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

Beyond the readOnly/openWorld annotations it discloses non-obvious traits: only the first page is returned (v1), there is no per-product URL so `url` is omitted, `image` is best-effort, ids are stable across searches, and listing plugins bill one unit per result page. That is exactly the context annotations cannot carry.

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 what it returns, then parameters, then caveats and billing. Dense but every sentence carries information; the single-block format and parenthetical asides make it slightly harder to scan than a bulleted layout.

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 substitutes by listing every returned field, and it covers pagination limits, missing fields, and cost model. Nothing an agent needs in order to call this correctly appears to be missing.

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%, so the baseline is 3; the description earns more by explaining why `gl`/`proxy_country` matter (region-specific prices/merchants) and that `productId`/`catalogId`/`offerId` are stable identifiers for tracking a single product.

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?

States a specific verb and resource ('Runs the Google Shopping vertical (`udm=28`) for `q` and returns the product cards') and enumerates the returned fields, so an agent can distinguish it from google_search, amazon_search, or walmart_search without opening the schema.

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 concrete guidance on when to set `gl`/`proxy_country` (region-specific prices) and `min_price`/`max_price` filtering, and warns to keep `max_results` modest for cost reasons. It stops short of explicitly naming which sibling tool to use when Google Shopping is wrong, so no full when-not/alternative routing.

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