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lzinga

US Government Open Data MCP

fda_food_recalls

Read-only

Search FDA food recall enforcement reports by classification (Class I to III), recalling firm, or reason for recall such as listeria.

Instructions

Search FDA food recall enforcement reports. Class I (may cause death), Class II (temporary health problems), Class III (unlikely harm).

Example searches:

  • 'classification:"Class I"' — most serious recalls

  • 'recalling_firm:tyson' — recalls by a specific company

  • 'reason_for_recall:listeria' — recalls due to listeria

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoOpenFDA search query. Examples: 'field:value', 'field:"Exact Phrase"', 'field:[20200101+TO+20231231]', '_exists_:field'. Combine with '+AND+', '+OR+', '+NOT+'.
limitNoMax results (default 10, max 100)
Behavior3/5

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

The description aligns with the readOnlyHint annotation by using 'Search.' It adds the classification definitions (Class I, II, III) but lacks details on pagination, rate limits, or data freshness that would aid behavioral understanding beyond annotations.

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 extremely concise (5 lines) with a clear front-loaded purpose. Every sentence serves a purpose: stating the verb, explaining classifications, and providing examples. No redundant words.

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

Completeness3/5

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

Given the absence of an output schema, the description does not explain what the returned reports contain (fields, structure), which is a gap for a search tool. It also doesn't mention limit behavior or pagination. More information on output would improve completeness.

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

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 100% schema description coverage, the description still adds value by providing concrete example search syntax for the 'search' parameter, showing exact field-value pairs and operators, which enhances understanding of how to construct queries beyond the schema.

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 purpose: 'Search FDA food recall enforcement reports.' It provides specific examples and differentiates from other FDA tools by focusing on food recalls, distinguishing it from siblings like fda_drug_recalls.

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 includes example search queries showing how to filter by classification, firm, and reason, giving clear usage context. However, it does not explicitly state when not to use this tool versus other FDA recall tools, which would be helpful for disambiguation.

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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