Core Web Vitals trend

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

Annotations already declare the tool safe (readOnly, idempotent, non-destructive). The description adds substantial behavioral detail: exactly 1 API request, 28-day rolling window semantics, ineligible week skipping, Monday data updates, and a {no_data: true} response payload. This is high-value context beyond what annotations provide.

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 a dense but well-organized paragraph. It front-loads the core purpose, then packs essential details about response shape, defaults, data freshness, and constraints. No word is wasted; every clause earns its place.

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?

Given 5 optional parameters and no output schema, the description fully compensates by specifying the response structure ('points' array, 'delta' with direction), the no-data payload, update cycle, and per-parameter guidance embedded in the schema. The tool is complex, and the description makes it self-sufficient.

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%, with each parameter already fully described in the input schema (mutual exclusion, defaults, enum restrictions, formatting rules). The description mostly adds output interpretation ('lower is always better', 'ineligible weeks are skipped') rather than parameter-level meaning, so it does not raise above the high-coverage 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 opens with a specific, action-oriented statement: 'Weekly p75 trend for an origin or URL from the CrUX History API (1 request).' This clearly names the resource (CrUX History API), the scope (origin or URL), and the granularity (weekly p75), which distinguishes it from siblings like get_core_web_vitals or compare_form_factors.

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 provides clear usage context: 'Provide exactly one of origin or url', fallback guidance for no_data, a note on update cadence, and parameter caps. It does not explicitly name alternative sibling tools or state 'use this instead of X', so it misses the top tier for alternative differentiation, but the context is strong.

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