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Python
Hybrid

meta_ads_pixels_events

List event types your Meta pixel has received, with sample counts, timestamps, and payloads. Use it to audit standard and custom events and inspect parameter names before building conversion rules or audiences.

Instructions

Lists distinct event types the pixel has received recently, with sample payloads. Returns event_name, sample_count, first_seen, last_seen, and a sample_parameters dict per event. Read-only. Use this to audit which standard events (Purchase, Lead, ViewContent, etc.) and custom events are firing, and to inspect parameter names before building conversion rules or audience definitions that reference them. For aggregate volume over time use meta_ads_pixels_stats.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pixel_idYesPixel ID to inspect.
account_idNoMeta Ads account ID in the format 'act_XXXXXXXXXX' (e.g. 'act_1234567890'). Optional — falls back to META_ADS_ACCOUNT_ID from the configured credentials. The leading 'act_' prefix is required.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.10.37
    • addedInput schema / additionalProperties
      Added value: +false
  2. Addedv0.9.12
  3. Removedv0.9.6
  4. Addedv0.9.2
  5. Removedv0.9.1
  6. Addedv1.0.5

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and explicitly declares 'Read-only.' It also describes return fields and the 'sample payloads' nature. However, 'recently' is vague and it does not mention potential constraints like time window limits, pagination, or auth requirements, leaving some behavioral traits undisclosed.

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 four sentences, each earning its place: purpose, return fields, read-only declaration, usage scenario, and alternative. It is front-loaded with the main action and not padded with redundancy.

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?

Given no output schema, the description compensates by detailing the return fields and the purpose. It also provides guidance on when to use and what to do with the data. However, it leaves 'recently' undefined and does not mention any runtime limitations, which is a minor gap but not critical for a read-only list 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%: both pixel_id and account_id are already described in the schema. The description does not add further meaning to the parameters, so the baseline of 3 applies, as the schema does 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 clearly states the verb 'Lists' and the resource 'distinct event types the pixel has received recently, with sample payloads.' It precisely lists the returned fields and distinguishes itself from meta_ads_pixels_stats by mentioning aggregate volume over time, making it unique among siblings.

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

Usage Guidelines5/5

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

Explicit use case is provided: 'Use this to audit which standard events ... and custom events are firing, and to inspect parameter names before building conversion rules or audience definitions.' It also gives an alternative for different needs: 'For aggregate volume over time use meta_ads_pixels_stats.' This fully guides the agent on when to use this tool vs. alternatives.

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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