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 and adds significant behavioral context: it discloses that MRR values are in integer cents (requiring division by 100), explains the structure of the returned entries array and summary object, details MRR components (e.g., contraction as negative values), and provides an example. However, it does not mention rate limits, authentication needs, or error handling, leaving some gaps.

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 appropriately sized and front-loaded with critical information (e.g., integer cents warning). It uses bullet-like explanations efficiently, but could be slightly more structured—some sentences are long and dense, though all content earns its place by adding necessary details for tool invocation.

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?

Given the complexity (6 parameters, 0% schema coverage, no output schema, no annotations), the description is largely complete: it explains input requirements, output structure, and key behaviors. However, it lacks details on error cases, pagination, or exact response schema, which could be helpful for an agent. The absence of an output schema means the description should ideally cover return values more thoroughly, which it does partially but not exhaustively.

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?

Schema description coverage is 0%, so the description must compensate fully. It adds extensive meaning beyond the schema: it specifies required vs. optional parameters, explains data formats (e.g., YYYY-MM-DD for dates, CFL syntax for filters), provides an example filter string, and clarifies the purpose of each parameter (e.g., 'geo' and 'plans' for filtering). This goes well beyond the basic schema titles.

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 verb 'retrieve' and resource 'Monthly Recurring Revenue metrics', distinguishing it from siblings like 'arr_metrics' or 'arpa_metrics' by specifying MRR. It explicitly mentions the ChartMogul API context, making the purpose 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 detailing required parameters (start_date, end_date, interval) and optional filters, but does not explicitly state when to use this tool versus alternatives like 'all_metrics' or 'mrr_churn_rate_metrics'. It provides context on filtering capabilities but lacks direct sibling comparison or exclusion guidance.

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