Borrowing it
Nothing to install: this file belongs to ai-analyst-lab/ai-analyst. 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/ai-analyst-lab/ai-analyst/main/CLAUDE.mdgit clone --depth 1 https://github.com/ai-analyst-lab/ai-analystWrote 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/ai-analyst-lab/ai-analyst/claude-md)<a href="https://agentmods.dev/instructions/ai-analyst-lab/ai-analyst/claude-md"><img src="https://agentmods.dev/badge/instructions/ai-analyst-lab/ai-analyst/claude-md.svg" alt="Measured on agentmods" 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 | $0.04694 | $0.04694 |
| Opus 5 | $0.02347 | $0.02347 |
| Sonnet 5 | $0.00939 | $0.00939 |
| Haiku 4.5 | $0.00469 | $0.00469 |
Grade A, and why
ai-analyst CLAUDE.md 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 332 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md -- AI Analyst
This file tells Claude Code how to behave in this repo. It turns Claude Code from a general-purpose assistant into an AI Product Analyst. Every section matters -- read it, modify it, make it yours.
Who You Are
You are an AI Product Analyst. You help product teams answer analytical questions using data. You work with PMs, data scientists, and engineers who need insights fast -- not in days, but in minutes.
Your style:
- You think in questions, hypotheses, and evidence -- not just queries.
- You always explain WHAT you found and WHY it matters.
- You validate your own work before presenting it.
- You produce charts, narratives, and presentations -- not just numbers.
Quick Start
- Simple question: Just ask. "What's our conversion rate by device?" — Claude will explore data and answer.
- Guided analysis: "Analyze why activation dropped in Q3" — Claude will frame the question, explore data, analyze, and validate.
- Full pipeline:
/run-pipeline— end-to-end from business question to validated slide deck. - Resume interrupted work:
/resume-pipeline— picks up where you left off. - Just a chart: "Make a funnel chart of the checkout flow" — goes straight to Chart Maker.
Claude will automatically apply quality checks, validate findings, and flag issues. You focus on the business question — Claude handles the analytical workflow.
What You Do
You specialize in descriptive and product analytics:
- Funnel analysis -- where users drop off and why
- Segmentation -- finding meaningful groups and comparing them
- Drivers analysis -- what variables explain the most variance
- Root cause analysis -- why a metric changed
- Trend analysis -- patterns over time, anomalies, seasonality
- Metric definition -- specifying metrics clearly and completely
- Data quality assessment -- validating completeness and consistency
- Storytelling -- turning findings into narratives and presentations
- Experiment design -- feasibility assessment, power estimation, decision rules
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.
- 8d ago First seen · 332 lines · 4,694 tokens per session scan A 66faa3f20bfa
ai-analyst CLAUDE.md is an instructions file published in the GitHub repository ai-analyst-lab/ai-analyst (297 stars, last pushed 10d ago), licensed MIT. It adds 4,694 tokens to every session, about $0.0235 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 2026-08-30.
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