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 does well by disclosing critical behavioral traits: the ARPA values are in integer cents requiring division by 100, the return format (entries array with date, arpa, arpa_percentage_change plus summary object), and provides a concrete example (arpa=84767 means $847.67). However, it doesn't mention rate limits, authentication requirements, or pagination behavior.

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 the core purpose and critical warning about integer cents. Every sentence adds value: purpose, critical conversion note, formula, return format, parameter requirements, optional parameters with syntax, and example. Minor redundancy exists in explaining the cents conversion multiple times.

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 6-parameter tool with no annotations and no output schema, the description provides excellent coverage: clear purpose, behavioral details (return format, data interpretation), complete parameter semantics, and an example. The main gap is lack of explicit guidance on when to use versus sibling metrics tools, but otherwise it's quite complete for the complexity level.

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 specifies required parameters (start_date, end_date, interval with format and allowed values), optional parameters (geo, plans, filters), provides the filter syntax format (CFL syntax), and references get_cfl_fields for field lists. The description 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 specific action ('Retrieve Average Revenue Per Account metrics') and resource (ChartMogul API metrics), distinguishing it from sibling tools like arr_metrics, asp_metrics, or mrr_metrics by focusing specifically on ARPA. It provides the exact formula (ARPA = Total MRR / Total Customers) to clarify what the metric represents.

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 context through the required parameters (date range and interval) and mentions an optional filter syntax, but doesn't explicitly state when to use this tool versus alternatives like mrr_metrics or customer_count_metrics. It references get_cfl_fields for filter field lists, which provides some guidance but not explicit comparison to sibling tools.

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