Cut-AI: Instructions file for Claude Code

CLAUDE.md

Cut-AI CLAUDE.md is an instructions file for Claude Code from AI-Nate/Cut-AI. It costs 1,447 tokens per session, scanned A, original, MIT.

Repository instructions for Cut-AI, a Python command-line tool that finds interesting parts of long videos and turns them into short clips.

In plain words
What is it for?
Use them to analyze subtitle transcripts, create highlight clips with FFmpeg, and optionally add English or bilingual subtitles.
Why use it?
They remove guesswork about the project structure, required environment, commands, and video-processing workflow.

Instructions file for Claude Code

Written for Claude Code: the file is CLAUDE.md. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions Claude Code.

This is AI-Nate/Cut-AI's own configuration. It tells Claude Code how to work on Cut-AI itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything Cut-AI configures →

Reuse

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.

Copy the file
curl -O https://raw.githubusercontent.com/AI-Nate/Cut-AI/main/CLAUDE.md
Clone the repo
git clone --depth 1 https://github.com/AI-Nate/Cut-AI

Made for: Claude Code.

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 Cut-AI CLAUDE.md

README.md
[![agentmods](https://agentmods.dev/badge/instructions/ai-nate/cut-ai/claude-md.svg)](https://agentmods.dev/instructions/ai-nate/cut-ai/claude-md)
Your own site
<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>
Per session 1,447 This file is loaded in full into every session.
When invoked 1,447 The same file — it is already loaded in full.
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 $0.01447 $0.01447
Opus 5 $0.00724 $0.00724
Sonnet 5 $0.00289 $0.00289
Haiku 4.5 $0.00145 $0.00145

Measured 8d ago against content hash a8c2a0e429c4, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

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.

CLAUDE.md · 107 lines

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

Read the full file on GitHub · 107 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. 8d ago First seen · 107 lines · 1,447 tokens per session scan A a8c2a0e429c4

Subscribe to this mod's changes

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.

Related

Other instructions, from other repositories

next.js AGENTS.md

AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.

vercel/next.js · 7,296 tokens

codex AGENTS.md

AGENTS.md instructions for openai/codex, covering rust/codex-rs, the codex-core crate, code review rules, crate api surface and model visible context.

openai/codex · 5,153 tokens

vscode buildNext.instructions.md

Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).

microsoft/vscode · 6,785 tokens

vscode oss-third-party-notices.instructions.md

Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, applying the notice (cutover) and fallback chain (never fail the build).

microsoft/vscode · 5,001 tokens

langchain AGENTS.md

AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.

langchain-ai/langchain · 4,469 tokens

spec-kit AGENTS.md

AGENTS.md instructions for github/spec-kit, covering agents.md, about spec kit and specify, quickstart — add a new integration in 5 steps, integration architecture and integrationmanifest — file tracking.

github/spec-kit · 7,104 tokens