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

With readOnlyHint=false declared, the description supplies the reason: results are 'Saved in the user's Puley history', explaining why a lookup tool is not read-only. It also discloses the data provenance ('Numbers are Google's own (Google Ads data)') and a hard input limit (up to 10 keywords) that the annotations do not cover. It stops short of describing rate limits, failure modes, or how the history entry behaves.

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?

Front-loaded with the payoff (the four metrics in one table), then parameter formats, then provenance — a sensible order with little waste. The opening is a long clause chain rather than a crisp summary sentence, which slightly slows scanning.

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?

No output schema exists, and the description compensates by naming the returned columns ('in one table') and the data source, plus the 10-keyword limit. Missing are the table's actual column layout for multi-keyword input and any error or partial-failure behavior, but nothing essential to making the call is absent.

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 0%, so the description carries the full burden and does: keywords is comma-separated with a concrete two-term example and a 10-item cap, and country is specified as a two-letter code. That is meaningfully more than the bare string types in 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?

The description enumerates the exact outputs (monthly search volume, cost-per-click, trend direction, related searches) delivered 'in one table', so an agent can tell what resource it gets back. The verb is only implicit ('gives you this data'), and it never distinguishes itself from the sibling search_trends, which plausibly also covers 'whether interest is rising or falling'.

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 by the tool's subject matter; there is no statement of when to prefer it over search_trends, google_results, or find_ads, and no exclusions or prerequisites (e.g., account connection, quota). An agent can infer intent but must guess at boundaries.

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