Borrowing it
Nothing to install: this file belongs to AI-Nate/Cut-AI. 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-Nate/Cut-AI/main/CLAUDE.mdgit clone --depth 1 https://github.com/AI-Nate/Cut-AIWrote 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-nate/cut-ai/claude-md)<a href="https://agentmods.dev/instructions/ai-nate/cut-ai/claude-md"><img src="https://agentmods.dev/badge/instructions/ai-nate/cut-ai/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 | $0.01447 | $0.01447 |
| Opus 5 | $0.00724 | $0.00724 |
| Sonnet 5 | $0.00289 | $0.00289 |
| Haiku 4.5 | $0.00145 | $0.00145 |
Grade A, and why
Cut-AI 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
Project Overview
Cut-AI is a Python CLI tool that automatically extracts highlight clips from long-form video recordings. It uses Gemini 3.0 Pro to analyze VTT transcripts, identify the best 2-3 minute segments, and then clips them from the source video using FFmpeg. It optionally burns in subtitles (monolingual or bilingual English + translated).
Directory Structure
Cut-AI/
script/ # All Python source code
docs/ # Reference guides (viral content guide, platform tips)
data/<session>/ # Source videos and VTT transcripts per recording session
output/<session>/ # Generated output per session (highlights, clips, transcripts, drafts)
.claude/skills/ # Claude Code skills (e.g., /viral-clips)
Commands
# Activate virtualenv (Python 3.14)
source venv/bin/activate
# Step 1: Analyze a VTT transcript to generate highlights.json
python script/cut_ai.py analyze --transcript data/<session>/transcript.vtt --output output/<session>/highlights_<session>.json
# Step 2: Clip highlights from video (plain, no subtitles)
python script/cut_ai.py clip --video data/<session>/video.mp4 --highlights output/<session>/highlights_<session>.json
# Step 3: Clip with burned-in subtitles
python script/cut_ai.py clip --video data/<session>/video.mp4 --highlights output/<session>/highlights_<session>.json --subtitles data/<session>/transcript.vtt
# Step 4: Clip with bilingual subtitles (English + Chinese)
python script/cut_ai.py clip --video data/<session>/video.mp4 --highlights output/<session>/highlights_<session>.json --subtitles data/<session>/transcript.vtt --translate Chinese
# Step 5: Generate dual-language clips (English/ + Chinese/ subdirectories)
python script/cut_ai.py clip_dual --video data/<session>/video.mp4 --highlights output/<session>/highlights_<session>.json --subtitles data/<session>/transcript.vtt --output output/<session>
# Step 6: Extract per-clip transcripts
python script/extract_transcripts.py output/<session>/highlights_<session>.json data/<session>/transcript.vtt --output output/<session>/transcripts
# Full automated pipeline via skill
/viral-clips data/<session>
# Test individual modules directly
python script/vtt_parser.py data/<session>/transcript.vtt
python script/gemini_analyzer.py data/<session>/transcript.vtt
python script/video_clipper.py input.mp4 output.mp4 00:05:00 00:07:30
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 · 107 lines · 1,447 tokens per session scan A a8c2a0e429c4
Cut-AI CLAUDE.md is an instructions file published in the GitHub repository AI-Nate/Cut-AI (22 stars, last pushed 7mo ago), licensed MIT. It adds 1,447 tokens to every session, about $0.0072 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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