  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 each parameter already described in the schema. The tool description adds no extra parameter semantics beyond what the schema provides, so the 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?

  The description clearly states the tool's function: having AI write comments with @spec-impl markers based on a design document. It also specifies it's the 3rd workflow step, distinguishing it from sibling tools like requirements, design, and implementation.

  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 explicitly positions the tool as the 3rd step in a workflow, providing clear sequencing context. It doesn't explicitly state when not to use it, but the sibling tool names and step numbering strongly imply appropriate usage scenarios.

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

• pass_to_ai_for_designA
  4/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden of behavioral disclosure. It specifies the output path and that the design is based on the requirements file, but it does not disclose whether existing files are overwritten, required permissions, or potential error conditions. This is some useful context but not comprehensive.

  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 front-loads the core purpose and ends with the output destination. It is free of fluff and every word earns its place, conveying the tool's function in exactly one line.

  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?

  For a tool with three parameters and no output schema, the description covers the essential aspects: purpose, input (requirements), output location, and workflow step. It does not mention error handling or permissions, but for a simple pipeline step, this is adequately complete.

  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 the schema already documents all parameters. The description repeats the default output path already described in the schema, adding no new semantic detail beyond what structured data provides. 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?

  The description clearly states that the tool creates a design document from a requirements definition document, and identifies it as the second step of a workflow. This distinguishes it from sibling tools like pass_to_ai_for_requirements, pass_to_ai_for_implementation, and pass_to_ai_for_comments, which are for other phases.

  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 workflow step designation ('2番目のステップ') indicates when this tool should be used relative to the overall process. It does not explicitly name alternatives or exclusions, but the context makes it clear this is for the design phase, not for requirements, comments, or implementation.

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

• pass_to_ai_for_implementationA
  4.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full transparency burden. It discloses that the tool updates files to a DONE state after implementation, which is a key side effect. It also mentions following @spec-impl markers. It does not detail all potential side effects (e.g., file modifications, error handling), but the main behavioral traits are covered.

  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, well-structured sentence that front-loads the primary purpose and includes workflow context. Every clause earns its place, with no redundant information. It is appropriately concise for the tool's complexity.

  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 covers the essential behavior—passing files, implementing per marker, and updating to DONE—which is sufficient for a simple workflow step. There is no output schema, but the description does not need to explain return values. It lacks details on failure modes or what the DONE state entails, but overall it is reasonably complete given the tool's scope.

  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 baseline is 3. The description adds meaningful context beyond the schema by indicating that target_files should contain comments and that implementation follows @spec-impl markers. This enriches the plain 'implementation target files' definition with domain-specific semantics.

  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 passes commented files to AI for implementation, with a specific verb ('実装させる') and resource (commented files). It also positions itself as the workflow's final step and references the @spec-impl marker, distinguishing it from sibling tools like pass_to_ai_for_requirements and pass_to_ai_for_design.

  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 explicitly mentions it is the workflow's last step, giving clear usage context and implying it should be used after other pass_to_ai steps. It does not explicitly name alternatives or provide when-not conditions, but the workflow positioning and sibling tool names make the intended usage clear.

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