TestDino MCP

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

With no annotations provided, the description carries the full burden and does well by disclosing key behavioral traits: it specifies pagination options (page/limit or offset/limit), a limit on fetching all results (up to 1000 with get_all=true), and authentication requirements (PAT configuration in mcp.json). It also hints at return content (summaries with statistics, duration, etc.), though it could mention error handling or rate limits.

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, starting with the core purpose and filtering options, then moving to pagination and return values, ending with usage examples and authentication note. Most sentences earn their place, though the authentication detail could be streamlined or moved to annotations if available, and some repetition with the schema exists.

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 complexity (9 parameters, no output schema, no annotations), the description is fairly complete: it covers purpose, usage, behavioral traits, and return content. However, it lacks details on error cases, exact output structure, or performance considerations, which would be helpful for a tool with many parameters and no output schema. It compensates well but has minor gaps.

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 thoroughly. The description adds minimal value beyond the schema by listing filter types (e.g., git branch, time interval) and pagination methods, but it does not provide additional syntax, format details, or usage examples not covered in the schema. 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 ('browse and filter') and resource ('test runs'), distinguishing it from siblings like 'get_run_details' or 'list_testcase' by focusing on filtering test executions rather than retrieving specific details or test cases. It provides concrete examples of what can be filtered (git branch, time interval, etc.).

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 (e.g., to answer questions like 'What tests ran on the develop branch?' or 'Show me all test runs from last week'), but it does not explicitly mention when not to use it or name alternatives among siblings (e.g., 'get_run_details' for detailed info on a specific run). The guidance is practical but lacks explicit exclusions.

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