Consumer Product Recall Evidence

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

The description adds real context the annotations don't: a $0.20 cost and the explicit refusal to make remedy or safety conclusions. However, 'Purchase' implies a monetary side effect that readOnlyHint=true and idempotentHint=true do not convey, and there is no detail on latency, rate limits, or what the package returns.

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?

One compact sentence with the cost and the scope disclaimer front-loaded; no filler. It is under-specified rather than bloated, which is a completeness problem, not a conciseness one.

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, no annotation detail on returns, and 0% schema coverage, the description should explain what an 'evidence package' contains and what product_token identifies. Instead it leaves the core mechanics and the relationship to sibling tools undefined.

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 0% for the single required product_token, so the description must compensate and it does not — it never mentions the parameter, its format, or where its value comes from. Only the bare type is available to the caller.

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 names the domain (CPSC hazard/remedy evidence) and discloses a price, but the verb 'Purchase' is odd for a tool named build_..._evidence and 'evidence package' is an abstraction. Nothing distinguishes it from the siblings match_product_recall or resolve_consumer_product, so an agent can't tell which to pick.

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?

There is no statement of when to call this versus match_product_recall or resolve_consumer_product, and no hint that product_token likely comes from resolve_consumer_product. The only guidance given is negative scope ('no individual-unit remedy completion'), which limits claims rather than directing usage.

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

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

The description adds genuinely useful behavioral context beyond the annotations: the call costs $0.03, which an agent should know before invoking. However, 'Purchase' reads oddly against readOnlyHint=true and is not clarified, and nothing is said about what an exact match returns (boolean, confidence, notice payload).

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?

It is a single short sentence with no wasted words, and the cost is front-loaded. But it is terse to the point of under-specification, so brevity here is not purely a virtue.

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?

The input is a one-string schema and the annotations already declare read-only, idempotent, open-world behavior, so little more is strictly needed. The remaining gap is what a 'match result' contains and how tokens are sourced, which the description leaves implicit.

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 single required parameter product_token has 0% schema description coverage, and the description does not explain what a token is or how to obtain one (presumably from resolve_consumer_product). With one undocumented parameter, the description fails to compensate for the schema 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?

The description names the resource (an exact CPSC recall-notice match result), which is more specific than a bare tautology, but 'Purchase' is a confusing verb for a read operation and no scope or product is mentioned. It also does not distinguish this from siblings build_product_recall_evidence or resolve_consumer_product.

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?

There is no when-to-use guidance, no prerequisites, and no mention of alternatives, despite two closely related sibling tools existing. The only implicit cue is the price, which hints at a paid lookup but does not say when it is warranted over the cheaper/different siblings.

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

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

Annotations already declare read-only, idempotent, and open-world behavior. The description adds meaningful context beyond that: it is free, matching is conservative, and crucially, absence of a match is not proof of safety. It doesn't describe what a positive match returns, but the added caveat is valuable.

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?

A single, front-loaded sentence with no wasted words. The 'Free:' prefix and the key caveat are both delivered efficiently.

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?

Annotations cover safety profile, but with no output schema and zero parameter descriptions, the description should do more. It doesn't say what a successful match returns (e.g., a recall notice identifier or details) or explain the optional manufacturer field.

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 0% for all three parameters. The description only clarifies that 'model' should be exact, leaving product_name and manufacturer unexplained. It does not compensate for the schema 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?

The description states a specific verb (match) and resource (published CPSC recall notice) with the constraint of an exact model. It is clear what the tool does, but it doesn't distinguish itself from the sibling match_product_recall, which sounds very similar.

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 offers only an implicit cue ('Free' suggests a low-cost first check) and a caveat about absence. There is no explicit guidance on when to use this tool versus match_product_recall or build_product_recall_evidence, nor any prerequisites or exclusions.

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