Get it running
Paste this into the AI that runs on your computer. It does the install, checks it works, and tells you what to type first. If anything fails, paste the error back to it.
Paste into Claude Code
Install autoclip (https://github.com/zhouxiaoka/AutoClip) on this computer and get it working for me. I am not a developer; explain each step in one line as you go and never skip one. You are Claude Code, running on my machine. 1. Check what this machine already has (git, Python or Node as the project needs, Docker if the README says so). Tell me anything missing and install it, asking me before anything that needs my password. 2. Clone https://github.com/zhouxiaoka/AutoClip into ~/tools/autoclip and follow the README's install exactly. 3. Configure it. If it needs an API key or a login, stop and ask me for it; never guess one and never store it anywhere except where the README says. Tool-specific notes: Copy env.example to .env and fill in an AI API key (for example API_DASHSCOPE_API_KEY for Qwen) — skip this entirely if you are running local Ollama or LM Studio instead. Run ./docker-start.sh from the project root; it starts the frontend on port 3000, the backend on port 8000, and Flower task monitoring on port 5555. Confirm it is healthy with curl http://localhost:8000/api/v1/health/ and by opening http://localhost:3000 in a browser. The most common failure is a stale Redis connection — check with redis-cli ping — and if a port is already taken, find and stop the process with lsof -i :8000 before retrying. 4. Run the smallest test the README gives, and show me the output. 5. When it works, tell me what to type first, in one line, for this job: Clip a single long talk. If anything fails, show me the exact error and fix it before going on.
Paste into Kimi
Install autoclip (https://github.com/zhouxiaoka/AutoClip) on this computer and get it working for me. I am not a developer; explain each step in one line as you go and never skip one. You are Kimi, running on my machine. 1. Check what this machine already has (git, Python or Node as the project needs, Docker if the README says so). Tell me anything missing and install it, asking me before anything that needs my password. 2. Clone https://github.com/zhouxiaoka/AutoClip into ~/tools/autoclip and follow the README's install exactly. 3. Configure it. If it needs an API key or a login, stop and ask me for it; never guess one and never store it anywhere except where the README says. Tool-specific notes: Copy env.example to .env and fill in an AI API key (for example API_DASHSCOPE_API_KEY for Qwen) — skip this entirely if you are running local Ollama or LM Studio instead. Run ./docker-start.sh from the project root; it starts the frontend on port 3000, the backend on port 8000, and Flower task monitoring on port 5555. Confirm it is healthy with curl http://localhost:8000/api/v1/health/ and by opening http://localhost:3000 in a browser. The most common failure is a stale Redis connection — check with redis-cli ping — and if a port is already taken, find and stop the process with lsof -i :8000 before retrying. 4. Run the smallest test the README gives, and show me the output. 5. When it works, tell me what to type first, in one line, for this job: Clip a single long talk. If anything fails, show me the exact error and fix it before going on.
Paste into Gemini CLI
Install autoclip (https://github.com/zhouxiaoka/AutoClip) on this computer and get it working for me. I am not a developer; explain each step in one line as you go and never skip one. You are Gemini CLI, running on my machine. 1. Check what this machine already has (git, Python or Node as the project needs, Docker if the README says so). Tell me anything missing and install it, asking me before anything that needs my password. 2. Clone https://github.com/zhouxiaoka/AutoClip into ~/tools/autoclip and follow the README's install exactly. 3. Configure it. If it needs an API key or a login, stop and ask me for it; never guess one and never store it anywhere except where the README says. Tool-specific notes: Copy env.example to .env and fill in an AI API key (for example API_DASHSCOPE_API_KEY for Qwen) — skip this entirely if you are running local Ollama or LM Studio instead. Run ./docker-start.sh from the project root; it starts the frontend on port 3000, the backend on port 8000, and Flower task monitoring on port 5555. Confirm it is healthy with curl http://localhost:8000/api/v1/health/ and by opening http://localhost:3000 in a browser. The most common failure is a stale Redis connection — check with redis-cli ping — and if a port is already taken, find and stop the process with lsof -i :8000 before retrying. 4. Run the smallest test the README gives, and show me the output. 5. When it works, tell me what to type first, in one line, for this job: Clip a single long talk. If anything fails, show me the exact error and fix it before going on.
Paste into Codex
Install autoclip (https://github.com/zhouxiaoka/AutoClip) on this computer and get it working for me. I am not a developer; explain each step in one line as you go and never skip one. You are Codex, running on my machine. 1. Check what this machine already has (git, Python or Node as the project needs, Docker if the README says so). Tell me anything missing and install it, asking me before anything that needs my password. 2. Clone https://github.com/zhouxiaoka/AutoClip into ~/tools/autoclip and follow the README's install exactly. 3. Configure it. If it needs an API key or a login, stop and ask me for it; never guess one and never store it anywhere except where the README says. Tool-specific notes: Copy env.example to .env and fill in an AI API key (for example API_DASHSCOPE_API_KEY for Qwen) — skip this entirely if you are running local Ollama or LM Studio instead. Run ./docker-start.sh from the project root; it starts the frontend on port 3000, the backend on port 8000, and Flower task monitoring on port 5555. Confirm it is healthy with curl http://localhost:8000/api/v1/health/ and by opening http://localhost:3000 in a browser. The most common failure is a stale Redis connection — check with redis-cli ping — and if a port is already taken, find and stop the process with lsof -i :8000 before retrying. 4. Run the smallest test the README gives, and show me the output. 5. When it works, tell me what to type first, in one line, for this job: Clip a single long talk. If anything fails, show me the exact error and fix it before going on.
What to point it at first
1
Clip a single long talk
Point it at one YouTube video or podcast recording you already have and let it produce a first batch of clips — this is the smallest test of the full pipeline, download through cutting.
2
Check the exciting-clip scores
Look at the scores the AI gave each cut before you publish anything — a good sign is that the top-scored clips contain a complete thought, not just a loud moment.
3
Build one themed collection
Take the clips from a single video and see what the AI groups into a collection versus what you would group by hand — mismatches show you where its topic detection needs a nudge.
What it must never do unattended
- Never publish a cut you have not watched to the end.
- Check the licence of every model and every clip before it goes out under your name.
- Never let it manage a Bilibili account login on its own — approve every cookie import, password entry, or QR login yourself.
Who made it
zhouxiaoka/autoclip on GitHub, under the MIT licence. 7,253 stars, checked 9 September 2026. Last change 7 September 2026. We did not write it; we checked it, and wrote this page so you can use it.
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