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

Annotations already cover the safety profile (readOnlyHint, destructiveHint=false, openWorldHint, idempotentHint=false), so the description only needs to add context. It does add two useful traits absent from the schema: the data is live ('right now', consistent with non-idempotency) and it consumes exactly one keyword lookup, which matters for quota-sensitive agents. It stops short of describing latency, failure modes, or what happens when read_pages is false.

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 generated artifact and then the enumerated return sections; no filler. The long comma-separated list is readable but borders on inventory-style rather than prioritised prose.

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?

There is no output schema, so the description carries the burden of describing return values and it does so thoroughly, section by section. Remaining gaps — response size, whether reading competitor pages slows the call, and error behavior for zero-volume keywords — are minor for a read-only lookup tool.

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?

With 100% schema description coverage, the baseline is 3. The description adds indirect meaning by explaining why the headings of the top 3 pages matter ('what a page needs to cover to compete'), which motivates the read_pages toggle without naming it or stating its cost/speed trade-off.

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 the concrete resource precisely: Google's live first page for a search, enumerating the exact sections returned (top 10, AI Overview and cited sites, People also ask, related searches, own position, headings of the top 3 competitors). That is far more specific than the title. However, it never states a verb or names any sibling (e.g. get_ai_competitors, get_page_two, get_citations), so the 'compare' angle in the tool name is only implied by 'what a page needs to cover to compete'.

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 implied rather than stated: 'right now' signals a fresh live snapshot and 'Uses one keyword lookup' hints at the cost model for one call. There is no explicit when-to-use versus when-not, and none of the 25 sibling tools are named as alternatives for deeper competitor, citation, or page-two analysis.

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