Server Quality Checklist

Tool Scores

• push_to_repoC
  2.7/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden but lacks behavioral details. It states 'push content' but doesn't disclose if this creates/overwrites files, requires authentication, has rate limits, or what happens on success/failure (e.g., commit creation). It's minimal and misses key operational traits for a write operation.

  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 zero waste. It's front-loaded and appropriately sized for the tool's complexity, making it easy to parse quickly without unnecessary elaboration.

  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's complexity (a write operation to GitHub with 4 parameters), no annotations, and no output schema, the description is incomplete. It doesn't cover behavioral aspects, return values, or error handling, leaving significant gaps for an agent to understand how to invoke 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?

  The input schema has 100% description coverage, clearly documenting all 4 parameters (repo_name, file_path, content, message). The description adds no meaning beyond the schema, as it doesn't explain parameter interactions or usage nuances. Baseline 3 is appropriate since the schema does the heavy lifting.

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

  Purpose3/5

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

  The description 'Push content to a GitHub repository' states a clear verb ('push') and resource ('GitHub repository'), but it's vague about what 'push' entails (e.g., creating/updating files, committing changes) and doesn't distinguish it from sibling tools like 'create_repo' (which likely creates repositories) or 'get_user' (which likely retrieves user data). It's not tautological, but lacks specificity.

  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. It doesn't mention prerequisites (e.g., needing an existing repository), exclusions (e.g., not for creating repos), or compare to siblings like 'create_repo' for repository creation. Usage is implied by the action but without explicit context.

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

• create_repoC
  2.9/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It states 'Create' which implies a write/mutation operation, but doesn't mention authentication needs, rate limits, whether the operation is idempotent, or what happens on success/failure. This leaves significant gaps for an agent to understand the tool's behavior.

  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 that states exactly what the tool does with zero wasted words. It's appropriately sized and front-loaded with the core functionality.

  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?

  For a mutation tool with no annotations and no output schema, the description is insufficient. It doesn't address authentication requirements, error conditions, return values, or how it differs from sibling tools. The agent would need to guess about critical behavioral aspects of this repository creation operation.

  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 has 100% description coverage, so all parameters are documented in the structured schema. The description adds no additional parameter information beyond what's already in the schema properties. This meets the baseline expectation when schema coverage is complete.

  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') and resource ('new GitHub repository'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'push_to_repo' which also interacts with repositories, missing an opportunity for clearer distinction.

  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 'push_to_repo' (which might modify existing repositories) or 'get_user' (which retrieves information). There's no mention of prerequisites, such as authentication requirements or GitHub account permissions.

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

• get_userC
  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 carries the full burden of behavioral disclosure. 'Get GitHub user information' implies a read-only operation, but it doesn't specify if it requires authentication, rate limits, what data is returned, or error handling. For a tool with no annotations, this leaves significant behavioral 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 'Get GitHub user information' is a single, efficient sentence that is front-loaded and wastes no words. It directly conveys the core purpose without unnecessary elaboration, making it highly concise and well-structured.

  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 no annotations and no output schema, the description is incomplete. It doesn't explain what user information is retrieved (e.g., profile data, repositories), the return format, or any behavioral aspects like error cases. For a tool with this complexity and lack of structured data, more context is needed.

  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, with the 'username' parameter clearly documented as 'GitHub username'. The description doesn't add any meaning beyond this, such as format examples or constraints. With high schema coverage, the baseline is 3, as the schema does the heavy lifting.

  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 'Get GitHub user information' clearly states the verb 'Get' and resource 'GitHub user information', making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'create_repo' or 'push_to_repo', which are clearly different operations, so it doesn't need sibling differentiation but could be more specific about what user information is retrieved.

  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. It doesn't mention prerequisites, context for usage, or any exclusions. While sibling tools are for different operations (creating and pushing to repos), there's no explicit guidance on usage scenarios for this tool.

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