Safe-Check (recall + counterfeit)

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

Without annotations, the description must fully disclose behavior. It describes the two components (marketplace risk and price comparison), the return fields (risk level, score, signals, advice), and notes it is a signal, not proof. This provides adequate transparency for a non-destructive tool.

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 composed of three sentences, each adding distinct information: primary purpose, methodology, and return values. It is front-loaded with the main action and avoids redundancy, making it highly efficient.

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 low complexity (3 params, no output schema, no nested objects), the description covers the key aspects: what it does, how it works, and what it returns. It is sufficiently complete for an agent to understand and invoke 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?

With 100% schema coverage, the baseline is 3. The description adds value by explaining the purpose of each parameter: query (product/brand with examples), price (for comparison against retail median), marketplace (optional with examples). This enhances understanding beyond the schema.

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 primary function: assessing counterfeit risk for collectible listings. It specifies the combined methodology (marketplace base-risk plus price vs retail median) and distinguishes it from siblings by focusing on risk assessment rather than recall lookup or safe check.

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 explains the tool is for assessing counterfeit risk as a signal, not proof, which implies usage when evaluating collectibles. It doesn't explicitly state when not to use it or suggest alternatives, but the context is clear enough for an agent to decide.

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?

No annotations provided, so description must cover behavioral traits. It discloses that results include agency source links and last-updated dates, but lacks details on rate limits, authentication needs, or whether it's purely read-only.

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?

Two concise sentences front-loading purpose and example usage with no filler. Every sentence earns its place.

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?

For a simple tool with one parameter and no output schema, the description adequately covers purpose, input examples, and output contents. Minor omission of detailed return structure, but functionally sufficient.

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% with one parameter already described. Description adds valuable examples ('Peloton bike', 'stroller') clarifying the expected input format, going beyond the schema.

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?

Clearly states it looks up US product recalls using live government feeds, with specific examples. Does not explicitly differentiate from siblings counterfeit_risk and safe_check, but context implies recall-specific focus.

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?

Provides explicit when-to-use context ('Use to check if something is recalled before buying/using it'), but does not mention when not to use or provide alternative sibling tools.

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?

No annotations are provided, so the description bears full burden. It mentions combining two checks but gives no info on side effects, read-only status, rate limits, or other behavioral traits.

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 short and front-loaded, but it omits necessary details about parameters and behavior, making it somewhat under-specified for the tool's complexity.

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 complexity of combining two checks, no output schema, and zero parameter descriptions, the description lacks sufficient context about return values, limitations, or interpretation.

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%, and the description does not explain any of the three parameters (query, price, marketplace), leaving their purpose and constraints unclear.

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 it combines a recall lookup and counterfeit-risk check into one call, and distinguishes itself from sibling tools by being a general-purpose product safety screen.

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?

It says 'Best general-purpose product-safety screen,' implying when to use it, but doesn't explicitly state when not to use it or what alternatives are for specific needs like counterfeit-only checks.

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