Server Quality Checklist

Tool Scores

• create_design_prC
  2.9/5.0
  Behavior2/5

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

  No annotations are present, so the description bears full responsibility for behavioral disclosure. The description only states 'Create GitHub PR', implying mutation, but fails to mention permissions, idempotency, error conditions, or any side effects.

  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 of 8 words. It is efficient and front-loads the primary action, though it could be expanded slightly to include more context without losing conciseness.

  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 tool has 4 parameters (3 required), no output schema, and no annotations, the description is too brief. It does not explain what 'generated component and test results' means or how the PR is created, leaving significant gaps for an agent to infer behavior.

  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% coverage with descriptions for all four parameters. The tool description adds no additional meaning beyond what the schema already provides, so it meets the baseline but does not exceed it.

  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 action 'Create GitHub PR' and specifies it includes generated component and test results. It distinguishes from sibling tools like analyze_figma_design and design_to_code by focusing on PR creation, though it could be more explicit about the integration of outputs.

  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 is provided on when to use this tool versus alternatives like setup_project_branch or test_design_implementation. The description does not mention prerequisites or typical workflow context.

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

• design_to_codeB
  3.1/5.0
  Behavior2/5

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

  Without annotations, the description carries the full burden of behavioral disclosure. It mentions PR creation but lacks details on authentication, permission requirements, commit process, or error handling. The tool's behavior regarding mutation (creating a PR) is stated but not elaborated upon.

  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 concise with two sentences. The main purpose is stated first, making it easy to grasp. It could be slightly more structured, but it is efficient and free of fluff.

  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 (4 parameters, conversion and PR creation, no output schema, no annotations), the description is incomplete. It does not explain what the tool returns (e.g., PR URL), mention dependencies (e.g., Git, Figma API), or address security or setup requirements. More context is needed for safe and effective use.

  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 covers all four parameters with descriptions (100% coverage), so the baseline is 3. The description adds minimal new information beyond stating that Figma URLs or file IDs are accepted, which is already in the schema. No additional semantic details provided.

  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 the tool converts Figma designs to React components and creates a GitHub PR. It specifies the verb ('Convert' and 'create') and resources (Figma design, React component, GitHub PR), which distinguishes it from sibling tools like 'analyze_figma_design' (analysis only) and 'create_design_pr' (PR creation alone).

  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 is provided on when to use this tool versus alternatives such as 'analyze_figma_design' or 'create_design_pr'. The description does not mention prerequisites, limitations, or conditions (e.g., when the Figma design is ready for conversion).

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

• test_design_implementationB
  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 must carry the full burden. It mentions 'visual regression testing' but does not disclose what happens during testing (e.g., diff report generation, pass/fail criteria) or any side effects (e.g., artifact creation).

  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 that is concise and front-loaded with the key action. It earns its place but could be slightly more structured (e.g., adding a hint about output).

  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 no output schema and 3 required parameters, the description should explain what the tool returns, potential failure modes, or prerequisites (like a Figma access token). It lacks these details, making it incomplete for a testing 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?

  Schema description coverage is 100%, so the description adds minimal extra meaning beyond the parameter names and schemas. It clarifies that figmaInput can be a URL or file ID, but that is already implied.

  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 purpose: testing a component against a Figma design using visual regression testing. It distinguishes from sibling tools like analyze_figma_design or design_to_code, which have different purposes.

  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 alternatives. It does not specify prerequisites, scenarios, or when to avoid using it, leaving the agent to infer context.

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

• analyze_figma_designB
  3.2/5.0
  Behavior2/5

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

  With no annotations, the description must convey behavioral traits. However, it only says 'analyze and extract' without indicating side effects, permissions, or whether it is read-only. Mutation potential is unclear.

  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, front-loaded sentence with no redundant words. Every part is meaningful and earns its place.

  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?

  The tool has no output schema and no annotations, yet the description omits details about the return format or structure of extracted data. Given the single parameter, it is minimally incomplete.

  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 100% of the single parameter with a description. The description adds no further meaning beyond the schema, so the 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 verb 'Analyze' and the resource 'Figma design', and specifies the outputs: 'design tokens, components, and structure'. This distinctly separates it from sibling tools like 'design_to_code' or 'create_design_pr'.

  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 is provided on when to use this tool versus its siblings (e.g., when to analyze vs convert to code). There is no mention of prerequisites or context, leaving the agent to infer usage.

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

• setup_project_branchB
  3.4/5.0
  Behavior2/5

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

  With no annotations, the description carries full burden but only says 'Create'. It does not disclose whether the branch is created locally or remotely, or any other behavioral traits like authentication needs or side effects.

  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, efficient sentence with no wasted words. It front-loads the key action and resource.

  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?

  Despite having only 2 parameters and no output schema, the description omits important context such as whether the branch is created in the remote repository, what the return value is, or if any subsequent actions are needed. An agent might need more to use it 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?

  Schema coverage is 100%, so the baseline is 3. The description adds no parameter information beyond what the input schema already 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 clearly states the action ('Create') and the resource ('new GitHub branch') with a specific context for feature development. It is distinct from sibling tools which focus on design analysis, PR creation, etc.

  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 use for feature branch creation but provides no explicit guidance on when not to use or alternatives. Since no sibling tools overlap, the lack of exclusions is acceptable but still minimal.

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