Awesome-omni-skill windows
Note: Qwen 3 coder is a 30B parameter model requiring at least 24GB of VRAM to run smoothly. More is required for longer context lengths.
git clone https://github.com/diegosouzapw/awesome-omni-skill
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/ai-agents/windows" ~/.claude/skills/diegosouzapw-awesome-omni-skill-windows && rm -rf "$T"
T=$(mktemp -d) && git clone --depth=1 https://github.com/diegosouzapw/awesome-omni-skill "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/ai-agents/windows" ~/.openclaw/skills/diegosouzapw-awesome-omni-skill-windows && rm -rf "$T"
skills/ai-agents/windows/SKILL.md- uses sudo
- makes HTTP requests (curl)
- references API keys
Windows
Note: Qwen 3 coder is a 30B parameter model requiring at least 24GB of VRAM to run smoothly. More is required for longer context lengths.
Note: Qwen 3 coder is a 30B parameter model requiring at least 24GB of VRAM to run smoothly. More is required for longer context lengths.
Available Resources
Usage
Using with Claude Code
Endpoints
Models
Differences from the Anthropic API
Signing in
API keys
Status codes
Error messages
Errors that occur while streaming
Get started
Base URL
Example request
Libraries
-
Python
-
JavaScript
Versioning
Usage
Endpoints
Models
Disabling streaming
When to use streaming vs non-streaming
Example response
Recommended models
-
embeddinggemma
-
qwen3-embedding
-
all-minilm
Generate embeddings
Generate a batch of embeddings
Tips
Key streaming concepts
Handling streamed chunks
Generating structured JSON
Generating structured JSON with a schema
Example: Extract structured data
Example: Vision with structured outputs
Tips for reliable structured outputs
Supported models
-
Qwen 3
-
GPT-OSS
-
DeepSeek-v3.1
-
DeepSeek R1
-
thinking models
Enable thinking in API calls
Stream the reasoning trace
CLI quick reference
Calling a single tool
Parallel tool calling
Multi-turn tool calling (Agent loop)
Tool calling with streaming
Using functions as tools with Ollama Python SDK
Quick start
Usage with Ollama's API
Authentication
Web search API
Web fetch API
Building a search agent
MCP Server
Cloud Models
Cloud API access
Local only
Setting context length
CPU only
Nvidia GPU
- Link: Configure the repository
curl -fsSL \ | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg curl -fsSL https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list \ | sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' \ | sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list sudo apt-get update
-
Link: Configure the repository
curl -fsSL \ | sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
AMD GPU
Vulkan Support
Run model locally
Try different models
How can I upgrade Ollama?
How can I view the logs?
Is my GPU compatible with Ollama?
How can I specify the context window size?
How can I tell if my model was loaded onto the GPU?
How do I configure Ollama server?
How do I use Ollama behind a proxy?
Does Ollama send my prompts and answers back to ollama.com?
How do I disable Ollama's cloud features?
How can I expose Ollama on my network?
How can I use Ollama with a proxy server?
How can I use Ollama with ngrok?
How can I use Ollama with Cloudflare Tunnel?
How can I allow additional web origins to access Ollama?
Where are models stored?
How can I use Ollama in Visual Studio Code?
How do I use Ollama with GPU acceleration in Docker?
Why is networking slow in WSL2 on Windows 10?
How can I preload a model into Ollama to get faster response times?
How do I keep a model loaded in memory or make it unload immediately?
How do I manage the maximum number of requests the Ollama server can queue?
How does Ollama handle concurrent requests?
How does Ollama load models on multiple GPUs?
How can I enable Flash Attention?
How can I set the quantization type for the K/V cache?
Where can I find my Ollama Public Key?
-
Ollama Cloud
How can I stop Ollama from starting when I login to my computer?
