techniqueadvancedOpenCLAW

OpenCLAW v2026.3.7: Production-Ready Agents with ContextEngine & Model Routing

OpenCLAW, a tool for building custom AI assistants, has a major update that makes it more reliable for business use. It can now automatically switch between different AI models (like from OpenAI or Google) if one fails, and offers a new 'ContextEngine' for developers to create more advanced memory and data retrieval systems for their AI agents.

AI SETUP PROMPT

Paste into Claude Code or Codex CLI — it will scan your project and set everything up

# Apply Technique: OpenCLAW v2026.3.7: Production-Ready Agents with ContextEngine & Model Routing

## What This Is
OpenCLAW, a tool for building custom AI assistants, has a major update that makes it more reliable for business use. It can now automatically switch between different AI models (like from OpenAI or Google) if one fails, and offers a new 'ContextEngine' for developers to create more advanced memory and data retrieval systems for their AI agents.

Source: https://skywork.ai/skypage/en/openclaw-ai-agentic-automation/2037033275390431232

## Before You Start

Scan my workspace and analyze:
- The project language, framework, and directory structure
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)

Then ask me before proceeding:
1. Which AI provider/API should this use? (Use whatever I already have configured, or ask me to set one up — options include direct provider APIs or a unified service like OpenRouter)
2. Where in my project should this be integrated?
3. Are there any customizations I need (model preferences, naming conventions, constraints)?

## Source Access Note

The source URL (https://skywork.ai/skypage/en/openclaw-ai-agentic-automation/2037033275390431232) may not be directly accessible from the terminal. Use the Reference Implementation and Additional Context sections below instead. If you need more details, ask me to paste relevant content from the source.

## What to Implement

This is an **AI Technique** — a pattern or methodology for working with AI models.

- Explain how this technique applies to my current project and what benefit it provides
- Implement it in a way that fits my existing codebase — suggest concrete files to modify or create
- If it requires specific model capabilities (structured output, function calling, etc.), verify my current provider supports them
- Show me a working example I can test immediately

## Additional Context

- Scan the user's project dependencies (e.g., package.json, requirements.txt) to identify if OpenCLAW is used. If present, update the OpenCLAW framework package to the latest stable version, `v2026.3.7-beta.1` or newer.
- Inspect the project's configuration files for an existing AI model setup. Implement the new model routing feature by creating a model chain that includes a primary frontier model (e.g., from OpenAI or Google) and at least one fallback model (e.g., from Anthropic or Cohere), configuring automatic retry and failover logic.
- Create a new plugin class that implements the `ContextEngine` interface. Implement a basic `ingest` hook that logs incoming file content and an `assemble` hook that logs the context being prepared for the LLM prompt, demonstrating the new lifecycle capabilities for custom RAG or memory management.

## Guidelines

- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it

3,373 charactersCompatible with Claude Code & Codex CLI

MANUAL SETUP STEPS

01Scan the user's project dependencies (e.g., package.json, requirements.txt) to identify if OpenCLAW is used. If present, update the OpenCLAW framework package to the latest stable version, `v2026.3.7-beta.1` or newer.
02Inspect the project's configuration files for an existing AI model setup. Implement the new model routing feature by creating a model chain that includes a primary frontier model (e.g., from OpenAI or Google) and at least one fallback model (e.g., from Anthropic or Cohere), configuring automatic retry and failover logic.
03Create a new plugin class that implements the `ContextEngine` interface. Implement a basic `ingest` hook that logs incoming file content and an `assemble` hook that logs the context being prepared for the LLM prompt, demonstrating the new lifecycle capabilities for custom RAG or memory management.

FIELD OPERATIONS

Multi-Provider RAG Agent

Build an agent using the new `ContextEngine` to create a custom Retrieval-Augmented Generation (RAG) pipeline that ingests documents from a local directory. Use the model router to query a primary model (like Claude 3 Opus) with the retrieved context, and configure it to automatically fall back to a cheaper/faster model (like Llama 3) if the primary API call fails or times out.

Self-Contained Sub-Agent Task Executor

Create a main agent that delegates complex tasks to sub-agents. Use the `prepareSubagentSpawn` hook in the `ContextEngine` to provide the sub-agent with only a specific subset of files and memory relevant to its task, preventing context leakage from the main agent and improving focus and efficiency.

STRATEGIC APPLICATIONS