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

Goes well beyond the readOnly/idempotent/openWorld annotations by disclosing pricing ($0.005 USDC per successful call, x402 on eip155:8453), the failure-billing rule (not charged if a source is down), result ordering (newest first), and the semantic that an empty result is still an answer. These are exactly the operational details an agent cannot infer from structured fields.

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 sentences, all front-loaded: inputs, output shape, then operational/cost caveats. Every clause carries information, though the output-field enumeration and billing details make it dense rather than terse. No filler or 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, the description carries the return-value burden and does so by enumerating the normalized fields (date, title/product, hazard/reason, remedy, classification, firm, link). Combined with source coverage and billing semantics, an agent has everything needed to call and interpret it.

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 baseline is 3, and the description adds value by restating the two parameter groupings (product/brand text vs. vehicle make-model-year) so the agent knows which fields to combine. It adds little on limit or category beyond the schema, but it clarifies the either/or input pattern the enum alone would not.

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 ('returns matching official U.S. recalls') and names the three authoritative sources (CPSC, NHTSA, FDA), leaving no ambiguity about what the tool does. None of the siblings (crawler, domain_verify, sec_company, etc.) overlap, so differentiation is automatic.

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 defines the two input modes clearly: a product/brand name for consumer/food/drug/device categories, or make/model/year for vehicles. It does not name alternatives or state exclusions, but no sibling competes for this use case, so the guidance is sufficient context without explicit when-not rules.

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