China Medical Device Lookup

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds useful context by stating that the tool takes no arguments and returns only the standard document, not records or facts, but it does not describe the document's structure or any pagination/format details.

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 sentences with no wasted words. The core purpose is front-loaded, and the clarifying exclusions ('not business records or an assessment of facts') are valuable for agent decision-making.

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 zero-parameter, read-only, idempotent tool, the description is complete enough. It tells an agent what the tool returns, what it does not return, and that no arguments are needed. The lack of an output schema is offset by the clear high-level description of the document.

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 are zero parameters, and the description explicitly confirms 'Takes no arguments,' so there is no ambiguity about invocation. Baseline for zero-parameter tools is 4, and the description removes any doubt about whether arguments are needed.

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 ('Retrieve') and a clear resource ('definitions of information formation classes, provenance fields and snapshot/version metadata'), and further clarifies that it returns the information-standard document rather than business records or factual assessments. It is clear on its own, though it does not explicitly differentiate itself from likely-related siblings such as get_standard_metadata.

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 its use case: call this tool when you need the standard definitions/metadata document, and it explicitly says it does not return business records or factual assessments. However, it does not name alternatives or explain when to prefer this over sibling tools like get_standard_metadata or search_standard_metadata.

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 goes well beyond the readOnlyHint and idempotentHint annotations by disclosing that the query performs no inference or aggregation, is limited to the available snapshot, returns an empty data array on no matches, and raises argument errors for missing or invalid input. These are concrete behavioral traits an agent needs before calling.

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 compact and front-loaded: purpose first, then return shape, then behavioral caveats, then errors. Every sentence contributes useful information, and there is no redundant or filler content.

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?

Even without an output schema, the description provides the important return characteristics: paginated structured records, specific fields, empty behavior, snapshot limitation, and error behavior. Combined with the comprehensive input schema, an agent has everything needed to 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?

Schema description coverage is 100%, so the schema already documents all four parameters thoroughly. The description adds no parameter-level detail beyond stating that company is required cancels; it does not improve on the schema's literal-match, pagination, and snapshot semantics.

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 a specific verb and resource: 'Find recorded medical-device products associated with a company or registrant name.' This clearly states what the tool returns and the key lookup dimension, making it easy for an agent to distinguish it from device-specific or category-based search siblings.

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 clear context for when to use this tool: when querying by company/registrant name and when only recorded snapshot facts are needed. It explicitly excludes inference and aggregation behavior, which helps an agent choose this over more analytical alternatives, though it does not name specific sibling tools or provide explicit when-not-to-use conditions.

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 annotations (read-only, idempotent, non-destructive), the description discloses that the query performs no inference or aggregation, is limited to the available snapshot, returns an empty array on no match, and raises argument errors on invalid input. These are substantive behavioral details not present in 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 compact and front-loaded with the primary purpose, followed by inputs, returns, and behavior. A small amount of redundancy ('Inputs: udi' and 'Required: udi') and the error sentence could be trimmed, but overall 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?

With no output schema, the description appropriately summarizes the return shape (paginated records, source_class, provenance, snapshot, pagination, limits) and covers no-match and error behavior. It relies on the thorough input schema for pagination defaults and next_offset semantics, which is acceptable.

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 applies. The description only restates that udi is required and does not add parameter-level details about limit, offset, or snapshot; it does clarify error behavior for missing required input, which is mild added 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 and resource: 'Look up medical-device records when a UDI identifier is known.' This clearly identifies the exact-match lookup purpose, and the mention of a known UDI implies a distinction from search-based siblings, though no sibling is named explicitly.

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 a clear usage condition ('when a UDI identifier is known'), and notes that no match or invalid input yields specific results. It does not name alternative tools or state when-not-to-use in relation to siblings, so it stops short of explicit routing.

