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Search Family Facilities

fda_search_family_facilities
Read-onlyIdempotent

Search FDA-registered facilities across a parent company and any explicitly linked subsidiaries. Use this when you know the parent company but the FDA records may sit under child entities like Actavis, Watson, or Cephalon. Supports optional city, state, country, and operations filters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name
limitNoMax results to return (1-500)
stateNoState code (e.g. CA, NY)
offsetNoResult offset for pagination
companyYesParent company name
countryNoISO country code (e.g. US, DE)
operationsNoDECRS operations keyword

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and idempotentHint=true, which communicate the safety profile. The description adds context about linked subsidiaries, which is useful, but does not disclose any additional behavioral traits such as pagination behavior, result format, or rate limits. Given the strong annotation coverage, a score of 3 is appropriate.

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

Conciseness5/5

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

The description is two sentences long and front-loaded: the first sentence states the core purpose, the second provides usage context and lists filters. Every sentence adds value, and there is no redundancy or filler.

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 search tool with no output schema, the description covers the essential aspects: what it searches, when to use it, and the available filters. Pagination details are already in the schema via limit/offset. The lack of return-value documentation is a minor gap, but not critical for a read-only search operation with full schema coverage.

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?

The input schema has 100% description coverage for all 7 parameters, so the schema itself carries the semantic load. The description only lists optional filters (city, state, country, operations) without adding meaning beyond what the schema already provides. The baseline is 3 for high schema coverage.

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 a specific verb ('Search') and resource ('FDA-registered facilities across a parent company and any explicitly linked subsidiaries'), and distinguishes this from the sibling tool fda_search_facilities by highlighting the parent/subsidiary scope. Examples of child entities (Actavis, Watson, Cephalon) reinforce purpose clarity.

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 states when to use the tool: 'Use this when you know the parent company but the FDA records may sit under child entities.' It gives clear context for the appropriate scenario. However, it does not explicitly mention alternatives or 'when not to use' cases, so it falls short of a 5.

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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