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

No annotations are present, so the description carries the disclosure burden. It states the operation and output, and explicitly notes plain-language support in any language, but it does not mention error behavior, rate limits, data freshness, or read-only status—mostly inferable from 'Search' but not explicit.

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?

Two sentences front-load the core purpose and query modes, then give the output shape. There is no filler, tautology, or unnecessary repetition.

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 or annotations, the description usefully states return contents and query flexibility. It is slightly incomplete around limit behavior and error cases, but for a search tool it provides enough to call correctly.

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?

The schema already documents the query parameter well, and the description adds the 'any language' behavior and an example. However, it adds nothing about the limit parameter beyond the schema's numeric bounds, so at 50% schema coverage it only partially compensates for the gap.

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 action (search), concrete resource (vehicle safety recall notices across seven named registers), and query dimensions (recall number, make/model, plain-language). This differentiates it from siblings like get_recall_notice by emphasizing multi-register search and citation-oriented output.

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 clear context: use when you need to find recall notices by recall number, make/model, or problem description, and returns titles and URLs for citation. It does not explicitly name sibling tools or say when not to use them, but the supported query modes and output make the intended use obvious.

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