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fda_drug_adverse_events

Read-onlyIdempotent

FDA Adverse Event Reporting System (FAERS) reports for a specific drug. Each result describes a reported adverse reaction including patient demographics, reactions, outcome, and seriousness. Used for pharmacovigilance and post-market safety analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drugYesDrug name (brand or generic) to query FAERS for. Example: 'Lipitor' or 'atorvastatin'.
limitNoMaximum rows to return (default 25, max 100).
end_dateNoInclusive ISO date upper bound (YYYY-MM-DD).
reactionNoOptional MedDRA-preferred-term reaction filter (e.g. 'headache', 'nausea', 'liver injury').
start_dateNoInclusive ISO date lower bound (YYYY-MM-DD).
serious_onlyNoIf true, only return serious adverse events (death, hospitalization, life-threatening, disability).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • addedInput schema / properties / limit / maximum
      Added value: +100
    • addedInput schema / properties / limit / minimum
      Added value: +1
    • changedInput schema / properties / limit / type
      Previous value: -"number"New value: +"integer"
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false, and openWorldHint=true, covering the safety profile fully. The description adds value by detailing what each result contains (patient demographics, reactions, outcome, seriousness), which goes beyond the annotations and helps the agent understand output content. However, with annotations covering behavior so thoroughly, the bar is lower, and the description doesn't add much beyond that basic content listing.

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?

Three sentences, each earning its place: the first states the data source and scope, the second describes return content, and the third states the intended use case. No waste, and the purpose is front-loaded.

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 query tool with full schema coverage and no output schema, the description covers what the tool does, what it returns, and its general domain. It lacks guidance on when to choose this over sibling tools, which would make it complete, but it is otherwise sufficient.

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 fully documents all six parameters. The description adds no parameter-specific guidance. Baseline 3 is appropriate when the schema does all the heavy lifting.

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 names a specific source (FAERS), a specific resource (adverse event reports), and a specific scope (for a specific drug). It is distinguishable from siblings like fda_drug_lookup and fda_drug_recalls, which serve different purposes.

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 implies usage via 'used for pharmacovigilance and post-market safety analysis,' giving implied context. However, it does not explicitly state when to use this tool versus alternatives like fda_drug_lookup or fda_drug_recalls, nor does it set exclusions.

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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