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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantial extra context: it is executable, fetches the URL and probes the origin via HEAD/GET, needs no browser, and results are cached ~24h. That caching and network-probing behavior is not derivable from the annotations.

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?

Front-loaded with purpose, then checks, then exclusions, then execution model and return shape. Dense and mostly earned, though the ten-artifact enumeration and return-object dump make it longer than strictly necessary.

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?

No output schema exists, yet the description spells out the return JSON fields (ok, url, score, grade, pass/warn/fail, checks[]), the execution model, and caching. Nothing material is missing for correct invocation.

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% and the single url parameter is already documented with its default in the schema, so the description needn't add parameter detail. It adds nothing beyond the schema, making the baseline 3 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?

States a specific verb (Score) and resource (a URL for design-system AI readiness) and enumerates the ten artifacts probed, so an agent knows exactly what this does. It also differentiates itself from siblings by naming designesy_score and designesy_drift_score.

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?

Gives an explicit use case (verify whether a design system is the default context AI tools build from) plus an explicit 'When NOT to use' clause routing to designesy_score for contract scoring and designesy_drift_score for drift detection.

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