A comprehensive integration layer for connecting coding agents, IDEs, and app backends to Ollama for local or cloud-based AI inference.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ollama-skill
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install ollama-skill using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Ollama Runtime Skill?
The Ollama Runtime Skill provides a robust framework for integrating Ollama into diverse AI coding environments and agent harnesses. It offers a developer-friendly path for implementing native API calls or leveraging compatibility modes for OpenAI and Anthropic SDKs.
By using this entry in the Openclaw Skills library, developers can seamlessly switch between local on-prem deployments and Ollama Cloud while maintaining consistent workflows for streaming, structured outputs, and tool calling. This skill focuses on high-performance runtime and inference integration with minimal code changes.
Ollama Runtime Skill Use Cases
- Running Ollama locally or in Docker for data privacy and low-latency coding tasks
- Wiring coding assistants like Claude Code or VS Code plugins to Ollama APIs
- Implementing provider-agnostic model routing in enterprise agent harnesses
- Generating machine-readable JSON data for multi-stage agent pipelines
- Enabling semantic search and RAG via local embedding models
How Ollama Runtime Skill Works
- Identification of the preferred deployment mode such as local, Docker, or direct cloud API.
- Configuration of system environment variables for API base URLs and authentication keys.
- Implementation of the core chat path using native REST endpoints or compatibility adapters.
- Optional activation of advanced features like streaming, structured outputs, or tool calling based on app requirements.
- Execution and validation using integration patterns that ensure proper error handling and model routing.
Ollama Runtime Skill Setup
Environment Configuration
# Local / on-prem / Docker
export OLLAMA_HOST=http://localhost:11434
export OLLAMA_API_BASE=http://localhost:11434/api
export OLLAMA_MODEL=qwen3-coder
# Direct cloud API (optional)
export OLLAMA_API_KEY=your_api_key
Installation
git clone https://github.com/WaiYanNyeinNaing/ollama-skill.git
cd ollama-skill
pip install -r requirements.txt
Ollama Runtime Skill Data Schema & Taxonomy
| Component | Data Type | Description |
|---|---|---|
| API Base URL | String | Endpoint for communication (e.g., http://localhost:11434/api) |
| Message Object | Array | List of roles (system, user, assistant) and content strings |
| Output Format | JSON Schema | Defines the required structure for machine-readable model responses |
| Tool Definition | Object | Schema for external functions including name, description, and parameters |
Ollama Runtime Skill Advanced Features
- Multi-protocol compatibility with OpenAI and Anthropic SDK patterns to reduce migration costs
- Support for reasoning traces and thinking models in agentic workflows
- Parallel tool calling for efficient execution of multiple external functions
- Native embedding support for RAG and semantic search applications
- Configurable streaming for real-time UI feedback in terminals and coding editors
SKILL.md
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