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Product Code Cross-Reference

fda_product_code_lookup
Read-onlyIdempotent

Cross-reference a device product code across classification details, 510(k) clearances, and PMA approvals. Returns classification info plus paginated lists of all clearances and approvals for that product code. Use to understand the regulatory landscape for a specific device type. Requires: product code.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
product_codeYesDevice product code
approvals_limitNoPMA approvals result limit
approvals_offsetNoPMA approvals result offset
clearances_limitNo510(k) clearances result limit
clearances_offsetNo510(k) clearances result offset

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safe read-only nature is established. The description adds behavioral context beyond the annotations by stating that it returns classification info plus paginated lists of all clearances and approvals, which is not captured by the annotations or schema alone.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded with the core action and return value. However, the final sentence 'Requires: product code' is redundant with the input schema and does not add value, preventing a perfect score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a read-only lookup tool with no output schema and a fully documented input schema, the description adequately explains what is returned (classification info plus paginated clearances/approvals) and the intended use case. It could mention empty-result behavior or how to navigate pagination more explicitly, but it is largely complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

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 parameters including product_code, approvals_limit, approvals_offset, clearances_limit, and clearances_offset. The description only adds 'Requires: product code,' which is redundant with the schema's required field, providing no additional semantic guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Cross-reference') and resource ('device product code across classification details, 510(k) clearances, and PMA approvals'). It also distinguishes itself from sibling tools like fda_search_510k and fda_search_pma by focusing on cross-referencing across all three data types in one call.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly says when to use the tool: 'Use to understand the regulatory landscape for a specific device type.' It does not mention when not to use it or list alternative sibling tools, but the intended use case is clear enough for an agent to select it appropriately.

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

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TDQS

A4.1/5.0
Disambiguation4/5

Most tools have distinct purposes with clear boundaries, such as fda_search_drugs for drug applications and fda_search_510k for device clearances. However, some overlap exists, like fda_device_udi and fda_device_udi_lookup both querying UDI data, which could cause confusion despite differences in scope.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with a clear fda_ prefix, using descriptive verbs like search, get, list, and link. This uniformity makes the set predictable and easy to navigate, with no deviations in naming style.

Tool Count2/5

With 48 tools, the count is excessive for a single server, making it overwhelming and difficult for agents to manage. While the domain is broad (FDA data), the toolset feels bloated with many specialized or overlapping tools that could be consolidated.

Completeness5/5

The toolset provides comprehensive coverage of FDA data domains, including drugs, devices, inspections, compliance, recalls, and facilities. It supports full CRUD-like operations (e.g., search, get, link, save) and lifecycle workflows, with no obvious gaps for the intended purpose.

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