Averra Extract MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds significant behavioral context beyond the annotations. While annotations indicate destructive and idempotent hints, the description elaborates with safety warnings (e.g., cannot revoke the currently authenticating key, returns 400 error), idempotency details ('revoking an already-revoked key is safe'), and error handling specifics (400, 401, 404). This provides actionable insights not covered by annotations alone.

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 with clear sections (e.g., Args, Returns, Examples, Error Handling) and front-loaded key information. While comprehensive, some sections like 'Error Handling' are detailed but necessary for clarity. It avoids redundancy and each sentence adds value, though it could be slightly more concise in parts.

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 complexity (destructive operation with safety constraints), rich annotations, and lack of output schema, the description is highly complete. It covers purpose, usage, parameters, return values, examples, and error handling, providing all necessary context for an AI agent to invoke the tool correctly and handle edge cases.

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 100% schema description coverage, the schema already documents parameters well. The description adds minimal extra semantics, such as referencing averra_list_api_keys for obtaining the ID and noting the default output format. However, it doesn't provide significant additional meaning beyond the schema, so it meets but doesn't exceed the baseline expectation for high schema coverage.

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 ('revoke') and resource ('Extract API key by its ID'), distinguishing it from sibling tools like averra_create_api_key and averra_list_api_keys. It explicitly mentions the immediate deactivation and irreversibility, which clarifies the nature of the operation beyond just the name.

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 explicit guidance on when to use this tool (e.g., 'User explicitly asks to revoke a specific key' and 'Rotating keys — after confirming the new key works') and when not to use it ('Don't use without user confirmation — this invalidates a credential'). It also references sibling tools like averra_list_api_keys for obtaining the key ID, offering clear alternatives and context.

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