Defiance Storefront

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

Annotations already declare readOnlyHint and idempotentHint. The description adds that results include canonical links, from-price, stock availability, and the 'catalog facts only' constraint, enhancing transparency without contradicting annotations.

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 concise sentences, front-loaded with the core action, and no redundant phrases. Each sentence contributes a distinct aspect: search scope, result contents, and boundary.

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 search tool with complete schema, rich annotations, and an output schema, the description is sufficient. It explains the public dataset, return fields, and an important caveat, making it fully contextual.

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 covers 100% of parameters (q, limit, response_format) with full descriptions. The description only affirms the result shape and doesn't add additional parameter semantics, so it stays at baseline 3.

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 opens with 'Full-text search over the public research-use-only catalog,' identifying the action, resource, and scope. It differentiates from sibling lookup tools by restricting to catalog facts and excluding guidance.

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 clearly states the catalog is for research-use-only and that it never provides guidance, giving an exclusion but not naming a specific alternative tool. The context of full-text search is clear, though explicit when-to-use alternatives could be stronger.

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?

Beyond the readOnlyHint and idempotentHint annotations, the description discloses that the tool takes no lot identifiers and cannot be used to discover lots, which is critical behavioral context. It also notes it links to a course, adding value over the annotations alone.

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 three sentences, each serving a distinct purpose: stating the function, clarifying limitations, and providing practical guidance. It is front-loaded with the main purpose and contains no filler or redundancy.

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 optional parameter and comprehensive annotations, the description covers purpose, constraints, and usage alternatives. It also implies the return type via the response_format parameter, making it complete enough for an agent to select and invoke the tool 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?

The schema has 100% coverage and the only parameter, response_format, has a clear description of its enum values and default. The tool description does not add extra parameter semantics, but the schema already fully explains the parameter, so the baseline of 3 is appropriate.

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 explains what a Certificate of Analysis is and how lot verification works, using the specific verb 'explains' and resource 'education course'. It explicitly distinguishes itself from verification tools by stating it 'performs no verification' and cannot be used to discover lots, setting it apart from sibling lookup tools.

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 provides explicit usage guidance: it is for educational purposes and linking to a course, not for actual verification. It also instructs the agent to 'point a human at the signed verifier' for real lot checks, giving a clear alternative and when-not-to-use guidance.

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?

Beyond the readOnlyHint annotation, the description discloses that claims are 'derived context, never measured lot values or efficacy statements' and warns that third-party source URLs must be treated as data, not instructions. These are non-obvious behavioral and safety traits that materially improve safe invocation.

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 two sentences, front-loaded with the core function, and the second sentence delivers essential caveats. Every sentence earns its place with no redundancy or filler.

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 read-only tool with one parameter, the description is complete: it identifies the return categories (claims and literature sources), flags their derived status, and warns about third-party content. No output schema exists, but the description supplies enough context for correct invocation and 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?

The input schema already fully documents the single 'slug' parameter with 100% coverage. The description adds only the context that it is per-sequence, not new parameter-level semantics. With high schema coverage, baseline 3 is appropriate.

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 ('Returns') with a precise resource scope: 'review-pending identity/commerce/quality claims and literature sources for one sequence.' This clearly distinguishes it from broader search or lookup sibling tools by emphasizing the evidence-package nature and the per-sequence scope.

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 implies usage ('for one sequence') and clarifies it returns evidence rather than raw sequence data, but it does not explicitly state when to use this tool over siblings or provide exclusion criteria. No alternatives are named, so guidance remains implicit rather than actionable.

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 readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which cover the safety profile. The description adds useful context about the tool's output content. However, the statement 'No inputs' is inaccurate because the schema defines an optional response_format parameter, which slightly misrepresents the tool's 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?

The description is concise and front-loaded with 'Returns,' covering all essential content in a single sentence. However, the 'No inputs' clause is both unnecessary and incorrect, which detracts from overall efficiency and precision.

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 tool has no output schema, so the description must explain return values, which it does: research-use boundary, prohibited uses, and allowed/blocked machine data. It does not mention the optional response_format parameter or the ability to choose output format, and the 'No inputs' claim is misleading. Overall, it is adequate but has clear gaps.

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 schema fully documents the single parameter (response_format) with an enum and description, so baseline is 3. However, the description explicitly claims 'No inputs,' which contradicts the schema. Since the description actively misleads about the parameter, it adds negative value rather than complementing 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 verb 'Returns' and the specific resource: the platform's research-use-only boundary, prohibited uses, and allowed/blocked public machine data. This distinguishes it from sibling tools like catalog_search, evidence_lookup, and sequence_lookup, which focus on different content domains.

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 provides clear context for when to use this tool: when the agent needs to understand research-use boundaries, prohibited uses, or data access rules. It does not explicitly name alternatives or exclusions, but the specificity of the content makes the intended usage obvious.

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 annotations already establish read-only, idempotent, non-destructive behavior. The description adds value by clarifying the public research-use-only scope, listing included fields, and explicitly stating what data is not exposed (lot-specific certificate data). This is useful context beyond the annotations.

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-loaded with the primary action and return content, and no wasted words. The exclusion of lot-specific data is noted efficiently as a second sentence.

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 no output schema, the description covers what is returned (identity metadata, availability, COA availability, evidence links) and what is not (lot-specific certs). It also provides next-step guidance via the COA flow, making it appropriately complete for this simple tool.

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 schema already explains both parameters. The description does not add new parameter details beyond reinforcing the 'one sequence' concept tied to the slug, giving no additional semantic value.

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 returns a record for one sequence by slug, listing key fields (identity metadata, availability, COA availability, evidence links). It distinguishes itself from siblings by explicitly noting it is a single-sequence lookup and that lot-specific certificate data is excluded.

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 explicitly states when not to use this tool ('Lot-specific certificate data is not exposed here') and points to an alternative ('verify a specific lot through the signed COA flow'). This provides clear usage direction beyond what the schema conveys.

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