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cyntrica

Gov Data MCP

by cyntrica

fda_food_adverse_events

Read-only

Search CAERS food adverse event reports for illnesses, allergic reactions, and injuries from foods and dietary supplements. Filter by reactions, outcomes, or industry using openFDA query syntax.

Instructions

Search FDA food adverse event reports (CAERS database). Reports of illnesses, allergic reactions, and injuries from foods and dietary supplements.

Example searches:

  • 'products.industry_name:"Dietary Supplements"' — supplement events

  • 'reactions:"hospitalization"' — events involving hospitalization

Count fields: reactions.exact, outcomes.exact, products.industry_name.exact

Input Schema

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

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

Annotations already declare readOnlyHint=true, so safety is covered. The description adds useful context (CAERS database, example query fields) but doesn't disclose additional behavioral traits like pagination, rate limits, or result format. Beyond the annotation, it offers modest added transparency.

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 well-structured: one intro sentence, two useful example searches, and a count-fields note. Every sentence earns its place with no filler or redundancy.

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 2-param read-only search without an output schema, the description covers the database, content type, example queries, and count fields. It doesn't describe the response format, but the examples and context are sufficient for basic usage.

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?

Schema coverage is 100% with detailed search syntax and limit description. The description adds value by giving tool-specific example queries and mentioning count fields (reactions.exact, outcomes.exact), which helps the agent construct valid queries beyond the generic 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 'Search FDA food adverse event reports (CAERS database)' with a specific verb and resource. It further specifies the content (illnesses, allergic reactions, injuries) and distinguishes from sibling tools like fda_animal_events or fda_drug_events.

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?

Provides clear context on what the tool covers (foods and dietary supplements) and includes concrete example searches with field values (e.g., 'products.industry_name:"Dietary Supplements"'). It doesn't explicitly name alternatives, but the examples and scope make the intended usage clear.

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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