Server Quality Checklist

Tool Scores

• get_developer_contextA
  3.8/5.0
  Behavior2/5

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

  The readOnlyHint annotation already tells the agent it's safe. The description adds no behavioral details beyond stating it uses the configured API key. It does not mention rate limits, authentication failure behavior, or other 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, well-structured sentence that front-loads the tool's purpose and immediately clarifies input requirements. Every part earns its place.

  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?

  Given the tool has no parameters, a read-only annotation, and no output schema, the description adequately covers what the tool does and that it requires no input. It does not describe return format but is sufficient for an agent to decide to call it.

  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?

  There are zero parameters; schema coverage is 100%. The description adds value by explicitly stating 'No parameters required', reinforcing that the tool needs no input.

  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 retrieves the authenticated user's developer profile, listing specific data points (coding statistics, subscription status, GitHub integration, organization memberships). It distinguishes itself from sibling tools like get_ai_insights by focusing on a broad profile.

  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 notes 'No parameters required', implying simple invocation, but offers no explicit guidance on when to use this tool versus siblings like get_productivity_summary or get_recent_activity.

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

• get_ai_insightsA
  4/5.0
  Behavior4/5

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

  Annotations declare readOnlyHint=true, and the description adds valuable context by detailing the specific analytics returned (e.g., human vs AI comparison, efficiency trends), enhancing transparency beyond the annotation alone.

  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 sentence that efficiently lists all analytics. While it is clear and front-loaded, it could be more structured (e.g., bullet points) but remains adequately concise.

  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?

  With a simple input schema (one parameter) and no output schema, the description compensates by thoroughly listing all output components. The tool's behavior is fully captured for accurate invocation.

  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% and the parameter description fully explains the 'range' parameter (named or custom dates). The tool description adds no additional meaning beyond the schema, so a 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 tool gets 'AI-assisted coding analytics' and enumerates specific metrics like adoption timeline and contribution share, distinguishing it from sibling tools (e.g., get_productivity_summary covers general productivity, not AI-specific insights).

  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 does not provide explicit when-to-use or when-not-to-use guidance relative to siblings. However, the list of analytics implies it is for AI adoption tracking, so an agent can infer usage context.

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

• get_productivity_summaryA
  4.1/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true, so the description adds context on what the tool returns (total coding time and breakdowns). It does not disclose further behavioral traits like auth or rate limits, but given the annotation coverage, this is sufficient.

  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 action, and contains no unnecessary words. It efficiently conveys the tool's purpose and output.

  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?

  For a simple tool with two parameters, full schema coverage, and annotations, the description adequately explains the return values (breakdowns) and completes the user's understanding without needing 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?

  The input schema provides 100% coverage of both parameters with descriptions. The tool description does not add new semantic information about the parameters beyond what the schema already states.

  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 a specific verb ('Get') and identifies the resource ('aggregated coding productivity statistics') clearly. It distinguishes from sibling tools which focus on developer context or recent activity, and specifies the breakdowns returned.

  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 time-range aggregated statistics but does not provide explicit guidance on when to use this tool versus alternatives like get_developer_context or get_recent_activity.

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

• get_recent_activityA
  4.2/5.0
  Behavior4/5

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

  Annotations declare readOnlyHint=true, and the description reinforces this by describing the function as retrieving data. It adds value by disclosing pagination behavior and response metadata (total count). 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is two sentences long, front-loaded with the core purpose, and every sentence adds value. No unnecessary 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 paginated read-only tool with no output schema, the description adequately covers the main behavior: pagination and response metadata. While it could mention the exact fields in the response, the description is sufficient for an agent to use the tool 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 for all 8 parameters. The description adds context about pagination parameters and date range filtering but does not elaborate on filter parameters like editor, project, or language. Since schema covers them, a baseline 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 it gets 'recent coding heartbeats (activity events)', which is a specific verb and resource. This distinguishes it from siblings like get_ai_insights or get_productivity_summary, which are about different data.

  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 mentions pagination and how to use 'page' and 'per_page' parameters, providing clear context for navigating large results. However, it does not explicitly say when to use this tool versus alternatives or when not to use it.

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