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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavioral context the annotations do not carry: the data source and license (CC BY 4.0), the attribution obligation when citing a norm to a user, and that access is free. It does not describe freshness, caching, or response shape.

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 metric list and the validate_design pointer are front-loaded and earn their place, but the promotional register ('ACTUALLY', 'not opinions', capitalised emphasis) inflates the text and adds no selection value. It is one dense block rather than wastefully long, but a portion of it is hype rather than information.

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 must carry the return content, and it does by enumerating the benchmark fields an agent can expect. The one remaining gap is the response's structural form (single object vs. per-metric records) and any freshness caveat, but for a zero-parameter read tool this is close to 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?

The tool takes zero parameters and schema description coverage is 100%, so there is nothing for the description to disambiguate. Baseline of 4 applies for a parameterless tool.

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 names a specific resource (live-measured web design norms) and enumerates the exact metrics returned — median design score, border-radius, font sizes, colour split, spacing grid, motion duration. It also distinguishes itself from the sibling validate_design. It stops short of a clean verb+resource framing ('get_web_benchmark' is never restated) because the opening is marketing copy rather than a functional statement.

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?

It states when to use it ('ground design decisions in real norms') and names the alternative for a related-but-different job ('To grade specific values of your own design, call validate_design(...)'). No explicit when-not-to-use or negative conditions are given, but the routing guidance is clear and actionable.

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