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OpenClaw

nim

Invoke various LLMs (GLM-5, Kimi-k2.5, Llama 3.1, etc.) via NVIDIA NIM API to save main agent tokens and leverage specialized model capabilities.

d-wwei0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install d-wwei/openclaw-nim-skill

Inspect the source and compatibility requirements, then follow its installation steps.

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View source ↗Guides

Skill instructions

NVIDIA NIM Skill for OpenClaw

This skill allows OpenClaw to delegate tasks to external models hosted on the NVIDIA NIM platform.

Setup

  1. Get API Key: Register at build.nvidia.com and get your nvapi-... key.
  2. Set Environment Variable:
    export NVIDIA_API_KEY="your_api_key_here"
    

Usage

Direct Command
python3 scripts/nim_call.py <model_alias> "<prompt>"
Supported Aliases
  • glm5: Zhipu AI GLM-5
  • kimi: Moonshot Kimi-k2.5
  • r1: DeepSeek R1 (Llama-8B Distill)
  • llama: Llama 3.1 405B
  • phi: Microsoft Phi-4

Integration with CLAUDE.md

Add this to your project's CLAUDE.md:

- /nim <model> <prompt>: Call NVIDIA NIM models.

Source information

Source
github
Repository
openclaw/skills
Path
skills/d-wwei/openclaw-nim-skill
Version
—
Commit
050b6a49fe4522f3c3241cff7708f05c10f01df0
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

README

OpenClaw NVIDIA NIM Skill

🚀 Token-Saving Superpower for OpenClaw/Claude Code

This skill integrates the NVIDIA NIM (Inference Microservices) platform into your OpenClaw environment. It allows you to "outsource" heavy tasks like summarization, long-form explanation, or deep reasoning to specialized models (GLM-5, Kimi-k2.5, DeepSeek R1, etc.) for FREE, saving up to 90%+ of your main agent's context tokens.

🌟 Features

  • Multi-Model Support: Switch between top Chinese and Global models instantly.
  • Zero Dependencies: Pure Python implementation using urllib.
  • Token Efficiency: Keeps your main conversation lean by handling long inputs/outputs externally.

📦 Installation

  1. Clone this repo into your skills/ directory.
  2. Get your free API Key from NVIDIA Build.
  3. Add export NVIDIA_API_KEY="your-key" to your .zshrc or .bashrc.

🛠 Usage

In your OpenClaw session:

"Use /nim with kimi to summarize this long file: [path]"

Or via CLI:

python3 scripts/nim_call.py kimi "Summarize the history of AI"

📜 License

MIT

Extracted content

SKILL.md
# NVIDIA NIM Skill for OpenClaw

This skill allows OpenClaw to delegate tasks to external models hosted on the NVIDIA NIM platform.

## Setup

1. **Get API Key**: Register at [build.nvidia.com](https://build.nvidia.com) and get your `nvapi-...` key.
2. **Set Environment Variable**:
   ```bash
   export NVIDIA_API_KEY="your_api_key_here"
   ```

## Usage

### Direct Command
```bash
python3 scripts/nim_call.py <model_alias> "<prompt>"
```

### Supported Aliases
- `glm5`: Zhipu AI GLM-5
- `kimi`: Moonshot Kimi-k2.5
- `r1`: DeepSeek R1 (Llama-8B Distill)
- `llama`: Llama 3.1 405B
- `phi`: Microsoft Phi-4

## Integration with CLAUDE.md
Add this to your project's `CLAUDE.md`:
```markdown
- /nim <model> <prompt>: Call NVIDIA NIM models.
```
README
# OpenClaw NVIDIA NIM Skill

🚀 **Token-Saving Superpower for OpenClaw/Claude Code**

This skill integrates the **NVIDIA NIM (Inference Microservices)** platform into your OpenClaw environment. It allows you to "outsource" heavy tasks like summarization, long-form explanation, or deep reasoning to specialized models (GLM-5, Kimi-k2.5, DeepSeek R1, etc.) for FREE, saving up to 90%+ of your main agent's context tokens.

## 🌟 Features

- **Multi-Model Support**: Switch between top Chinese and Global models instantly.
- **Zero Dependencies**: Pure Python implementation using `urllib`.
- **Token Efficiency**: Keeps your main conversation lean by handling long inputs/outputs externally.

## 📦 Installation

1. Clone this repo into your `skills/` directory.
2. Get your free API Key from [NVIDIA Build](https://build.nvidia.com/).
3. Add `export NVIDIA_API_KEY="your-key"` to your `.zshrc` or `.bashrc`.

## 🛠 Usage

In your OpenClaw session:
> "Use /nim with kimi to summarize this long file: [path]"

Or via CLI:
```bash
python3 scripts/nim_call.py kimi "Summarize the history of AI"
```

## 📜 License
MIT

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