TestDino MCP

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns 'raw historical data with test run details' and a 'debugging prompt from the API,' and mentions the AI client's role in analysis. However, it lacks details on permissions, rate limits, or error handling, which are important for a tool fetching historical data.

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 details on returns and usage. It's efficient but could be slightly tighter by reducing redundancy (e.g., 'historical execution and failure data' and 'raw historical data' are similar). Every sentence adds value, such as the example.

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 covers purpose and usage well but lacks behavioral details like response format, pagination, or error cases. For a debugging tool with historical data, more context on data structure or limitations would improve completeness, but it's adequate as a minimum viable description.

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 both parameters fully. The description adds no additional meaning beyond implying the test case name is used for debugging, but this is minimal. 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 specific action ('Fetch historical execution and failure data') and resource ('for a specific test case'), distinguishing it from siblings like 'get_testcase_details' or 'list_testcase' by focusing on debugging with historical data rather than basic retrieval or listing.

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?

It explicitly states when to use this tool: 'Use this when you need to debug a failing test case.' This provides clear context and distinguishes it from alternatives like 'get_testcase_details' for basic info or 'list_testcase' for enumeration, with an example reinforcing the debugging scenario.

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