ga4-bigquery-export

ga4-bigquery-export is a skill for Claude Code from Ad-Superpowers/ad-superpowers-plugin. It costs 91 tokens per session (5,267 once invoked), scanned A, original, MIT.

A guide for exporting raw Google Analytics 4 event data to BigQuery, Google's cloud data warehouse, where it can be queried and combined with other data.

In plain words
What is it for?
Use it to plan BigQuery linking, choose daily or streaming exports, and query unsampled event-level GA4 data.
Why use it?
It helps when standard GA4 reports do not provide the detail, history, or data joins needed for analysis.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the ad-superpowers plugin — 17 skills, 35 commands, 5 agents, 1 MCP server shipped together

Good fit Use it to plan BigQuery linking, choose daily or streaming exports, and…

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ad-superpowers/ad-superpowers-plugin/ga4-bigquery-export
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Ad-Superpowers/ad-superpowers-plugin --skill ga4-bigquery-export
Clone the repo
git clone --depth 1 https://github.com/Ad-Superpowers/ad-superpowers-plugin

Made for: Claude Code.

Or install ad-superpowers, the plugin that ships this one along with the rest of its 17 skills, 35 commands, 5 agents, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for ga4-bigquery-export

README.md
[![agentmods](https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/ga4-bigquery-export.svg)](https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/ga4-bigquery-export)
Your own site
<a href="https://agentmods.dev/skills/ad-superpowers/ad-superpowers-plugin/ga4-bigquery-export"><img src="https://agentmods.dev/badge/skills/ad-superpowers/ad-superpowers-plugin/ga4-bigquery-export.svg" alt="Measured on agentmods" height="20"></a>
Per session 91 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,267 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00091 $0.05267
Opus 5 $0.00046 $0.02634
Sonnet 5 $0.00018 $0.01053
Haiku 4.5 $0.00009 $0.00527

Measured 6d ago against content hash d5350052f71a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

ga4-bigquery-export scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugin/skills/ga4-bigquery-export/SKILL.md · 709 lines

How it starts

The opening of the file, as written. The whole thing — 709 lines — stays where its author put it; the contents beside it link to each section on GitHub.

GA4 BigQuery Export Guide

Complete guide for configuring BigQuery export and analyzing GA4 raw event data.

Quick Decision Tree

GA4 BIGQUERY EXPORT FLOW
│
├─► DO YOU NEED BIGQUERY?
│   ├─► YES, if you need:
│   │   ├─► Raw event-level data
│   │   ├─► Custom attribution models
│   │   ├─► Unsampled data
│   │   ├─► Data joins with other sources
│   │   ├─► ML/AI analyses
│   │   └─► Long-term data storage
│   │
│   └─► NO, GA4 UI is sufficient if:
│       ├─► Standard reports suffice
│       ├─► Exploration capabilities are enough
│       └─► No external data joins needed
│
├─► WHICH EXPORT TYPE?
│   ├─► Daily export (free)
│   │   └─► Data available next day
│   │
│   ├─► Streaming export (GA360)
│   │   └─► Real-time data (within minutes)
│   │
│   └─► Fresh daily export (GA360)
│       └─► Multiple times per day
│
└─► COST CONSIDERATIONS?
    ├─► GA4 daily export itself: FREE (no GA360 needed)
    ├─► BigQuery storage: ~$0.02/GB/month (GCP cost, not GA4)
    ├─► Queries: $5/TB scanned (on-demand) or flat rate
    └─► Optimize with partitioning to reduce query costs

Configuring BigQuery Export

BIGQUERY LINKING SETUP
======================

PREREQUISITES:
├── Google Cloud Project with billing enabled
├── BigQuery API enabled
├── GA4 property Editor or Admin access
└── BigQuery Admin permissions in GCP project

STEP 1: PREPARE GCP PROJECT
────────────────────────────
1. Go to console.cloud.google.com
2. Create project or select existing project
3. Enable BigQuery API:
   └── APIs & Services → Enable APIs → BigQuery API

4. Billing setup (required for export)

STEP 2: CREATE GA4 BIGQUERY LINK
─────────────────────────────────
LOCATION: GA4 Admin → Product Links → BigQuery Links

┌────┬────────────────────────────────────────────────────────────────┐
│ 1  │ Click "Link"                                                   │
├────┼────────────────────────────────────────────────────────────────┤
│ 2  │ Select Google Cloud project                                    │
├────┼────────────────────────────────────────────────────────────────┤
│ 3  │ Choose data location (EU/US) - CANNOT be changed later!       │
├────┼────────────────────────────────────────────────────────────────┤
│ 4  │ Select data streams to export                                  │
├────┼────────────────────────────────────────────────────────────────┤
│ 5  │ Choose export frequency:                                       │
│    │ ├── Daily (free, recommended to start)                         │
│    │ └── Streaming (GA360 only)                                     │
├────┼────────────────────────────────────────────────────────────────┤
│ 6  │ Include advertising ID (optional, for app data)                │
├────┼────────────────────────────────────────────────────────────────┤
│ 7  │ Click "Submit"                                                  │
└────┴────────────────────────────────────────────────────────────────┘

IMPORTANT:
├── Data location (EU/US) CANNOT be changed
├── Choose the SAME region as other data for joins
├── Export usually starts within 24 hours
└── Historical data is NOT exported

Read the full file on GitHub · 709 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 709 lines · 91 tokens per session scan A d5350052f71a

Subscribe to this mod's changes

ga4-bigquery-export is a skill published in the GitHub repository Ad-Superpowers/ad-superpowers-plugin (5 stars, last pushed 8d ago), licensed MIT. It adds 91 tokens to every session and 5,267 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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