Server Quality Checklist

Tool Scores

• generate_issueC
  2.6/5.0
  Behavior2/5

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

  There are no annotations, so the description is the only source of behavioral transparency. It fails to disclose whether the tool writes to GitHub, returns a data structure, or requires authentication, and it doesn't describe 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, grammatically clean sentence with no filler words. However, it could have been slightly more informative while still being concise, so 4.

  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 the rich parameter schema, the description leaves major context gaps: no output schema, no side effects, and no distinction from create_github_issue. The tool's actual function in the workflow remains ambiguous.

  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 parameters with descriptions, so the baseline is 3. The description's mention of 'issue description, issue details, and repository labels' loosely maps to the schema but adds no new semantics beyond what the schema already provides.

  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 uses a specific verb 'generate' and resource 'structured GitHub issue', but it doesn't differentiate from the sibling create_github_issue. 'Generate' is ambiguous about whether the tool actually creates the issue on GitHub or simply produces a structured data object.

  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 given about when to use generate_issue versus create_github_issue, check_duplicate_issue, or list_github_labels. There is no mention of prerequisites, workflow order, or exclusions.

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

• create_github_issueB
  3.1/5.0
  Behavior2/5

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

  Annotations are absent, so the description must fully disclose behavior. It only states 'Create a new issue', providing no information about authentication requirements, potential duplicate creation on repeated calls, rate limits, or side effects. This leaves the agent without expectations beyond the basic mutation.

  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, concise sentence that clearly names the operation and resource. It wastes no words and is immediately scannable, earning a top score for structure.

  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?

  For a tool with this complexity, the description is minimally adequate: it covers the core action and the schema handles parameter details. However, it lacks any mention of return values (e.g., issue URL) or interaction with sibling tools, leaving some context incomplete for an agent without additional hints.

  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 all five parameters (owner, repo, title, body, labels) individually documented. The tool description itself adds no extra semantic context for parameters, so it scores at the baseline of 3 as per the rubric.

  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 the target resource (a new issue in a GitHub repository), making the purpose immediately understandable. However, it does not differentiate from sibling tools such as generate_issue or check_duplicate_issue, so it falls short of a perfect score.

  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?

  There is no guidance on when to use this tool versus alternatives. The description does not mention prerequisites, when to prefer check_duplicate_issue first, or any context that would help an agent select this tool over generate_issue. It simply states the operation without usage context.

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

• list_github_issuesA
  3.7/5.0
  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 adds the 'open' filter behavior, which is a useful behavioral detail beyond the parameters. However, it does not disclose read-only nature, pagination, rate limits, or other potential behaviors, so transparency is minimal but not absent.

  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 unnecessary words. It effectively communicates the tool's purpose without 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?

  For a simple list tool with two parameters, the description is adequate but minimal. It lacks any mention of return format, pagination, or other behavior that would help an agent set expectations. Given no annotations or output schema, the description provides the essential purpose but not enough context for complex decision-making.

  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 both 'owner' and 'repo'. The tool description does not add any parameter-specific semantics beyond the schema, so the baseline score of 3 applies.

  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 the specific verb 'List' with the resource 'open issues in a GitHub repository', clearly stating what the tool does. It distinguishes itself from sibling tools like create_github_issue and list_github_labels by focusing on retrieval of open issues.

  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 usage for retrieving open issues but does not explicitly state when to use this tool versus alternatives. It lacks exclusions or mention of alternative tools, so the usage context is only implied by the description and tool name.

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

• list_github_labelsA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries full burden. It only states the basic list action; it does not disclose return format, pagination, or read-only status, though a list operation is inherently safe.

  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, focused sentence with no wasted words.

  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 simple list tool with two parameters, the description adequately conveys the operation. It does not describe return values or pagination, but the output schema is absent and the operation is straightforward.

  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 fully documents both parameters (owner and repo) with clear descriptions, so the description adds no additional parameter meaning. Baseline 3 applies due to high schema 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 lists labels in a GitHub repository, using a specific verb and resource. It is distinct from sibling tools that focus on issues.

  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 clear context for its use (listing labels), but does not explicitly mention alternatives or exclusion criteria. Since siblings are all about issues, the distinction is implied.

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

• check_duplicate_issueA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description carries the behavioral burden. It discloses that the tool retrieves open issues and performs 'cheap lexical candidate ranking,' and it explicitly sets expectations that results are candidates, not definitive duplicates. This is transparent about the tool's limitations, though it does not mention auth, rate limits, or empty-result behavior, which would make it fully transparent.

  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 three sentences: the first states the core purpose, the second explains the mechanism and caveat, and the third gives an exclusionary usage rule. Every sentence carries useful information with no redundancy 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 has three parameters, no output schema, and no annotations. The description explains the return value conceptually ('candidates'), the ranking method, and the relationship to sibling tools. While it does not describe the exact return format, the conceptual explanation is sufficient for an AI to invoke the tool correctly and interpret the results appropriately.

  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 covers all three parameters with descriptions (owner, repo, description) at 100% coverage. The tool description does not add new parameter-level semantics beyond what the schema provides, 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 opens with a specific verb-resource pair: 'Find the most likely existing open GitHub issues that could be related to a proposed issue.' This clearly distinguishes the tool from siblings like list_github_issues, especially with the explicit instruction not to call that sibling for duplicate checking.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides explicit usage context: it is for duplicate checking against existing open issues, and it warns against using list_github_issues separately for this purpose. It also clarifies that results are candidates only and semantic determination is the AI's responsibility, which guides appropriate use.

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