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 key behavioral traits: the default limit (20), a warning about excessive token usage, the return structure (same as list_customers), critical data format details (mrr/arr in integer cents), and exact match requirements for the email parameter. This covers mutation safety, performance considerations, and output expectations comprehensively.

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. Every sentence adds value: purpose, limit warning, return structure, data format, and parameter details. However, it could be slightly more structured (e.g., bullet points) for easier parsing, and the API context '[ChartMogul API]' is redundant if implied by the server.

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 tool's moderate complexity (2 parameters, no output schema, no annotations), the description is complete. It covers purpose, usage guidelines, behavioral traits (limits, token usage, data format), and parameter semantics. No output schema exists, so the description appropriately explains the return structure and data format, leaving no significant gaps for agent understanding.

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 schema description coverage is 0%, so the description must compensate. It adds substantial meaning beyond the basic schema: it specifies that the email parameter requires an exact match (e.g., '[email protected]'), explains the limit parameter's default (20) and a warning against high values, and clarifies data semantics (mrr/arr as integer cents). This fully documents both parameters' usage and constraints.

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's purpose: 'Search customers by email address.' It specifies the exact resource (customers) and verb (search) with a precise search criterion (email address), distinguishing it from sibling tools like list_customers (which lists all customers) and retrieve_customer (which fetches a specific customer by ID).

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 for when to use this tool: searching by email address. It implies an alternative (list_customers) by mentioning the return structure is the same, but does not explicitly state when to choose one over the other or list other alternatives like retrieve_customer. It also includes usage warnings (limit, token usage) but lacks explicit exclusions or prerequisites.

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