ChartMogul MCP Server

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 effectively describes the tool's behavior by explaining the calculation, interpreting result ranges (normal range -10% to +10%), and detailing the return structure (entries array with date, mrr_churn_rate, mrr_churn_rate_percentage_change, plus summary object). However, it does not cover aspects like rate limits, authentication requirements, or error handling.

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 well-structured and front-loaded with key information (purpose, formula, result interpretation), but it includes some redundancy (e.g., repeating that negative values are good) and could be slightly more concise. Most sentences earn their place by providing essential details, though the example at the end could be integrated more efficiently.

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 tool with 6 parameters, 0% schema coverage, and no output schema, the description is largely complete. It covers the purpose, parameters, result interpretation, and return structure. However, it lacks information on error cases, pagination, or API-specific constraints (e.g., date range limits), leaving minor gaps given the complexity.

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?

Given 0% schema description coverage, the description compensates fully by explaining all parameters. It specifies required parameters (start_date, end_date, interval with format YYYY-MM-DD and interval options), optional parameters (geo, plans, filters), and provides detailed guidance on filters (CFL syntax, referencing get_cfl_fields for field list). This adds significant meaning beyond the basic 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 explicitly states the tool retrieves Net MRR Churn Rate metrics as a percentage, clearly distinguishing it from sibling tools like 'mrr_metrics' or 'customer_churn_rate_metrics' by focusing specifically on MRR churn calculations. It provides the exact formula (Net MRR Churn = (Churned MRR + Contraction MRR - Expansion MRR) / MRR at Start × 100), making the purpose highly specific and unambiguous.

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 implies usage by specifying required parameters (start_date, end_date, interval) and mentioning optional filters, but it does not explicitly state when to use this tool versus alternatives like 'mrr_metrics' or 'customer_churn_rate_metrics'. It provides context on interpreting results (e.g., negative values indicate net negative churn) but lacks direct guidance on tool selection among siblings.

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