check_quality_gates

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

The description adds significant transparency beyond annotations: it details the special 'NO_GATES_CONFIGURED' result, the effect of use_default_gates, and the JSON response structure. Annotations already declare readOnlyHint=true, which is consistent with 'Read-only' in the description.

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 longer but every sentence adds value. It front-loads the main action and provides details on behavior and parameters. Minor redundancy could be trimmed (e.g., repeating 'pass'), but overall efficient.

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 schema covers all parameters and annotations are present, the description completes the picture with edge-case behaviors, default configs, and expected output format. No output schema exists, but the description compensates with a clear JSON template.

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 clear descriptions. The description adds context about the use_default_gates parameter (opt-in, default false) and explains that config merges with project config. This adds meaning beyond the schema alone.

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 configurable quality gate checks and returns pass/fail results. It specifies the types of checks (complexity, coupling, etc.) and distinguishes itself from sibling tools like check_architecture or detect_antipatterns by being a comprehensive gate runner.

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 guides usage: 'Designed for CI integration — AI can verify gates pass before committing. Use before PR/commit.' It also details the behavior when no gates are configured and how to opt-in to defaults. However, it does not explicitly compare to alternative tools or state when not to use it.

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