Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
Check GPU status, running experiments, and available resources
Install GPU Monitor
$ npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Xiangyue-Zhang/auto-deep-researcher-24x7 gpu-monitor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/gpu-monitor .claude/skills/gpu-monitor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "gpu-monitor" agent skill from https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/gpu-monitor into .claude/skills/gpu-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gpu-monitor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/gpu-monitorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Xiangyue-Zhang/auto-deep-researcher-24x7 gpu-monitor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/gpu-monitor .agents/skills/gpu-monitor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "gpu-monitor" agent skill from https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/gpu-monitor into .agents/skills/gpu-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gpu-monitor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Xiangyue-Zhang/auto-deep-researcher-24x7 gpu-monitor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/gpu-monitor .cursor/skills/gpu-monitor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "gpu-monitor" agent skill from https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/gpu-monitor into .cursor/skills/gpu-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gpu-monitor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7.git --path skills/gpu-monitor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Xiangyue-Zhang/auto-deep-researcher-24x7 gpu-monitor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/gpu-monitor .gemini/skills/gpu-monitor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "gpu-monitor" agent skill from https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/gpu-monitor into .gemini/skills/gpu-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gpu-monitor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Xiangyue-Zhang/auto-deep-researcher-24x7 gpu-monitorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/gpu-monitor .github/skills/gpu-monitor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "gpu-monitor" agent skill from https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/gpu-monitor into .github/skills/gpu-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gpu-monitor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Xiangyue-Zhang/auto-deep-researcher-24x7 gpu-monitor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/gpu-monitor .opencode/skills/gpu-monitor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "gpu-monitor" agent skill from https://github.com/Xiangyue-Zhang/auto-deep-researcher-24x7/tree/main/skills/gpu-monitor into .opencode/skills/gpu-monitor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "gpu-monitor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
gpu-monitor- GitHub stars
- 1.3k
- Token cost
- ~280 tokens
- SKILL.md length
- 68 words
- Files
- 2
- Skills in repo
- 8
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Check GPU status, running experiments, and available resources
- Works in 5 steps: Run nvidia-smi to get current GPU status → Display a clean summary table → Identify which GPUs are free (< 1GB… → …
- AI & LLM Engineering work in your project
- SKILL.md covers Usage, Behavior and Output Format
- Calls claude
What it does
GPU Monitor is an agent skill from Xiangyue-Zhang/auto-deep-researcher-24x7. Check GPU status, running experiments, and available resources
Its SKILL.md is about 280 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).
It sits in AI & LLM Engineering. The repository describes itself as: 🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory. The licence is Apache-2.0.
When your agent uses it
- AI & LLM Engineering work in your project
Example prompts
- “/gpu-monitor”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Run nvidia-smi to get current GPU status
- Display a clean summary table
- Identify which GPUs are free (< 1GB memory used)
- Identify which GPUs are running experiments (check for python/torchrun processes)
- If --server is provided, SSH to remote server first
What it can do on your machine
Read from SKILL.md and the folder at commit dbf3df8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
claude
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
GPU Monitor loads about 280 tokens when it runs. Until then it costs about 19 tokens; SKILL.md has 68 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from Xiangyue-Zhang/auto-deep-researcher-24x7 at commit dbf3df8, republished under its Apache-2.0 licence (© Xiangyue-Zhang). 68 words, ~280 tokens.
Download SKILL.mdSave it as
.claude/skills/gpu-monitor/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- gpu-monitor
- description
- Check GPU status, running experiments, and available resources
gpu-monitor
Quick GPU status check for experiment management.
Usage
Claude Code: /gpu-monitor
Claude Code: /gpu-monitor --server user@remote-host
Codex: $gpu-monitorBehavior
- Run
nvidia-smito get current GPU status - Display a clean summary table:
- GPU ID, Name, Memory (used/total), Utilization %, Temperature
- Running processes on each GPU
- Identify which GPUs are free (< 1GB memory used)
- Identify which GPUs are running experiments (check for python/torchrun processes)
- If
--serveris provided, SSH to remote server first
Output Format
GPU Status
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
GPU Name Memory Util Temp
0 L20X 144GB 45123/147456 98% 72°C ← training (PID 12345)
1 L20X 144GB 234/147456 0% 35°C ← FREE
2 L20X 144GB 43210/147456 95% 70°C ← training (PID 12346)
3 L20X 144GB 1024/147456 12% 40°C ← keeper
Free GPUs: [1]
Training: GPU 0 (PID 12345), GPU 2 (PID 12346)© Xiangyue-Zhang, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/gpu-monitor of Xiangyue-Zhang/auto-deep-researcher-24x7.
- SKILL.md
- agents/openai.yaml
Open the folder on GitHubat commit dbf3df8
Compare with similar skills
GPU Monitor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| GPU Monitor this skillXiangyue-Zhang/auto-deep-researcher-24x7 | 1.3k | — | ~280 | Automated safety check: Pass | Apache-2.0 | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 4 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Add Uint Supportpytorch/pytorch | 104k | 2 repos | ~2.3k | Automated safety check: Pass | Custom licence | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3.3k | Automated safety check: Pass | MIT | |
| 1passwordtrpc-group/trpc-agent-go | 1.9k | 14 repos | ~656 | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about GPU Monitor
What does GPU Monitor do?
Check GPU status, running experiments, and available resources. GPU Monitor is an agent skill from Xiangyue-Zhang/auto-deep-researcher-24x7.
When should I use GPU Monitor?
GPU Monitor fits situations like: AI & LLM Engineering work in your project.
How do I install GPU Monitor in Claude Code?
Run `npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a claude-code`. Or copy the skill folder (skills/gpu-monitor in Xiangyue-Zhang/auto-deep-researcher-24x7) into .claude/skills/gpu-monitor in your project. Claude Code loads it when a task matches its description.
How do I install GPU Monitor in Codex?
Run `npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a codex`. Or copy the skill folder (skills/gpu-monitor in Xiangyue-Zhang/auto-deep-researcher-24x7) into .agents/skills/gpu-monitor in your project. Codex loads it when a task matches its description.
Can I use GPU Monitor in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Xiangyue-Zhang/auto-deep-researcher-24x7 --skill gpu-monitor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/gpu-monitor, .gemini/skills/gpu-monitor, .github/skills/gpu-monitor and .opencode/skills/gpu-monitor in your project.
What does GPU Monitor need to run?
Going by SKILL.md and its folder, GPU Monitor needs the command-line tools its instructions call (claude).
Does GPU Monitor access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is GPU Monitor safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does GPU Monitor use?
GPU Monitor is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does GPU Monitor use?
About 280 tokens (SKILL.md is roughly 1.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to GPU Monitor?
Skills that share tags, products or a category with GPU Monitor: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains GPU Monitor?
Xiangyue-Zhang (a GitHub user) maintains it in Xiangyue-Zhang/auto-deep-researcher-24x7, which has 1,296 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on June 3, 2026.
Source: Xiangyue-Zhang/auto-deep-researcher-24x7 on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.