Server Quality Checklist

Tool Scores

• rc_list_metricsA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false. The description adds value by specifying the return format (Markdown-formatted list grouped by category), how metric names should be used in rc_get_chart, and providing example queries. No contradictions with 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 Args, Returns, and Examples sections. Every sentence adds value; no fluff or redundancy. It is appropriately sized for a simple single-parameter tool.

  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 simplicity (one optional parameter with enum, no output schema), the description is complete. It explains the return format, purpose, and relationship to sibling rc_get_chart, fully enabling correct use.

  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 goes beyond by listing the exact category enum values in the Args section and giving concrete examples with natural-language queries, which clarifies how to use the parameter.

  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 all available RevenueCat Charts API metrics with descriptions, using a specific verb ('List') and resource ('RevenueCat Charts API metrics'). It distinguishes from sibling rc_get_chart by noting it's for discovery before calling rc_get_chart.

  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?

  Provides explicit guidance on when to use ('Use this to discover what subscription data you can query before calling rc_get_chart') and names the alternative rc_get_chart. It lacks an explicit 'when not to use' statement but implies it through the 'before calling' context.

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

• rc_get_chartA
  4.7/5.0
  Behavior5/5

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

  The description goes well beyond the annotations by detailing output format (markdown table with summary statistics), multi-measure chart behavior, segmented chart top-10 columns, and error handling including auto-retry with backoff and invalid metric responses. This provides rich behavioral context not available from annotations 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 lengthy but well-organized into sections (overview, args, returns, examples, error handling). Every section provides essential information; the examples and error handling add value over schema. Slightly verbose due to repetition of some parameter details, but overall efficient for the tool's complexity.

  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?

  The description fully covers all parameters, output format, examples, and error handling. With no output schema, it still explains return values clearly. For a tool with 7 parameters and 21 possible metrics, this is comprehensive and complete.

  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?

  Despite 100% schema coverage, the description adds substantial meaning with natural language examples, common metric values, default resolution, auto-detection of project_id, and date format clarification. This goes far beyond the schema descriptions.

  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 queries RevenueCat Charts API metrics as a time series and returns a formatted markdown table. It explicitly distinguishes its purpose from sibling tools by mentioning rc_list_metrics for metric discovery and focusing on chart data with summary statistics, which is distinct from an overview tool.

  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 explicit usage guidance through examples that map natural language queries to parameter values, and mentions using rc_list_metrics to discover available metrics. It does not explicitly contrast with rc_get_overview, but the examples and parameter explanations give clear context for when to use this tool.

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

• rc_get_overviewA
  4.7/5.0
  Behavior5/5

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

  Annotations already declare readOnlyHint and idempotentHint, and the description adds the return format (Markdown summary with specific metrics) and auto-detection of project_id. It also discloses that api_key is required and that project_id is auto-detected, which is behavioral context beyond the schema.

  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 clear one-sentence summary, followed by Args, Returns, and Examples sections. No unnecessary fluff; every section adds value and it is front-loaded with the main 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?

  For a simple read-only tool with two parameters and no output schema, the description explains what it returns (specific metrics list), how to call it, and provides three usage examples. It is complete enough for an agent to select and invoke correctly.

  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 already fully describes both parameters (100% coverage), and the description reinforces api_key format and adds auto-detection behavior for project_id with an example. This adds meaningful context beyond the schema's static description.

  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 'Get' and resource 'overview' of 'subscription health metrics', clearly distinguishing it from sibling tools like rc_list_metrics and rc_get_chart. It states it returns a real-time snapshot without a date range, which is a unique scope.

  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?

  It provides clear context by stating 'No date range needed — returns current state' and gives example questions for when to call it. However, it does not explicitly mention when not to use it or direct to alternatives like rc_list_metrics or rc_get_chart, so there are no explicit exclusions.

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