benchmark_gate

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

With no annotations, the description carries full burden. It explains the tool runs checks and returns pass/fail with metrics, but does not disclose whether any state changes or side effects occur (e.g., writing logs or locking resources). The behavior appears read-only but is not confirmed.

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?

Two sentences covering purpose, return value, and use case. No fluff; every sentence is informative and front-loaded. Ideal for quick understanding.

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 explains the return format (pass/fail with metrics) and use case (CI pipelines), which compensates for the lack of an output schema. It could mention how thresholds are used or default actions, but is largely sufficient.

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 coverage is 100%, with each parameter having a description. The tool description adds little beyond listing return metrics; it does not explain how parameters interact or provide usage examples. Baseline 3 is appropriate.

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 runs a benchmark suite and checks results against thresholds, returning pass/fail with metrics. It distinguishes from 'run_benchmark' by emphasizing the gate functionality, though it does not explicitly differentiate from siblings.

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 explicitly recommends use in CI pipelines to prevent quality regressions, providing clear context. However, it does not mention when not to use or compare to other tools like 'run_benchmark', leaving some ambiguity.

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