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AdLoop: Google Ads, Reddit Ads & GA4

by kLOsk
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Python
Remote

Validate tracking

validate_tracking
Read-only

Compare gtag or dataLayer events from your codebase against GA4 data to find fired, missing, or unexpected events and likely causes.

Instructions

Compare tracking events found in the codebase against actual GA4 data.

Takes the event names found in the codebase's gtag('event', ...) or dataLayer.push calls and checks which ones actually fire in GA4.

Returns matched events with their GA4 counts, events missing from GA4, unexpected GA4 events, auto-collected events (page_view, session_start, etc.), insights on likely causes, and the date range.

Google Analytics Data API: https://developers.google.com/analytics/devguides/reporting/data/v1 and Google Ads API: https://developers.google.com/google-ads/api/docs/start

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
property_idNoGA4 property as "properties/123456789" (see get_account_summaries). If empty, uses the default from config.
date_range_endNoEnd date, same formats as date_range_start.today
expected_eventsYesEvent names found in the codebase, e.g. ["sign_up", "purchase"].
date_range_startNoStart date: "today", "yesterday", "NdaysAgo" (e.g. "28daysAgo"), or "YYYY-MM-DD".28daysAgo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changedv0.27.1
    • addedInput schema / properties / date_range_end / description
      Added value: +"End date, same formats as date_range_start."
    • addedInput schema / properties / date_range_start / description
      Added value: +"Start date: \"today\", \"yesterday\", \"NdaysAgo\" (e.g.\n\"28daysAgo\"), or \"YYYY-MM-DD\"."
    • addedInput schema / properties / expected_events / description
      Added value: +"Event names found in the codebase, e.g. [\"sign_up\",\n\"purchase\"]."
    • addedInput schema / properties / property_id / description
      Added value: +"GA4 property as \"properties/123456789\" (see\nget_account_summaries). If empty, uses the default from config."
  2. Addedv0.13.2
  3. Removedv0.13.0
  4. First observedv0.9.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, establishing the safe read profile. The description adds real behavioral context beyond that: it reads gtag('event', ...)/dataLayer.push calls, diffs them against GA4-fired events, and produces "insights on likely causes" — explaining what the comparison actually yields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded, but the long enumeration of return fields duplicates what the existing output schema already covers, and the trailing API links include an irrelevant Google Ads API reference for a GA4-only tool. Structure is fine; several sentences do not earn their place.

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 100% schema coverage and an output schema, the description need not restate parameters or return values, and it is complete enough to call correctly: it covers the input source, the diff behavior, and the date-range output. Missing only explicit sibling routing.

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 fully documents property_id, date_range_start/end, and expected_events. The description adds no format or syntax detail beyond what the schema already provides, so the baseline 3 applies.

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 gives a specific verb and resource ("Compare tracking events found in the codebase against actual GA4 data") and details the mechanism via gtag/dataLayer calls. It is clear, but it never distinguishes itself from the closely-related sibling audit_event_coverage, leaving the agent to infer which one to pick.

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?

Usage is only implied: the agent can infer it runs after extracting event names from a codebase. There is no explicit when-to-use, no exclusions, and no routing to alternatives such as get_tracking_events or audit_event_coverage.

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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