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autodl-autogpu
Use when work in any project needs an AutoDL instance powered on or off in GPU mode (有卡) or non-GPU mode (无卡), switched between them, checked (status, balance, billing, free GPUs), or kept from burning GPU time while idle or after the session ends (空转, 忘关机, 自动关机); also, where the project's GPU is an AutoDL instance, before experiments, training or data transfer run on it, e.g. in an automated research or experiment pipeline, under another experiment skill, or on a request like 按计划自动跑实验 (自动科研).
Choose how to use this skill
You do not need every option. Choose the path your AI client supports. The stable page stays the same; versioned files are immutable.
1. Native installer
This listing has no registered native installer command. Use the complete package or source fallback below, depending on what your client supports.
Do not guess an installer command or replace an existing version without reviewing the diff.
2. Complete package recommended
Download the ZIP when available. It includes SKILL.md plus the references, security notes and version metadata.
No complete ProSkills package is published for this listing yet.3. Prompt-only
Copy the prompt above when the agent can read the stable page or when you want to adopt the workflow without installing a skill.
Need only the instruction file?
Download SKILL.md only if your client requires a single file. The complete ZIP is safer for a full installation because it preserves the references and release context.
No path installs or executes anything by itself. Your agent still needs access to the project files. Before updating, compare the installed version and review the diff.
// RATINGS
// README
Background and motivation
A pay-as-you-go AutoDL instance is billed for as long as it is powered on, whether or not the GPU is in use. The following situations are common as a result.
- A training run finishes during the night, and the instance remains powered on until it is shut down the next day
- An AI runs the experiments autonomously, its conversation is interrupted, and nobody shuts the instance down
- Data transfer needs only the non-GPU mode (0.1 yuan per hour), but switching modes is tedious, so the instance is kept in GPU mode and always depends on manual operation
autodl-autogpu serves automated research and automated experiments, and it reduces cost. Once it is installed, power-on, shutdown and the switch between GPU and non-GPU mode are all carried out by the AI, nobody has to attend to the console, and the AI and the skill's scripts carry the workflow forward. For a project that already uses an automated research workflow (ARIS, for example), adding this skill automates the step of running experiments on AutoDL, which reduces both cost and manual work. Two situations are thereby avoided: an instance that idles from the end of a run at night until the next day at needless expense, and a workflow that stalls because someone has to power the instance on in the console before every experiment.
The skill does not rely on the AI's judgement alone. A guard program deployed on the instance shuts it down once it has been idle for the configured time, and it decides and acts by itself even when the AI's conversation has been interrupted. In addition, a budget record helps to keep the spending under control.
Usage
No commands need to be memorised; state the request in natural language.
| Instruction | What is done |
|---|---|
| start the training | checks the balance and the budget, powers on in GPU mode, deploys the guard, starts the job and reports |
| upload the data and shut down once it is copied | powers on and transfers the files (in non-GPU mode when the permission includes it, to reduce cost), then shuts down and books the cost |
| how much of this month's budget is left | answers from the local ledger; no power-on is needed |
| run the experiments of the plan | when another experiment skill reaches a step that needs the instance, it invokes this skill first; power-on, starting the jobs and shutdown are all carried out through it |
It does not ask for confirmation at each step. It reports once after the power-on and once after the shutdown, as in the following example.
Powered on with GPU (RTX 3080 Ti x1, 0.98 yuan/h, billed from 11:36:39). Shuts down after 15 idle minutes; no latest shutdown, no console timer.
Shut down. Billing stopped at 11:45:26: 8 min 47 s this time, 0.14 yuan; 0.60 GPU hours and 0.61 yuan in this project so far.
The AI can act only while the conversation is active. To have it manage the instance until shutdown, let it wait in the background for the job to finish. If the conversation ends midway (the application is closed or the network is interrupted), the job continues, and the guard on the instance shuts it down once it is idle, so the GPU is not left running unused.
How it works
The AI runs on the local computer and reaches the instance by two routes. Power-on is possible only on the web page of the AutoDL console, which the AI operates through a browser; jobs are started and the instance is shut down over SSH. The budget and the usage ledger are kept on the local computer and checked before every power-on. The guard runs on the instance and shuts it down when idle, whether or not the AI's conversation is still active.
Quick start
1. Installation
The current version is for Claude Code. A version for Codex will follow.
git clone https://github.com/grenbel/autodl-autogpu ~/.claude/skills/autodl-autogpu
Alternatively, this command can be sent to the AI, which then installs the skill itself. The AI checks the local environment at first use and, with the user's consent, installs whatever is missing; nothing has to be prepared in advance.
Where the environment runs commands in a sandbox, the skill's commands have to run outside the sandbox, because they need network access (SSH), read the SSH key, and keep a record under the user's home directory that only the user can access. At first use the AI explains this and asks for approval.
2. First-time setup
In the project, tell the AI that the project uses an AutoDL instance, for example
This project's experiments run on AutoDL. Use autodl-autogpu to power the instance on and off.
At first use the AI guides the user through the following setup. Each item is asked by the AI and answered by the user; the AI does not ask for what it can determine by itself.
Establishing the SSH connection. The AI checks the local environment, generates a dedicated key and returns one line, the public key. Paste it under "设置SSH免密登录" above the instance list in the AutoDL console. This is done once per computer and applies to every instance of the account. If a key has already been added to AutoDL, tell the AI which one.
The AI then needs the connection details of the instance. In the instance list of the console, each row has a column "SSH登录" towards the right. Click the copy button next to "登录指令" (login command) and send the copied text to the AI. It has the following form.
ssh -p 12345 [email protected]
The column is shown only while the instance is running and is empty when the instance is shut down. At first use, the login command is therefore provided after the instance has been powered on. The password shown below it is not needed.
Logging in to AutoDL in the browser. The browser used by the AI (for example the built-in browser of the Claude desktop app) must be logged in to AutoDL. The login is performed by the user.
Confirming the settings. The AI asks about the following items in turn.
| Item | Example answer |
|---|---|
| Which instance to use | the instance ID from the first column of the instance list |
| How GPU and non-GPU modes are used | "non-GPU for moving data, GPU for experiments", or "GPU only", "non-GPU only" |
| Budget | "at most 100 yuan this month", "20 GPU hours in total", or "none" |
| Idle time before automatic shutdown | usually 15 minutes; a latest shutdown time or a console timer can be specified as well |
| Whether to clone automatically when no GPU is free | off by default; answer explicitly to turn it o |
// HOW IT'S BUILT
KEY FILES