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

Annotations already declare this is a safe, read-only, non-destructive operation, so the bar is lower; the description adds real context beyond them by disclosing free/pro size and sheet limits and by warning that proposed mappings snap to the nearest standard step and should be verified on screen before applying. That caveat materially changes how an agent should treat the output.

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?

Three sentences do the work in order: what it audits and how to feed it, what it returns, and the caveat about applying results. The long report enumeration is dense but every item is informative and nothing is redundant filler.

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?

With no output schema, the description carries the burden of describing returns and it does so thoroughly, listing each finding class and the mapping table shape. Remaining minor gaps are error/empty-input behavior and accepted color formats, which the schema partially implies.

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 three parameters including the {value, count} item form; the description largely restates this. It adds only the token categories accepted inside `values`, which is marginal value over the schema.

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 and resource ('Audit the scales behind a set of design values') and enumerates exactly what it reports, so an agent knows it produces a consolidation proposal, not just a lint. It does not differentiate itself from closely related siblings such as audit_type_scale, audit_spacing or check_contrast_tokens, which is the only gap.

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 three input modes (css, url, values) and their tier gating imply when each is appropriate, which is genuinely useful selection guidance for invocation. However, there is no statement of when to reach for this tool versus the narrower scale-specific audits in the sibling list, and no exclusions.

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