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

Annotations already provide idempotentHint and destructiveHint, but the description adds substantial behavioral detail: credentials/cookies/signatures are replaced with {{variables}}, only JSON bodies are kept, and responses already saved as examples are not duplicated. It also discloses the side effect of creating an endpoint when needed. No contradiction with annotations.

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 three sentences, front-loaded with the core action, then conditional behavior, then usage guidance. Every sentence adds value—no filler or repetition. It efficiently covers functionality, transformation, idempotency, and use case without being verbose.

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 7-parameter tool with no output schema, the description covers the main workflow, parameter relationships, and side effects well. It is missing some explicit detail on collection_id/path and error scenarios, but the essential calling context (where to get request_id, what happens on existing vs new endpoint, data transformation) is complete enough for an agent to act.

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 71%, so the description needs to compensate. It adds meaning for method + path and endpoint_id by explaining they are alternatives, and clarifies request_id's source. However, collection_id and path are not elaborated, but the description's workflow context gives enough operational guidance 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 opens with a specific verb 'Document' and a distinct resource: a real request captured by a tunnel. It clearly differentiates itself from siblings by explaining the conditional behavior (add as example vs create endpoint) and explicitly says 'Use it to document webhooks and calls you have only seen in traffic,' which separates it from manual example tools like add_api_example or upsert_api_endpoint.

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: use it for requests captured by a tunnel, with a pointer to list_requests for the request_id. It explains the decision logic (existing endpoint vs new endpoint) and the intended use case, but it does not explicitly name sibling alternatives or state when not to use it, so it falls short of full 5.

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