Nvidia
AMD Radeon
Metal (Apple GPUs)
Vulkan GPU Support
Table of Contents
-
Importing a Safetensors adapter
- URL: #Importing-a-fine-tuned-adapter-from-Safetensors-weights
-
Importing a Safetensors model
- URL: #Importing-a-model-from-Safetensors-weights
-
Importing a GGUF file
- URL: #Importing-a-GGUF-based-model-or-adapter
-
Sharing models on ollama.com
- URL: #Sharing-your-model-on-ollamacom
Importing a fine tuned adapter from Safetensors weights
-
fine tuning framework
-
Unsloth
-
MLX
Importing a model from Safetensors weights
Importing a GGUF based model or adapter
Quantizing a Model
Sharing your model on ollama.com
Libraries
Community
Install
Usage with Ollama
Recommended Models
Install
Usage with Ollama
Connecting to ollama.com
-
API key
-
Link: Click on
and set it to `Use custom base URL- URL: https://ollama.com`
Install
Usage with Ollama
Connecting to ollama.com
Install
Usage with Ollama
Cloud Models
Connecting to ollama.com
-
API key
-
Link: Add the cloud configuration block to
:~/.factory/config.json
{ "custom_models": [ { "model_display_name": "qwen3-coder [Ollama Cloud]", "model": "qwen3-coder:480b", "base_url": " "api_key": "OLLAMA_API_KEY", "provider": "generic-chat-completion-api", "max_tokens": 128000 } ] }
- URL: https://ollama.com/v1/",
Goose Desktop
-
Link: Confirm API Host is ` and click Submit
-
API key
-
Link: In Goose, set API Host to `
- URL: https://ollama.com`
Goose CLI
-
API key
-
Link: Update OLLAMA_HOST to `
- URL: https://ollama.com`
Coding Agents
-
Claude Code
- URL: /integrations/claude-code
-
Codex
- URL: /integrations/codex
-
OpenCode
- URL: /integrations/opencode
-
Droid
- URL: /integrations/droid
-
Goose
- URL: /integrations/goose
-
Pi
- URL: /integrations/pi
Assistants
- OpenClaw
- URL: /integrations/openclaw
IDEs & Editors
-
VS Code
- URL: /integrations/vscode
-
Cline
- URL: /integrations/cline
-
Roo Code
- URL: /integrations/roo-code
-
JetBrains
- URL: /integrations/jetbrains
-
Xcode
- URL: /integrations/xcode
-
Zed
- URL: /integrations/zed
Chat & RAG
- Onyx
- URL: /integrations/onyx
Automation
- n8n
- URL: /integrations/n8n
Notebooks
- marimo
- URL: /integrations/marimo
Install
Usage with Ollama
- Link: Confirm the Host URL is ` then click Ok
- URL: http://localhost:11434`,
Install
Usage with Ollama
- Link: In marimo, go to the user settings and go to the AI tab. From here you can find and configure Ollama as an AI provider. For local use you would typically point the base url to `
Connecting to ollama.com
Install
Using Ollama Locally
- Link: Confirm Base URL is set to
http://host.docker.internal:11434` if running through docker and click Saveif running locally or
Connecting to ollama.com
-
API key
-
Link: Set the API URL to `
- URL: https://ollama.com`
Overview
Install Onyx
Usage with Ollama
- Link: Provide your Ollama API URL and select your models.
<Note>If you're running Onyx in Docker, to access your computer's local network use
http://127.0.0.1`.</Note>instead of
Send your first query
Quick start
Configure without launching
Recommended models
Connect messaging apps
Stopping the gateway
Install
Usage with Ollama
Cloud Models
Connecting to ollama.com
- API key
Install
Usage with Ollama
Install
Usage with Ollama
- Link: (Optional) Update
if your Ollama instance is running remotely. The default is `Base URL
Connecting to ollama.com
-
API key
-
Link: Enable
and set it to `Use custom base URL- URL: https://ollama.com`
Install
Usage with Ollama
Install
Usage with Ollama
Connecting to ollama.com directly
-
API key
-
Link: Select Internet Hosted and enter URL as `
- URL: https://ollama.com`
Install
Usage with Ollama
- Link: Confirm the Host URL is ` then click Connect
- URL: http://localhost:11434`,
Connecting to ollama.com
-
API key
-
Link: Set the API URL to `
- URL: https://ollama.com`
Install
Manual install
Customizing
Updating
Installing specific versions
Viewing logs
Uninstall
System Requirements
Filesystem Requirements
Troubleshooting
Uninstall
Table of Contents
-
Format
- URL: #format
-
Examples
- URL: #examples
-
Instructions
- URL: #instructions
-
Notes
- URL: #notes
Format
Examples
Instructions
Notes
Get Started
Assistants
Coding
API
LLM libraries
Installing older or pre-release versions on Linux
Linux tmp noexec
Linux docker
NVIDIA GPU Discovery
AMD GPU Discovery
Multiple AMD GPUs
Windows Terminal Errors
System Requirements
Filesystem Requirements
API Access
Troubleshooting
Uninstall
Standalone CLI
How to Use This Skill
Reference these resources when working with Windows.