Swagger Testcase MCP

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

With no annotations provided, the description carries the full burden. It discloses key behaviors: it performs validation checks (e.g., for missing descriptions), returns a quality score (0-100), and implies it may fetch specs from URLs or local files. However, it does not mention authentication needs (though hinted by 'auth_header' parameter), rate limits, or error handling, leaving gaps for a tool with network/file operations.

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 front-loaded with the core purpose, followed by specific checks and output, all in two efficient sentences with zero waste. Every sentence earns its place by adding value (e.g., listing validation aspects clarifies scope).

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 no annotations and no output schema, the description is moderately complete. It covers the tool's purpose and output (quality score), but lacks details on behavioral traits (e.g., network/file access implications) and does not fully compensate for the absence of structured fields. For a tool with 3 parameters and potential complexity (network calls, validation logic), it should do more to guide usage.

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 100%, so the schema already documents all parameters (source, auth_header, headers). The description adds no additional parameter semantics beyond what's in the schema, such as explaining how 'source' interacts with validation or when 'auth_header' is required. Baseline 3 is appropriate as the schema does the heavy lifting.

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 with specific verbs ('validate', 'checks') and resources ('OpenAPI spec'), listing concrete validation aspects (missing descriptions, orphaned schemas, etc.) and the output (quality score). It distinguishes from siblings like 'analyze_endpoint' or 'compare_specs' by focusing on comprehensive spec validation rather than endpoint analysis or comparison.

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 implies usage for validating OpenAPI specs for quality, but does not explicitly state when to use this tool versus alternatives like 'analyze_endpoint' (for specific endpoints) or 'compare_specs' (for comparing multiple specs). It provides some context (e.g., checks for missing descriptions) but lacks explicit guidance on prerequisites or exclusions.

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