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在 OpenClaw 中安装
/install hardware-llm-optimizer
功能描述
Auto-detect PC hardware (CPU/GPU/RAM/VRAM) -> Determine max LLM parameters -> Recommend models (3B/7B/8B/13B/34B/70B) + quantization + deployment tools + bot...
使用说明 (SKILL.md)
Hardware LLM Optimizer
Detects PC hardware configuration and recommends which large language models can run.
Features
- Auto-detect: CPU, RAM, GPU (NVIDIA/AMD), VRAM
- Calculate: Maximum runnable model size
- Quantization: FP16 / 8bit / 4bit / 2bit recommendation
- Model Suggestion: Llama 2/3, Qwen, Mistral, Phi, Gemma, Yi, etc.
- Bottleneck Analysis: System constraint diagnosis
- Deployment Tools: Ollama, Llama.cpp, vLLM, Chatbox
- Optimization Tips: Low VRAM solutions
- Minimum Config Table: 3B/7B/13B/34B/70B requirements
Usage
When user asks about running LLMs on their computer:
检测电脑配置
大模型推荐
能跑什么模型
硬件检测
LLM优化
Quick Run
python3 skills/hardware-llm-optimizer/detect.py
Requirements
- Python 3.8+
- psutil:
pip install psutil - nvidia-smi (optional, for NVIDIA GPU detection)
Minimum Config Reference
| Model | Min VRAM | Rec VRAM | Quantization |
|---|---|---|---|
| 3B | 2GB | 4GB | Q4 |
| 7B | 6GB | 8GB | Q4/Q8 |
| 13B | 10GB | 16GB | Q4/Q8 |
| 34B | 20GB | 32GB | Q4 |
| 70B | 40GB | 80GB | Q4 |
Chinese Interface
This skill outputs in Chinese for user convenience.
安全使用建议
This skill appears to do what it claims: run locally, detect hardware, and print recommendations. Before installing/running: (1) review the detect.py yourself (it's included) and confirm you're comfortable executing it, (2) be aware it will reveal local hardware details (CPU/GPU/RAM) to whatever component runs the skill — if your agent forwards outputs to external services, those details could be transmitted, and (3) install psutil (pip install psutil) and ensure nvidia-smi is available if you want GPU detection. If you want extra caution, run the script in a local sandbox or VM first.
功能分析
Type: OpenClaw Skill
Name: hardware-llm-optimizer
Version: 1.1.0
The hardware-llm-optimizer skill is a legitimate tool designed to detect system hardware (CPU, RAM, GPU) and recommend suitable Large Language Models. The core logic in detect.py uses standard libraries like psutil and subprocess (to call nvidia-smi) to gather hardware specifications, which is consistent with its stated purpose in SKILL.md. No evidence of data exfiltration, unauthorized network access, or malicious prompt injection was found.
能力评估
Purpose & Capability
Name/description (detect hardware, recommend models/quantization/deployment) align with included files: SKILL.md instructs running detect.py and detect.py inspects CPU, RAM, GPU and gives model/quantization recommendations. No unrelated credentials, binaries, or services are requested.
Instruction Scope
SKILL.md directs the agent to run the bundled detect.py. The script only reads local system info (psutil), checks /proc/version for WSL, and calls nvidia-smi for GPU details — all within the stated purpose. It does not access external endpoints, env vars, or other user files beyond /proc/version.
Install Mechanism
No install spec; this is instruction-only with a bundled Python script. The only required third-party package is psutil (documented in SKILL.md). The script does not download or execute code from remote URLs.
Credentials
No environment variables, credentials, or config paths are requested. The script uses local APIs and optional nvidia-smi; this is proportionate to hardware-detection functionality.
Persistence & Privilege
Skill is not always-enabled, does not attempt to modify other skills or agent-wide settings, and does not persist credentials. It merely prints local detection results.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install hardware-llm-optimizer - 安装完成后，直接呼叫该 Skill 的名称或使用
/hardware-llm-optimizer触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.1.0
hardware-llm-optimizer 1.1.0
- Expanded model and quantization recommendation table to include 3B models and minimum config details.
- Added bottleneck analysis and more detailed optimization tips.
- Updated feature list: deployment tools section (Ollama, Llama.cpp, vLLM, Chatbox) and system constraint diagnosis.
- Improved documentation and usage instructions.
- Maintains Chinese output interface.
v1.0.0
Initial release of hardware-llm-optimizer:
- Automatically detects PC hardware: CPU, RAM, GPU (NVIDIA/AMD), and VRAM.
- Analyzes hardware to determine the maximum size of LLM models supported.
- Recommends suitable LLM models (7B/8B/13B/34B/70B), quantization options, and deployment tools.
- Provides additional features: Ollama and llama.cpp compatibility checks, local deployment tips, and low VRAM optimizations.
- Designed with a Chinese interface for user interaction.
元数据
常见问题
Hardware Llm Optimizer 是什么？
Auto-detect PC hardware (CPU/GPU/RAM/VRAM) -> Determine max LLM parameters -> Recommend models (3B/7B/8B/13B/34B/70B) + quantization + deployment tools + bot... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 91 次。
如何安装 Hardware Llm Optimizer？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install hardware-llm-optimizer」即可一键安装，无需额外配置。
Hardware Llm Optimizer 是免费的吗？
是的，Hardware Llm Optimizer 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Hardware Llm Optimizer 支持哪些平台？
Hardware Llm Optimizer 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Hardware Llm Optimizer？
由 SMS（@smseow001）开发并维护，当前版本 v1.1.0。
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