predict_test_failures

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

No annotations provided, so the description carries full burden. It states 'surface tests likely to fail' implying a read operation, but does not confirm whether it modifies state, requires authentication, or has rate limits. Behavioral traits like performance or side effects are undisclosed.

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?

Single sentence with no redundancy. The key information is front-loaded: the action (surface) and the input (edited files). While brief, it efficiently conveys the core purpose. Could be improved with a slight structure (e.g., stating output type) but does not waste words.

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 tool with one required parameter, no output schema, and no annotations, the description is incomplete. It does not specify the prediction basis, output format, or reliability. Siblings like 'predict_regression' may have richer definitions, making this underdeveloped by comparison.

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?

With 0% schema coverage, the description must compensate. It adds context that 'a set of edited files' is expected, but does not explain file path format, constraints (e.g., absolute vs relative), or how multiple files are processed. The schema defines a string array, but no further semantics.

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 uses a specific verb 'Surface' and a clear resource 'tests likely to fail given a set of edited files', distinguishing it from siblings like 'predict_regression' which focuses on regression rather than test outcomes. However, it could be more precise about the scope of tests (e.g., unit tests vs integration tests).

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?

No guidance on when to use this tool versus alternatives like 'predict_regression' or 'simulate_change'. The description does not mention which files or contexts are appropriate, nor does it exclude scenarios. Agents lack decision support for tool selection.

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