Task Router Skill
Task Router
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.
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-skillInspect the source and compatibility requirements, then follow its installation steps.
Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.
This skill allows OpenClaw to delegate tasks to external models hosted on the NVIDIA NIM platform.
nvapi-... key.export NVIDIA_API_KEY="your_api_key_here"
python3 scripts/nim_call.py <model_alias> "<prompt>"
glm5: Zhipu AI GLM-5kimi: Moonshot Kimi-k2.5r1: DeepSeek R1 (Llama-8B Distill)llama: Llama 3.1 405Bphi: Microsoft Phi-4Add this to your project's CLAUDE.md:
- /nim <model> <prompt>: Call NVIDIA NIM models.
These signals come from indexed source analysis and may lag behind changes. Check the current source files.
🚀 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.
urllib.skills/ directory.export NVIDIA_API_KEY="your-key" to your .zshrc or .bashrc.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"
MIT
# 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. ```
# 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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