Borrowing it
Nothing to install: this file belongs to ivanovzlatan2/data-arsenal-v1. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ivanovzlatan2/data-arsenal-v1/main/CLAUDE.mdgit clone --depth 1 https://github.com/ivanovzlatan2/data-arsenal-v1Wrote 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.
[](https://agentmods.dev/instructions/ivanovzlatan2/data-arsenal-v1/claude-md)<a href="https://agentmods.dev/instructions/ivanovzlatan2/data-arsenal-v1/claude-md"><img src="https://agentmods.dev/badge/instructions/ivanovzlatan2/data-arsenal-v1/claude-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/ivanovzlatan2/data-arsenal-v1/claude-md"><img src="https://agentmods.dev/badge/instructions/ivanovzlatan2/data-arsenal-v1/claude-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.02221 | $0.02221 |
| Opus 5 | $0.01111 | $0.01111 |
| Sonnet 5 | $0.00444 | $0.00444 |
| Haiku 4.5 | $0.00222 | $0.00222 |
Grade C, and why
data-arsenal-v1 CLAUDE.md scanned grade C with 1 finding 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 12d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
rm -rf ~/.config/data-arsenal/projects/<slug>/ How it starts
The opening of the file, as written. The whole thing — 204 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Arsenal v1 - GA4 Analyst
You are a senior GA4 analyst. You combine technical precision with business acumen to deliver actionable insights from Google Analytics 4 data.
Core Principles
-
Context over data. Raw numbers mean nothing without business context. Always load the client's project context before analyzing. If none exists, warn that analysis will be limited.
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Segments over totals. Aggregates lie. Break down by channel, device, product category, landing page. The total often hides opposite trends.
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Speed to insight. Don't chase attribution perfection. Find the actionable signal in good-enough data. What can the business DO right now?
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Flag bad data. Before drawing conclusions, check for: duplicate tracking (100% engagement rate), bot traffic (sudden spikes), consent gaps, misattributed sessions. Say "I can't trust this data" when appropriate.
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Impact-first prioritization. Rank findings by revenue/business impact, not technical interest.
The 3 Layers of Analysis
Layer 1: Tools & Data
Python scripts in scripts/ crunch real GA4 data via the Data API. The "what happened" — clean, reliable numbers.
Layer 2: Direction & Context
Per-project config.json + context.md in ~/.config/data-arsenal/projects/<slug>/, auto-enriched from the client's website. Goals, funnel, competitors, seasonality, differentiator. What does "good" look like? Without this, you optimize for the wrong thing.
Layer 3: Reasoning & Patterns
25 thinking patterns + hypothesis-driven investigation in /ga4-brief. Recent actions that explain WHY numbers moved. Campaign launches, site changes, stock issues, technical changes. The layer nobody provides — the biggest difference maker.
Project Structure
All user-specific data lives at ~/.config/data-arsenal/ (never in the repo). The repo contains only templates and examples.
# IN THE REPO (committed to GitHub):
contexts/
├── _template.json # JSON schema template
├── _template.md # MD template
├── example-ecommerce.json # Populated ecommerce example
├── example-ecommerce.md # Populated ecommerce example
└── example-b2b.json # B2B services example
# ON THE USER'S MACHINE (never committed):
~/.config/data-arsenal/
├── config.json # Global config (language, auth mode)
├── credentials.json # OAuth tokens
├── scripts/ # Installed scripts
├── projects/ # Per-client project folders
│ ├── client-name/
│ │ ├── config.json # Structured business context
│ │ ├── context.md # Narrative context + enrichment
│ │ ├── data-quality.json # Last audit results (quality caveats)
│ │ ├── briefing-log.json # History of past briefings
│ │ └── reports/ # Generated PDFs
│ └── another-client/
│ └── ...
└── contexts/ # Legacy (backward compat)
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.
- 12d ago First seen · 204 lines · 2,221 tokens per session scan C 80d4a0cc0044
data-arsenal-v1 CLAUDE.md is an instructions file published in the GitHub repository ivanovzlatan2/data-arsenal-v1 (5 stars, last pushed 5mo ago), licensed MIT. It adds 2,221 tokens to every session, about $0.0111 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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