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. The description adds meaningful context beyond that: it states 'performs no new inference or aggregation', notes 'Coverage is limited to the available snapshot', and explains empty results and error behavior. These details enrich the agent's understanding of call outcomes 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 front-loaded with the core purpose, then flows into inputs, return behavior, and error conditions. It is succinct with no filler, though it repeats 'registration_no' twice (in 'Inputs' and 'Required'), which is a minor redundancy. Still, every sentence contributes critical information, earning a 4.

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 tool with four parameters and no output schema, the description is remarkably complete: it explains pagination, snapshot behavior, empty results, and error handling. It references 'source_class, provenance, snapshot, pagination and limits' as return elements, but does not detail the structure of each record, which would push it to a 5. Given the constraints, it is well-rounded and sufficient for correct invocation.

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 each parameter already fully documented in the input schema. The description adds only marginal value on parameters, mentioning registration_no as required and hinting at pagination via 'paginated structured records'. It does not go beyond the schema's detailed parameter descriptions, 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's purpose: 'Find medical-device records associated with a registration or filing number.' It specifies a precise verb and resource, and the input registration_no makes the scope distinct from sibling tools that search by company or device. However, it does not explicitly name or differentiate from siblings, so it stops short of a 5.

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?

Usage is implied rather than explicit: the tool is for when you have a registration or filing number, and 'Required: registration_no' reinforces that. But the description provides no guidance on when not to use it or how it compares to alternatives like get_udi_company_products or search_udi_products. This matches the 'implied usage' level.

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?

Adds meaningful behavior beyond the read-only/idempotent annotations: no inference or aggregation, snapshot-limited coverage, paginated structured records, empty array on no match, and argument error on invalid input. This is exactly the context annotations do not convey.

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?

Four sentences with the purpose and return shape front-loaded, followed by edge cases and requirements. Minor redundancy ('Inputs: category' vs 'Required: category') but no wasted sentences.

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 paginated search tool with rich schema and annotations, the description covers return structure, pagination fields, no-match behavior, snapshot limitation, and errors on missing/invalid input. Nothing an agent needs to invoke it correctly is missing.

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 all four parameters at 100%, so the description only needs to add marginal semantics. It reiterates that category is required and notes validation error behavior, but does not add 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 ('Find') and resource ('medical devices by a recorded category name or classification code'). Clear and distinct from sibling tools by naming the category-based scope, though it does not explicitly contrast with search_udi_products.

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?

Implied usage is when searching devices by recorded category or code, but there is no explicit when-to-use guidance or mention of alternatives. No exclusions or conditions compared to sibling tools are provided.

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 and destructiveHint=false, so the safe, read-only nature is covered. The description adds valuable behavioral details: it performs no inference/aggregation, is limited to the available snapshot, and returns empty data array on no match. This goes beyond the annotations, justifying a 4.

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 a single paragraph with no filler, front-loading the primary purpose and then covering key behaviors. Every sentence adds value—purpose, behavior, coverage, and error handling—without redundancy. It is concise and well-structured.

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 is moderately complex with four parameters, but the schema covers all parameter semantics. The description explains pagination and snapshot behavior, and the annotations cover safety. It lacks explicit details on return value structure, but output schema is absent, so the description does not need to over-explain returns. A 4 is appropriate for completeness.

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%, so the schema already documents all four parameters in detail. The description reinforces the required nature of 'query' and notes the empty-array behavior on no match, which complements the schema. Since coverage is high, the baseline is 3, but the description adds useful context about the query behavior, moving it to 4.

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 'Find' and the resource 'medical devices by product or trade-name text'. It distinguishes this tool from siblings like get_udi_device (which likely fetches a single device) and search_udi_category (which searches by category), making the purpose unambiguous.

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 provides clear context on how to use it (search by product/trade-name text, returns paginated records, requires query). It does not explicitly name alternatives or conditions for when not to use it, but the sibling names (e.g., search_udi_category) imply alternatives exist, so a 4 is appropriate.

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