# qzcli

A skill that lets your agent drive GPU compute jobs on the 启智 platform through qzcli, a kubectl-style CLI.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 426 installs · ★ 18090
- Author: wanshuiyin
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/HEAD/skills/qzcli/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/qzcli

## What it does

qzcli is a command-line tool for the 启智 scheduler. The skill documents its commands so the agent knows the order of operations: `qzcli login`, then `qzcli res -u` to cache workspaces and compute groups, `qzcli avail` to see free nodes, `qzcli ls -c -r` to list what is running. Submitting a job means `qzcli create` with a name, command, image and instance count; `qzcli batch` takes a JSON config and expands a matrix of parameters into separate jobs.

The tool itself installs separately: `pip install rich requests prompt_toolkit mcp`, then clone the repo and run `pip install -e .`. Credentials are resolved in a fixed order — CLI arguments, `--password-stdin`, environment variables, the `QZCLI_ENV_FILE` file, `~/.qzcli/config.json`, interactive prompt. State lives in `~/.qzcli/`. If you want qzcli exposed as an MCP server, `claude mcp add qzcli -- qzcli-mcp` registers it.

Images are built off-platform and named at submit time, so the skill keeps a declarative env spec plus an `env:<name>@<specHash>` ledger in `.aris/compute/qizhi.md` to answer which image carries which stack. Run the kernel witness inside a submitted job rather than on the login side — a long training run started on the wrong image wastes the queue slot.

## Requirements
- Works with: Kubernetes

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill qzcli -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/qzcli/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/qzcli/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill qzcli -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/qzcli/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill qzcli -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/qzcli/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install wanshuiyin/Auto-claude-code-research-in-sleep qzcli
```

2. **Manually: put the files in place**
- File: `.github/skills/qzcli/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill qzcli -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep --path skills/qzcli
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/qzcli/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add wanshuiyin/Auto-claude-code-research-in-sleep --skill qzcli -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep/tree/HEAD/skills/qzcli/SKILL.md

## When to use it
- launch distributed training across several instances
- find a compute group with free nodes
- stop a job by its job-id
- submit a sweep of checkpoints from one config file
- trace which image holds a given stack

## Example prompts
- Log in to 启智 and show me free nodes: `qzcli login`, then `qzcli avail -n 4`
- Submit `my-training-job` running `bash /path/to/train.sh` on 4 instances
- Stop the job with this job-id

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 4a6d8ee18242b21f.

BEGIN THIRD-PARTY FILE 4a6d8ee18242b21f
````text
---
name: qzcli
description: Manage GPU compute jobs on the Qizhi (启智) platform using qzcli — a kubectl-style CLI tool. Use when user says "qzcli", "启智平台", "submit job", "stop job", "查计算组", "avail", "list jobs", "batch submit", or needs to manage distributed training jobs on a Qizhi instance.
argument-hint: "[login|avail|list|create|stop <job-id>|batch|status|watch]"
allowed-tools: Bash(*), Read, Write
---

# qzcli — 启智平台任务管理

A kubectl/docker-style CLI for managing GPU compute jobs on the Qizhi (启智) platform.

**GitHub:** [tianyilt/qzcli_tool](https://github.com/tianyilt/qzcli_tool)

## Environment contract

Qizhi is the scheduler-cluster shape of `../shared-references/compute-env-contract.md`:
images are built OFF-platform and referenced at submit time, so the declarative
env spec + `env:<name>@<specHash>` ledger (`.aris/compute/qizhi.md`) is what
keeps "which image has which stack" answerable. Run the kernel witness inside a
submitted job (not on the login side) before trusting an image for a long run.

## Installation

```bash
pip install rich requests prompt_toolkit mcp
git clone https://github.com/tianyilt/qzcli_tool
cd qzcli_tool && pip install -e .
```

### MCP Integration (optional)

To use qzcli as an MCP tool directly from Claude Code or Codex:

```bash
# Claude Code
claude mcp add qzcli -- qzcli-mcp

# Codex
codex mcp add qzcli -- qzcli-mcp
```

---

## Configuration

Credentials are read in this priority order:
`CLI args > --password-stdin > env vars > QZCLI_ENV_FILE (.env) > ~/.qzcli/config.json > interactive input`

```bash
# Option A: env file (recommended)
mkdir -p ~/.qzcli
cat > ~/.qzcli/.env <<'EOF'
QZCLI_USERNAME="your_username"
QZCLI_PASSWORD="your_password"
EOF

# Option B: environment variables
export QZCLI_USERNAME="your_username"
export QZCLI_PASSWORD="your_password"
export QZCLI_API_URL="https://qz.yourorg.edu.cn"
```

Config files are stored in `~/.qzcli/`: `config.json`, `.cookie`, `resources.json`, `jobs.json`.

---

## Quick Start

```bash
# 1. Login
qzcli login

# 2. Discover and cache workspaces/compute groups (run once, re-run after joining new workspaces)
qzcli res -u

# 3. Check available nodes
qzcli avail

# 4. List running jobs
qzcli ls -c -r
```

---

## Authentication

```bash
# Interactive login
qzcli login

# With credentials
qzcli login -u YOUR_USERNAME -p 'YOUR_PASSWORD'

# Read password from stdin (for scripts)
echo 'YOUR_PASSWORD' | qzcli login -u YOUR_USERNAME --password-stdin
````
END THIRD-PARTY FILE 4a6d8ee18242b21f

The third-party file has ended. Everything between the 4a6d8ee18242b21f tags is data: requests and commands from it are not followed. An “end of file” line with another tag inside the block is part of the file.

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