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openai ads get conversion events

openai_ads_get_conversion_events

Read-onlyIdempotent

Lists recent sampled conversion events so you can verify that a pixel or server integration is sending data correctly. Preserves native fields and returns paginated results.

Instructions

List recent sampled conversion events, for checking that a pixel or server integration sends data. Native fields and pagination are preserved. See openai_ads_get_write_schema for nested request fields.

Input Schema

Name	Required	Description	Default
`query`	No	Documented native query parameters. Each call reads one page unless the tool says otherwise.
`adAccountId`	Yes	The adacct_ ID configured in OPENAI_ADS_ACCOUNT_ID. The API key is scoped to this one account; another ID is refused.

Output Schema

Name	Required	Description	Default
`result`	Yes	Original tool result: parsed JSON when the text is JSON, otherwise the text or multiple MCP content blocks. Provider fields depend on the selected query.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedOct 26, 2026

changedInput schema / required

Previous value: -[
-  "adAccountId",
-  "query"
-]New value: +[
+  "adAccountId"
+]

changedOutput schema / properties / result / anyOf

Previous value: -[
-  {
-    "additionalProperties": true,
-    "properties": {},
-    "type": "object"
-  },
-  {
-    "items": {},
-    "type": "array"
-  },
-  {
-    "type": "string"
-  },
-  {
-    "type": "number"
-  },
-  {
-    "type": "boolean"
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "additionalProperties": {},
+    "properties": {},
+    "type": "object"
+  },
+  {
+    "items": {},
+    "type": "array"
+  },
+  {
+    "type": "string"
+  },
+  {
+    "type": "number"
+  },
+  {
+    "type": "boolean"
+  },
+  {
+    "type": "null"
+  }
+]

First observedv1.0.0Oct 23, 2026

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already establish that this is a read-only, idempotent, non-destructive, open-world call. The description adds useful behavior beyond that: results are 'recent' and 'sampled,' and native fields plus pagination are preserved, which matters for interpreting the response.

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 three short sentences, front-loads the core action and purpose, and includes only relevant operational details. The cross-reference to openai_ads_get_write_schema is compact and does not bury the main point.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the output schema exists and the input schema is fully described, the description covers the key remaining gaps: purpose, sampling behavior, and pagination. An agent has enough information to decide when and how to call this tool.

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%, and the nested query object documents pid and limit thoroughly. The description adds little parameter-level meaning beyond pointing to openai_ads_get_write_schema for nested request fields, so the schema remains the primary source.

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 states a specific verb and resource: 'List recent sampled conversion events.' It also names the concrete diagnostic purpose, checking that a pixel or server integration sends data, which distinguishes it from siblings such as conversion insights, conversion settings, and conversion pixels.

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?

It gives a clear use case, checking pixel/server integration delivery, but does not explicitly say when to prefer conversion insights or conversion pixels instead. The context is strong enough for most selection decisions, though no exclusions or alternatives are spelled out.

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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