Openfda

Fda Event Counts

fda_event_counts

Read-onlyIdempotent

Aggregate adverse events by reaction type, patient age, or outcome. Returns top reactions for a drug and event trends over time.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "patient.drug.openfda.brand_name:\"ASPIRIN\"",
      "count_field": "patient.reaction.reactionmeddrapt.exact"
    },
    "name": "fda_event_counts"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	OpenFDA search query to filter events before counting. Same syntax as fda_drug_events.
`count_field`	Yes	Field to count/aggregate by. Examples: "patient.reaction.reactionmeddrapt.exact" (top reactions), "receivedate" (timeline), "serious" (severity breakdown), "patient.drug.openfda.brand_name.exact" (co-reported drugs)

Output Schema

Name	Required	Description
`query`	Yes	The search query used to filter events
`results`	Yes	Array of count results by term
`count_field`	Yes	The field aggregated/counted by
`requested_query`	No	The search query as supplied, when it differs from the resolved query in `query`
`reaction_resolved`	No	The MedDRA preferred term actually used for the filter
`reaction_requested`	No	The reaction term as the caller supplied it, uppercased
`reaction_resolution`	No	How the supplied reaction term mapped onto a MedDRA preferred term. not_a_meddra_preferred_term means the filter matched nothing — counts are zero because the term missed, not because no reports exist
`reaction_resolution_hint`	No	Present when the term matched nothing; names a working way to discover the real preferred terms
`reaction_resolution_note`	No	Present when word order was corrected; states the substitution made

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedAug 27, 2026

changedInput schema / examples

Previous value: -[
-  {
-    "count_field": "patient.reaction.reactionmeddrapt.exact",
-    "query": "patient.drug.openfda.brand_name:\"ASPIRIN\""
-  },
-  {
-    "count_field": "receivedate",
-    "query": "serious:1+AND+receivedate:[20230101+TO+20231231]"
-  }
-]New value: +[
+  {
+    "count_field": "patient.reaction.reactionmeddrapt.exact",
+    "query": "patient.drug.openfda.brand_name:\"ASPIRIN\""
+  },
+  {
+    "count_field": "receivedate",
+    "query": "serious:1+AND+receivedate:[20230101+TO+20231231]"
+  },
+  {
+    "count_field": "patient.patientonsetage",
+    "query": "patient.drug.openfda.generic_name:\"MONTELUKAST\""
+  }
+]

Changed6 schema fields changedAug 10, 2026

addedOutput schema / properties / reaction_requested

Added value: +{
+  "description": "The reaction term as the caller supplied it, uppercased",
+  "type": "string"
+}

addedOutput schema / properties / reaction_resolution

Added value: +{
+  "description": "How the supplied reaction term mapped onto a MedDRA preferred term. not_a_meddra_preferred_term means the filter matched nothing — counts are zero because the term missed, not because no reports exist",
+  "enum": [
+    "exact_match",
+    "word_order_corrected",
+    "not_a_meddra_preferred_term"
+  ],
+  "type": "string"
+}

addedOutput schema / properties / reaction_resolution_hint

Added value: +{
+  "description": "Present when the term matched nothing; names a working way to discover the real preferred terms",
+  "type": "string"
+}

addedOutput schema / properties / reaction_resolution_note

Added value: +{
+  "description": "Present when word order was corrected; states the substitution made",
+  "type": "string"
+}

addedOutput schema / properties / reaction_resolved

Added value: +{
+  "description": "The MedDRA preferred term actually used for the filter",
+  "type": "string"
+}

addedOutput schema / properties / requested_query

Added value: +{
+  "description": "The search query as supplied, when it differs from the resolved query in `query`",
+  "type": "string"
+}

Changed1 schema field changedMay 8, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "count_field": {
+      "description": "The field aggregated/counted by",
+      "type": "string"
+    },
+    "query": {
+      "description": "The search query used to filter events",
+      "type": "string"
+    },
+    "results": {
+      "description": "Array of count results by term",
+      "items": {
+        "properties": {
+          "count": {
+            "description": "Number of occurrences",
+            "type": "number"
+          },
+          "term": {
+            "description": "The term/value counted",
+            "type": "string"
+          }
+        },
+        "required": [
+          "term",
+          "count"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    }
+  },
+  "required": [
+    "query",
+    "count_field",
+    "results"
+  ],
+  "type": "object"
+}

Changed1 schema field changedMay 6, 2026

addedInput schema / examples

Added value: +[
+  {
+    "count_field": "patient.reaction.reactionmeddrapt.exact",
+    "query": "patient.drug.openfda.brand_name:\"ASPIRIN\""
+  },
+  {
+    "count_field": "receivedate",
+    "query": "serious:1+AND+receivedate:[20230101+TO+20231231]"
+  }
+]

First observedApr 22, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the safety profile is covered. The description adds that the tool produces aggregated counts rather than raw events, which is useful context. It does not disclose any additional behavioral traits such as pagination, limits, or exact grouping semantics, but the output schema partially covers that.

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 two tight sentences with no filler. The central aggregation behavior is front-loaded, and the return summary is stated efficiently. Every sentence contributes useful information.

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?

With two required parameters, 100% schema coverage, rich examples, an output schema, and annotations covering the safety profile, the description is largely sufficient. The main missing element is explicit guidance for distinguishing this tool from overlapping FAERS siblings, but that is more of a usage-guideline gap than a completeness gap for invocation.

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 documents both query and count_field with examples. The description names aggregation dimensions like 'reaction type, patient age, or outcome,' which loosely maps to count_field examples, but it does not add meaningful syntax or format details beyond the schema. This matches the baseline of 3.

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?

The description uses a specific verb and resource: 'Aggregate adverse events by reaction type, patient age, or outcome.' It clearly says what the tool does and what it returns. However, it does not explicitly differentiate itself from closely related siblings like fda_faers_trend or fda_faers_reaction_profile, which also cover reactions and trends.

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 phrase 'Aggregate adverse events' implies this tool should be used when counts or grouped summaries are needed rather than raw event lists. There is no explicit guidance about when to choose this tool over overlapping siblings such as fda_faers_trend or fda_faers_reaction_profile. The usage context is present but only by implication.

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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