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drvvek
by drvvek

faers_count_by_field

Read-onlyIdempotent

Aggregate FAERS adverse event reports for a drug by any field, returning the top values—like a SQL GROUP BY count for pharmacovigilance analysis.

Instructions

Aggregate FAERS reports for a drug by any field (SQL GROUP BY equivalent).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoNumber of values to return.
eventsNoMedDRA preferred terms, e.g. ['PANCREATITIS']. Case-insensitive.
date_toNoEnd of a receivedate window, YYYYMMDD. Must be paired with date_from.
date_fromNoStart of a receivedate window, YYYYMMDD. Must be paired with date_to.
drug_nameYesActive substance name, e.g. 'EMPAGLIFLOZIN'.
raw_filterNoExtra Lucene clause ANDed onto the preset query, e.g. 'patient.patientsex:2'. Applied to every marginal of a contingency table. See faers_describe_fields.
count_fieldYesFAERS field to aggregate, e.g. 'patient.reaction.reactionmeddrapt.exact'. See faers_describe_fields for the catalogue.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, covering the safety profile. The description adds the useful aggregation semantics via the SQL GROUP BY analogy, but says nothing about result limits or query behavior beyond what annotations and schema imply.

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?

One tightly written sentence that front-loads the action, resource, and scope. It contains no filler or redundant restatement.

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?

The output schema, rich annotations, and full schema coverage mean the description need not explain return values or parameter details. However, for a seven-parameter aggregation tool in a crowded sibling set, the description is thin on sibling differentiation and usage context.

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 all seven parameters are documented in the schema itself. The description adds only the generic 'by any field' concept, not parameter-specific syntax or constraints beyond what the schema already provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: aggregate FAERS reports for a drug by any field, with a helpful SQL GROUP BY equivalent. It is clear but does not explicitly distinguish itself from specialized siblings such as faers_top_events or faers_outcome_breakdown.

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

Usage Guidelines2/5

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

Provides no when-to-use guidance, prerequisites, or alternatives to sibling tools. The SQL GROUP BY analogy hints at generic aggregation, but the agent receives no routing advice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.