Defiance Storefront

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds detail on the return content (canonical links, release state, from-price, stock availability) and a behavioral constraint (catalog facts only). This adds value 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 with no redundancy. The core purpose is front-loaded, and the constraint is appended 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?

For a read-only search tool with an output schema, the description covers what it searches, what it returns, and a key constraint. It lacks explicit routing to alternatives, but that's a minor gap given the tool's simplicity.

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 all three parameters are already documented. The description adds little beyond calling it a 'full-text search', which implies q is a query. It doesn't add syntax or format details 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?

States a specific verb ('search') and resource ('public catalog'), and enumerates the returned fields (sequences, canonical links, release state, price, stock). It distinguishes itself from sibling lookups by being a full-text search over the catalog, though it doesn't explicitly name alternatives.

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 notes 'Catalog facts only, never use guidance,' which gives a usage constraint, but it doesn't specify when to use this search vs the sibling lookup tools (e.g., sequence lookup). Usage context is implied but not explicit.

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 readOnly, idempotent, and non-destructive behavior. The description adds useful behavioral context beyond annotations by explaining the tool is educational only, takes no lot identifiers, performs no verification, and cannot be used for lot discovery. It does not describe the exact return content, but that is minor given 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?

The description is three sentences with no fluff: it states the main educational purpose, then immediately clarifies limitations and provides a routing suggestion. Key non-goals are front-loaded and every sentence adds value.

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 no output schema, the description is complete: it explains what the tool does, what it cannot do, and how to handle real verification needs. Nothing essential is missing for an agent to decide when to invoke 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%, with the single optional response_format parameter fully described by its enum and explanation. The tool description does not need to add parameter semantics because the schema already carries that burden, so the baseline score 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 states a specific purpose: explaining what a Certificate of Analysis is and how lot verification works, while linking the education course. It clearly differentiates itself from verification/lookup tools by explicitly stating it performs no verification and cannot discover lots.

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 gives explicit guidance on when not to use the tool: it cannot be used to discover lots or verify a real lot, and directs agents to point a human at the signed verifier for real lot checks. This provides clear context and an alternative path, meeting the when-not and alternative guidance criteria.

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 indicate read-only, non-destructive, and idempotent behavior. The description adds important caveats: claims are derived context (not measured values) and source titles/urls are third-party content to be treated as data, not instructions. This goes beyond annotations to prevent misinterpretation of the returned data.

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 main function and followed by critical caveats. There is no fluff or redundant information, and the structure is logical and easy to parse.

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 covers the purpose and important data-handling warnings. It does not explain how to interpret the 'evidence package' beyond the caveats, but that is not strictly necessary given the tool's scope. Slightly more detail on the structure of the return could be added, but it is not a significant gap.

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?

There is only one parameter, 'slug', with a minimal description 'The sequence slug.' The schema covers it fully, so the description adds no extra semantic value. The meaning is self-evident given the tool's purpose, 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 returns review-pending identity/commerce/quality claims and literature sources for one sequence. It is specific about the resource (sequence) and the type of data (claims and literature), distinguishing it from sibling tools like sequence_lookup or catalog_search.

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 no explicit guidance on when to use this tool versus alternatives. It does not mention conditions or contexts that would make this the preferred choice over sibling tools like defiance_sequence_lookup or defiance_catalog_search. Usage is implied but not clearly stated.

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 readOnly and idempotent. Description adds context about the content (policy details) and notes 'No inputs,' which is consistent with read-only behavior. No side effects mentioned, but not required given 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 short sentences, front-loaded with the primary purpose. No fluff.

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, the description covers the purpose and output. However, the contradiction about inputs creates a gap, and the response_format parameter is not mentioned in prose. Overall adequate but not complete.

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 documents one parameter with a clear description. However, the tool description says 'No inputs,' which contradicts the schema's parameter. This misleads agents into thinking no parameters exist and adds no 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?

States a specific verb 'Returns' and names the resource (platform policies) and the specific outputs (research-use-only boundary, prohibited uses, allowed/blocked lists). Clearly distinct from sibling tools like catalog or evidence lookup.

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?

No explicit guidance on when to use this tool versus alternatives. The title implies policy lookup, but no 'when' or 'when not' is mentioned. Sibling tools are listed but not contrasted.

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, so the tool's safety profile is clear. The description adds meaningful behavioral context beyond that: unreleased records state no price, and lot-specific certificate data is intentionally excluded, directing users to a different flow. These specifics help the agent anticipate edge cases without contradicting 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?

The description is two sentences: the first front-loads the primary purpose and return contents, the second addresses edge cases (unreleased records, lot-specific data). Every word earns its place; there is no fluff or repetition of the title or schema. It is compact and immediately useful.

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 two-parameter lookup tool with both parameters fully documented and no output schema, the description sufficiently covers what is returned (identity metadata, release state, availability, COA availability, evidence links), the behavior for unreleased records, and what is excluded. It provides enough context for an agent to invoke the tool correctly and interpret the result, even without an output schema.

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%: both 'slug' and 'response_format' have descriptive text in the schema. The tool description does not add parameter-level meaning beyond what the schema already provides, but it does contextualize the parameters by explaining the overall return content. Since the schema fully documents the parameters, a baseline score of 3 is appropriate; no extra semantic value is added.

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 the tool 'Returns the public record for one sequence' and lists the specific data included (identity metadata, release state, availability, COA availability, evidence links). It clearly distinguishes itself from catalog search (one vs. many) and from COA-specific tools by explicitly noting that lot-specific certificate data is not exposed, pointing to the 'signed COA flow' instead. This is a specific verb+resource with clear differentiation.

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 when to use the tool (to get a single sequence's public record) and gives a clear exclusion: 'Lot-specific certificate data is not exposed here; verify a specific lot through the signed COA flow.' While it does not explicitly name the sibling tool for COA lookup, it does route the agent away from this tool for lot-level verification, which is sufficient guidance for selecting among the listed siblings.

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