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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true, so the safety profile is covered. The description adds genuinely useful behavior the annotations cannot: the data source (CrUX), the 28-day rolling window, and p75 aggregation with good/NI/poor distribution shares. It stops short of noting that origins without sufficient traffic return no CrUX data.

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?

A single dense sentence, front-loaded with the resource and metric set, with no filler. The metric acronym list and the 'p75 + good/NI/poor shares' clause each carry information an agent needs to interpret the output.

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 adequately by naming metrics, aggregation level (p75), and distribution buckets. It is slightly incomplete on the segmentation parameter and on empty-data behavior, but an agent can call it correctly from this text.

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 50%: 'origin' has an example and 'form_factor' has an enum plus default but no prose. The description clarifies that 'origin' means the site origin rather than a full URL, which is real added meaning, but it says nothing about form_factor segmentation or what the ALL default aggregates. Enum values are largely self-explanatory, keeping this at the baseline.

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 ('Real-user Core Web Vitals ... for a whole origin'), the data source (Chrome UX Report), and the exact metrics returned (LCP, INP, CLS, FCP, TTFB). 'Whole origin' implicitly distinguishes it from a URL-level sibling like cwv_get_url, but no sibling is named explicitly, so differentiation rests on inference.

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?

Usage is only implied: 'whole origin' plus 'from the Chrome UX Report' signals this is the origin-level, field-data (not lab) option, which nudges the agent away from URL-level or Lighthouse-style tools. There is no explicit when-to-use/when-not statement and no mention of when CrUX data would be unavailable (low-traffic origins).

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