Server Quality Checklist

Tool Scores

• sonarqube_project_metricsA
  4.4/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, idempotentHint=true. Description adds value by detailing return format (raw list and dict) and behavior on unknown metric keys. Some redundancy with schema mutual exclusion info.

  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?

  Description is well-structured: purpose, wrapper, return format, advice, examples. Front-loaded and efficient, though slightly verbose with redundant listing of default metrics.

  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?

  Given annotations, output schema, and 100% schema coverage, the description completes the picture by covering purpose, usage, behavior, and examples. No gaps identified.

  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% with detailed descriptions. The description adds minor context (default metric set) already present in schema. Does not significantly enhance parameter understanding beyond schema.

  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?

  Clearly states the tool fetches measures for a single project, wraps SonarQube API, and distinguishes from siblings by specifying single project scope. Examples further clarify the purpose.

  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?

  Explicitly provides when-to-use and when-not-to-use with specific sibling tool names (sonarqube_worst_metrics, sonarqube_quality_gate_status). Also advises on metric key discovery.

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

• sonarqube_quality_gate_statusA
  4.6/5.0
  Behavior4/5

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

  Annotations already indicate readOnlyHint=true, idempotentHint=true, etc. The description adds operational context: wraps /api/qualitygates/project_status, returns per-condition breakdown, explains NONE meaning, and notes mutual exclusivity constraints. No contradictions.

  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 well-structured with a clear opening sentence, followed by bullet-point examples and 'Don't use' sections. It is slightly long but every sentence adds value and is front-loaded.

  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?

  Given the presence of an output schema (not shown but indicated 'Has output schema: true'), the description focuses on input parameters and purpose. It explains status values, use cases, and edge case (NONE). No gaps identified.

  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% with descriptions. The description adds usage context through examples showing how to use project_key, branch, and pull_request, and clarifies mutual exclusivity. This goes beyond the schema alone.

  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 starts with 'Fetch the Quality Gate status for a project,' using a specific verb and resource. It clearly distinguishes from sibling tools by noting alternatives like sonarqube_project_metrics for raw metrics and sonarqube_worst_metrics for org-wide failures.

  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 when-to-use examples ('Use when: Is project passing?') and when-not-to-use alternatives ('Don't use when: want raw metric values'). It also explains mutual exclusivity of branch and pull_request.

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

• sonarqube_get_issuesA
  4.9/5.0
  Behavior5/5

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

  Annotations already provide readOnlyHint, idempotentHint, etc. The description adds pagination details (has_more, page+1), total cap of 10,000 issues, and notes that Security Hotspots are rejected with an error, providing valuable context beyond annotations.

  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 well-structured with a summary, pagination section, and bulleted examples. Every sentence earns its place without redundancy or excess.

  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?

  Given the tool's complexity, annotations, and output schema, the description covers all necessary aspects: purpose, parameters, pagination, limitations, and usage examples. It is fully complete.

  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 description coverage is 100%, so baseline is 3. The description adds usage examples for parameters (e.g., 'severities=['BLOCKER','CRITICAL']') and clarifies defaults like 'resolved=False', adding extra semantic value.

  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 'Search issues for a SonarQube project' and wraps '/api/issues/search'. It provides specific verb+resource and distinguishes from siblings like 'sonarqube_list_projects' and 'sonarqube_worst_metrics'.

  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 gives explicit when-to-use and when-not-to-use examples, including alternatives for issue counts and Security Hotspots. Examples cover triage, security sweep, and closed issues, making usage clear.

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

• sonarqube_list_projectsA
  4.9/5.0
  Behavior5/5

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

  Annotations already indicate safe read-only operation; description adds pagination behavior (has_more, sort order), and clarifies what the tool doesn't return, exceeding annotation requirements.

  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?

  Well-structured with clear sections, front-loaded with main purpose, and every sentence provides useful guidance without verbosity.

  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?

  Given the output schema existence, the description covers usage context, pagination, and examples thoroughly, leaving no significant gaps.

  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%; description adds value with concrete examples for query and pagination instructions, enhancing understanding beyond the schema.

  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 lists SonarQube projects with qualifier 'TRK', and distinguishes itself from sibling tools by noting when to use it to discover project keys before calling other tools.

  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?

  Explicitly provides when-to-use examples (e.g., discover project keys, find projects with substring) and when-not-to-use (when key is known, need quality gate status), with specific sibling tool alternatives.

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

• sonarqube_worst_metricsA
  4.9/5.0
  Behavior5/5

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

  Beyond readOnlyHint annotations, description details algorithm steps, API call pattern, metric directionality, and performance implications of candidate_pool parameter.

  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?

  Well-structured with algorithm steps and examples, though slightly verbose; all content is relevant and front-loaded with core purpose.

  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?

  Covers all necessary aspects: algorithm, parameters, performance, limitations, and distinguished from siblings; output schema exists, reducing need for return value description.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Adds substantial meaning beyond 100% schema coverage by explaining how candidate_pool affects accuracy/speed, metric directionality, and query filtering purpose.

  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 ranks projects by the worst value of a single metric, with specific examples and differentiation from sibling tool for single-project queries.

  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?

  Explicit when-to-use and when-not-to-use examples are provided, including alternative tool for single-project queries and branch-specific limitations.

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