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

With no annotations, the description carries the full burden and does meaningfully disclose behavior: cross-source normalization into one shape, a unified severity class with stated derivation rules (Class I highest, FDA/USDA verbatim, CPSC derived from hazard language), newest-first ordering, and the HTTP/pricing/auth context (GET /v1/recalls, $0.01 via x402). It omits rate limits and error/empty-result behavior.

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 the core purpose and normalization model, with pricing/docs demoted to a bracketed footer. Dense but every clause earns its place; the severity-class digression is slightly heavy for a description but still informative.

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 4 params, no output schema, no annotations, and low schema coverage, the description adequately covers sources, normalization, and severity but leaves the agent without record-shape or three-of-four parameter explanations. Adequate but with clear gaps for a tool whose structured metadata is thin.

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 only 25% (only q is documented), so the description must compensate and does not. It adds no meaning for limit, since, or category, and notably never explains the 'vehicle' enum value, which the three named sources (FDA/USDA/CPSC) do not obviously cover.

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 resource (product recalls) and scope (FDA, USDA, CPSC aggregated into one normalized schema), clearly indicating this is the cross-agency tool. It does not name or contrast the category-specific siblings (gov_recalls_food, gov_recalls_drug, etc.), so differentiation is implied rather than explicit.

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?

Usage is only implied: covering all three agencies signals this is the general fallback vs the per-category siblings, and 'Newest first' gives ordering context. There is no explicit when-to-use/when-not guidance and no routing to the six category-specific recall tools, which is a notable gap.

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