test_cases

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

Without annotations, the description carries the transparency burden. It discloses the use of a 'killable subprocess' (important for safety against ReDoS hangs) and states the return contents (pass plus false positives/negatives). This goes beyond the schema and provides useful behavioral context.

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 two short sentences, front-loaded with the action verb 'Check', and contains no filler or irrelevant detail. Every word contributes to understanding the tool's function and behavior.

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?

The description covers the core purpose, key parameters, return value, and the important safety behavior (subprocess/killable). Given that an output schema exists and optional parameters have defaults, the description is adequate, though it could mention the `engine` and `timeout_ms` parameters for completeness.

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?

The description explains the semantic roles of the three required parameters: `pattern`, `positives`, and `negatives`. However, it does not explain the optional `engine` or `timeout_ms` parameters. With 0% schema coverage, the description only partially compensates for the missing parameter documentation.

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 function with a specific verb ('Check'), the resource ('*pattern*'), and the expected outcome ('matches all positives and rejects all negatives'). This distinguishes it from sibling tools like `gen_benign` or `analyze`, which have different purposes.

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 when to use the tool (to validate a regex against positive/negative examples) but provides no explicit guidance on when to prefer it over alternatives or what prerequisites exist. It does not mention exclusions or alternatives, so it earns a mid-range score.

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