Server Quality Checklist

Tool Scores

• get_daily_usage_dataC
  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 the full burden of behavioral disclosure. It states this is a read operation ('Get'), implying it's non-destructive, but doesn't mention any behavioral traits like authentication requirements, rate limits, data freshness, or pagination. For a tool that likely accesses sensitive usage data, this lack of context is a significant gap.

  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, efficient sentence that front-loads the core purpose and includes specific metric examples. It avoids redundancy and wastes no words, though it could be slightly more structured by separating usage guidance from the purpose statement.

  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 of usage metrics and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the return values look like (e.g., format, granularity), potential side effects, or error conditions. For a data-fetching tool with no structured output documentation, this leaves the agent under-informed.

  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 description coverage is 100%, with both parameters clearly documented as epoch milliseconds for date ranges. The description adds marginal value by implying date-range filtering ('daily usage metrics'), but doesn't provide additional syntax, format details, or constraints beyond what the schema already specifies. Baseline 3 is appropriate when 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 clearly states the verb 'Get' and specifies the resource 'detailed daily usage metrics for the team', including concrete examples like 'lines added/deleted, AI suggestions, and model usage'. It distinguishes from sibling tools by focusing on usage metrics rather than spending data or team members, though it doesn't explicitly name the alternatives.

  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 'get_spending_data' or 'get_team_members'. It doesn't mention prerequisites, exclusions, or specific contexts where this tool is preferred, leaving the agent to infer usage based on the purpose alone.

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

• get_spending_dataC
  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. It mentions 'optional filtering and pagination', which hints at read-only behavior and some operational traits, but it doesn't cover critical aspects like rate limits, authentication needs, error handling, or what the output looks like (e.g., format, structure). For a tool with no annotations, this leaves significant gaps in understanding its behavior.

  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, efficient sentence that front-loads the core purpose ('Get team member spending information') and adds brief context ('with optional filtering and pagination'). There's no wasted wording, and it's appropriately sized for the tool's complexity, though it could be slightly more structured if it included more usage details.

  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, no output schema, and 5 parameters, the description is incomplete. It covers the basic purpose and hints at behavior but fails to address key contextual elements like output format, error conditions, or how it differs from sibling tools. For a data retrieval tool with filtering and pagination, more detail is needed to guide the agent effectively.

  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 description coverage is 100%, meaning all parameters are documented in the input schema. The description adds minimal value beyond the schema by mentioning 'optional filtering and pagination', which loosely relates to parameters like 'searchTerm', 'page', and 'pageSize', but doesn't provide additional meaning or context. Given the high schema coverage, a baseline score of 3 is appropriate as the description doesn't compensate with extra insights.

  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 verb ('Get') and resource ('team member spending information'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'get_daily_usage_data' or 'get_team_members', which might also retrieve related data. The description is specific about what data is retrieved but lacks sibling 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 mentions 'optional filtering and pagination', which implies some context for usage, but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_daily_usage_data' or 'get_team_members'. There's no mention of prerequisites, exclusions, or specific scenarios that warrant its use over siblings, leaving the agent with minimal direction.

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

• get_team_membersB
  3.2/5.0
  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. It states it 'gets' a list, implying a read operation, but doesn't disclose behavioral traits like whether it requires authentication, has rate limits, returns paginated results, or handles errors. The description is minimal and lacks context beyond the basic action.

  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 directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy to parse quickly.

  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?

  Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It explains what data is retrieved but lacks details on behavior, usage context, or output format. For a read-only tool with no parameters, this is the bare minimum, leaving gaps in understanding how to effectively use 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?

  The input schema has 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add parameter details, but since there are no parameters, this is acceptable. Baseline is 4 for 0 parameters, as the description doesn't need to compensate for any gaps.

  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 verb ('Get') and resource ('list of team members') with specific attributes (names, emails, roles). It's specific enough to understand what data is retrieved, though it doesn't explicitly differentiate from sibling tools like 'get_daily_usage_data' or 'get_spending_data' since those appear to be about different resources.

  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 context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name and description alone.

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