Get Endpoint Details

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds useful behavioral context about error handling: it returns errors if the spec is not loaded or if the path/method is not found, with suggestions. This goes beyond the annotations and helps the agent anticipate failure modes.

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-organized into clear sections: purpose, usage context, Args, Returns, Examples, and Error Handling. It is front-loaded with the main purpose, and every section provides necessary information without unnecessary flourish. The length is justified by the richness of detail, making it easy to scan.

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?

With 3 required parameters, no output schema, and moderate complexity, the description covers all necessary context: what the tool returns, when to use it, examples of concrete usage, and error handling. It also notes the prerequisite that a spec must be loaded, which is essential for the tool to function. Overall, it gives the agent a complete picture.

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 coverage is 100% and every parameter has a description in the schema, so the baseline is 3. The description adds value by repeating parameter definitions in an Args section and, more importantly, by providing examples that show how to map natural language requests to spec_name, path, and method. These examples clarify parameter usage beyond 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 tool 'gets detailed information about a specific API endpoint' including parameters, request body, responses, and security. It distinguishes from swagger_list_paths by mentioning it is used after listing paths, but does not differentiate from the closely named sibling swagger_get_endpoint_full, which could confuse an agent selecting between the two.

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 explicitly says to use this tool after swagger_list_paths to drill down into a specific endpoint's complete details. It provides concrete examples of user intents and parameter mapping. However, it does not mention any alternatives or when NOT to use this tool (e.g., when swagger_get_endpoint_full would be more appropriate), so it lacks explicit exclusions.

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