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 and excels by disclosing critical behavioral traits: it specifies the default limit (20) and discourages higher values, details the response structure (subscription objects with specific fields), explains data interpretation (mrr/arr as integer cents), and mentions pagination (cursor/has_more). This covers safety, output format, and operational constraints effectively.

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, starting with the core purpose and immediately detailing key information like the default limit and response structure. However, it could be slightly more structured by separating usage notes from field descriptions, but every sentence adds value without waste.

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 (2 parameters, no annotations, no output schema), the description is complete enough. It covers the tool's purpose, usage guidelines, behavioral details (like pagination and data interpretation), and parameter semantics, providing all necessary context for an AI agent to invoke the tool correctly without needing additional structured data.

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?

The input schema has 0% description coverage, so the description must compensate fully. It adds significant meaning beyond the schema by explaining that 'uuid' is a required customer UUID and 'limit' has a default of 20 with a discouragement for values over 20. This clarifies the purpose and constraints of both parameters, making them understandable without relying on the 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 ('List customer subscriptions') and resource ('customer subscriptions'), distinguishing it from sibling tools like 'list_customers' or 'list_subscription_events' by focusing on subscriptions for a specific customer. It provides concrete details about what is returned, making the purpose 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 gives clear context for usage by specifying that it requires a customer UUID and discourages limits over 20, but it does not explicitly mention when to use this tool versus alternatives like 'list_subscription_events' or 'retrieve_customer' for subscription-related data. It provides practical constraints but lacks sibling differentiation.

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