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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it explains that waived rules are listed separately, that unrun checks are reported as such and are NOT the same as passing, and that the result is the board author's configured checks. This is meaningful behavioral disclosure that helps an agent interpret results correctly.

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 compact and front-loaded: the first sentence states the primary use case and what the tool returns. Every subsequent sentence adds essential interpretive context (waived rules, unrun checks, not a design review). No filler or repetition of schema details.

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 tool has a rich output schema, so return-value details are already covered. The description covers the key contextual gaps: when to use it, how to interpret results (waived rules, unrun checks), and how it differs from a design review. For a read-only query tool with 100% schema coverage and an output schema, this is complete.

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 all five parameters thoroughly. The description adds value by clarifying the semantics of the 'rules' parameter ('YOUR OWN limits... never stored as if a fab had published it') and the 'vendor' parameter ('Returns geometric checks against that fab's stored profile... instead of the board's own DRC/ERC'). It also clarifies that 'category' filters violation details but counts are always returned. This goes beyond the schema's field-level descriptions.

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 states a specific verb ('returns'), a clear resource (stored DRC and ERC results for a board's current version), and explicitly distinguishes itself from a design review. It also names the sibling tool run_checks implicitly by saying 'This is not a design review,' which helps an agent differentiate it from the run_checks sibling.

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 says when to use it: 'Use when the user asks whether a board passes KiCad's own checks, or before trusting a design.' It also gives a clear exclusion: 'This is not a design review,' which routes the agent away from using this tool for broader design review tasks. It further clarifies the semantics of unrun checks, which is critical for correct interpretation.

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