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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool's scope (last 365 days), the source (CPSC API), and the caveat about keyword matching (title only, not supplier-specific). This is useful behavioral context, though it could go further by mentioning rate limits or error handling, but the description covers the key pitfalls.

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 a single, information-dense paragraph with no filler. It front-loads the core function (recall retrieval), then gives the data source, the output fields, and the important caveat about keyword matching, followed by a clear usage directive. Every sentence adds value, and it is compact.

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?

Given the tool's moderate complexity (3 optional parameters, specific API source) and the lack of an output schema, the description covers the essential aspects: what it does, the time window, the output fields, and the interpretation caveat. It could be more complete with an example of how to use pick vs. query, but the current description is sufficient for an agent to call it correctly in most cases.

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 100%, so the schema already documents all three parameters (pick, query, only_hits). The description adds minimal extra meaning beyond the schema, but it does imply that the tool filters by product category and keyword, which aligns with the parameters. No additional syntax or nuance is provided, so a baseline 3 is appropriate.

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 clearly states the tool's purpose: retrieving official US product recalls from the CPSC saferproducts.gov API for a product category within the last 365 days, including date, title, hazard, and URL. It specifies the data source, the time window, and the output fields, distinguishing it from other tools in the set.

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?

The description explicitly says 'Use before recommending or sourcing a category,' providing a clear context for when to use this tool. It also warns that a keyword hit means only the title contains the word, not that a specific supplier or SKU is affected, which helps agents avoid misinterpretation and guides them away from using it for supplier-level checks.

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