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

Annotations already declare readOnly, idempotent, openWorld and non-destructive, so the safety profile is covered. The description adds genuinely useful behavior beyond that: default sort order, the underlying data source and its publication lag versus FDA announcements, and the set of fields returned. It does not discuss paging limits or rate behavior, but the schema handles the caps.

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?

Three dense sentences: purpose and scope first, then filters, then return shape and the data-lag caveat. No filler, and the most decision-relevant facts are front-loaded.

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?

No output schema exists, so the description compensates by enumerating the returned fields (recall number, class, status, firm, product, reason, distribution, dates, record link). Combined with the 100%-covered input schema and the source-lag caveat, an agent has everything needed to call it 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?

Schema coverage is 100%, so the baseline is 3. The description earns above baseline by explaining that keyword matching is conjunctive across all words, that quoted phrases are kept intact, and that keywords are matched against product description, reason, firm and lot/code fields — semantics the schema's 'Keywords ... Up to 6 words' does not convey.

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 ('Searches FDA recall enforcement reports published through openFDA') plus scope (food, drugs, medical devices) and default ordering (newest report date first). This is clearly distinguishable from the vehicle/consumer-product recall siblings, which target different agencies and datasets.

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 for when this is the right source (FDA Enforcement Report data, 2012 onward) and a useful caveat that it can lag FDA's recall announcements. It does not explicitly name a sibling or state when to prefer another tool, so it falls short of full alternative routing.

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