ChartMogul MCP Server

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

With no annotations provided, the description carries full burden. It discloses the tool returns an entries array with specific fields (date, customer_churn_rate, customer_churn_rate_percentage_change) plus a summary object, and provides an example interpretation (customer_churn_rate=3.9 means 3.9%). However, it doesn't mention rate limits, authentication requirements, error conditions, or whether this is a read-only operation (though 'retrieve' implies it).

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 efficiently structured with the core purpose first, followed by parameter details and an example. Every sentence adds value, though it could be slightly more front-loaded by moving the example to the end. The length is appropriate for a 6-parameter tool with complex filtering options.

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?

For a metrics retrieval tool with no annotations and no output schema, the description does well by explaining the return structure (entries array with specific fields plus summary object) and providing parameter details. However, it doesn't fully address behavioral aspects like pagination, error handling, or authentication requirements that would be important for an API tool.

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?

With 0% schema description coverage, the description fully compensates by explaining all 6 parameters: it identifies required vs. optional parameters, specifies date format (YYYY-MM-DD), lists interval options (day, week, month, quarter, year), explains what geo and plans parameters do, and provides detailed syntax for filters (CFL syntax with reference to get_cfl_fields). This adds substantial meaning beyond the bare schema.

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 retrieves customer churn rate metrics as a percentage, specifies the exact formula (Customer Churn Rate = (Churned Customers / Total Customers at Start) × 100), and distinguishes it from sibling tools like 'mrr_churn_rate_metrics' by focusing on customer metrics rather than MRR metrics. The purpose is specific and well-differentiated.

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 clear context about required parameters (start_date, end_date, interval) and optional filters, but doesn't explicitly state when to use this tool versus alternatives like 'customer_count_metrics' or 'mrr_churn_rate_metrics'. It mentions using 'get_cfl_fields' for filter field lists, which is helpful guidance but not full alternative comparison.

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