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cyntrica

Gov Data MCP

by cyntrica

fda_animal_events

Read-only

Search FDA adverse event reports for drug side effects in animals (dogs, cats, horses, cattle). Filter by species, date, or seriousness to find specific outcomes.

Instructions

Search animal/veterinary adverse event reports (1.3M+ reports). Reports of drug side effects in animals — dogs, cats, horses, cattle, etc. Each report has: animal info (species, breed), drugs, reactions (VEDDRA terms), outcomes. Note: Some fields may contain 'MSK' (masked) values for privacy.

Example searches:

  • 'animal.species:"Dog"' — dog events

  • 'original_receive_date:[20200101+TO+20231231]' — events in date range

  • 'serious_ae:true' — serious adverse events only

Count fields: animal.species.exact, primary_reporter.exact, serious_ae

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+'.
Behavior4/5

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

Annotations provide readOnlyHint=true, and the description adds meaningful context: the 1.3M+ report scale, masked 'MSK' values for privacy, and example query patterns that hint at response behavior. This goes beyond what the annotation states, with no contradictions.

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 well-structured and front-loaded: a clear lead sentence, report contents, privacy note, and examples. Every line adds value, though the density of examples and count fields makes it slightly more verbose than strictly necessary.

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 two-parameter search tool with no output schema, the description covers the data domain, query syntax examples, privacy considerations, and report contents. It does not describe the response envelope, but the core information an agent needs to select and invoke the tool is present.

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% (both parameters have descriptions), and the description supplements this with concrete search examples ('animal.species:"Dog"', date range syntax) and a list of count fields, giving actionable guidance for constructing queries beyond the schema's generic field descriptions.

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 opens with a specific verb and resource ('Search animal/veterinary adverse event reports'), and immediately distinguishes this tool from FDA human drug/device event tools by focusing on animal/veterinary data. It further clarifies scope with report contents (species, drugs, reactions, outcomes).

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

Usage Guidelines3/5

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

The description strongly implies usage for animal adverse event searches, but it does not explicitly state when to use this tool versus sibling FDA tools (e.g., fda_drug_events) or mention exclusions/alternatives. The included example searches are useful for query construction but do not guide tool selection.

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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