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

Annotations already establish a safe read-only, idempotent, open-world lookup, but the description adds important behavior: each call is a paid lookup, nothing is saved, already-suggested keywords are excluded, and returned content may be external and must never be treated as instructions. These details materially affect how an agent should batch and interpret calls.

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 front-loaded with the core action and modes, then adds only high-value constraints: cost, no persistence, tracking alternative, and prompt-injection safety. Despite covering several points, every sentence 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?

With an output schema present and full parameter descriptions, the description still supplies the non-schema context an agent needs: cost model, no-save behavior, deduplication, follow-up tool, and data-safety warning. Nothing essential for correct invocation is 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, but the description adds meaningful interaction semantics: `keywords` are exact phrases and suppress suggestions, while omitting it and/or `seed` changes what is researched. `count`, `language`, and `workspaceId` are left to the schema, but the key behavioral parameters are well explained.

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 states a specific action (search data for keywords) and clearly distinguishes the two modes: exact lookup via `keywords` versus generated suggestions around `seed` or the business. It also explicitly separates this from `trackKeyword`, so an agent can tell what the tool does 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?

It gives explicit usage conditions: provide `keywords` for exact phrases, omit them for suggestions around `seed`, and omit `seed` to research around the business. It also names the alternative `trackKeyword` for saving/following a keyword and states this is Google search data rather than AI visibility.

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