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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered; the description adds the return envelope including an errors[] channel, which usefully warns that partial-source failures are possible. It could still say whether sources are fetched in parallel or degrade independently (e.g. does a failing Ngram abort the call), which would push this to a 5.

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 tight clauses — sources, when to use, when not to use, returns — each earning its place, with the highest-value routing information front-loaded.

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?

All four parameters are optional with sane defaults, and the description covers sources, use cases, exclusions, and the return shape; only the per-parameter behavior (limit scope, geo semantics) is thin, which is a modest gap for a read-only aggregator.

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 only 25% — only query is documented — but the return key list ({query, geo, trending[], pageviews, ngram, errors}) implicitly maps to the include enum values, and 'regional' hints at geo. Still, limit, the geo format expectation, and the meaning of include=all vs individual values are left to the schema alone.

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?

Names the concrete sources it aggregates (Google Trends RSS, Wikipedia pageviews, Google Books Ngram) and the kind of question it answers, which cleanly separates it from web_search or cyberlibrary search siblings.

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 explicit when-to-use triggers (topic rising, long-term attention, regional trending, evidence of public interest) and an explicit do-not-use clause naming the two siblings (social_hot, prediction_market_odds) that cover adjacent needs.

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