Get Chart Data

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.

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.

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.

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.

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.

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.