techniqueadvancedOpenCLAW

OpenCLAW v2026.3.7-beta.1: Introducing the ContextEngine Plugin Interface

OpenCLAW's latest update introduces a 'ContextEngine' for smarter, more customizable AI agents that can handle complex tasks and remember more information. It also adds automatic failover, ensuring the AI remains operational by switching between different AI models (like OpenAI or Google) if one fails, increasing reliability for business-critical applications.

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-beta.1: Introducing the ContextEngine Plugin Interface

## What This Is
OpenCLAW's latest update introduces a 'ContextEngine' for smarter, more customizable AI agents that can handle complex tasks and remember more information. It also adds automatic failover, ensuring the AI remains operational by switching between different AI models (like OpenAI or Google) if one fails, increasing reliability for business-critical applications.

Source: https://skywork.ai/blog/ai-agent/clawdbot-openclaw-agentic-ai/

## 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/blog/ai-agent/clawdbot-openclaw-agentic-ai/) 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 project for an existing OpenCLAW installation. If found, recommend updating to version `v2026.3.7-beta.1` or later by checking the project's dependency manager (e.g., `requirements.txt`, `package.json`). If not installed, clone the official GitHub repository for OpenCLAW.
- Review project dependencies and security logs for any mention of CVE-2026-25253. Advise pinning the OpenCLAW version to `v2026.3.7-beta.1` and implementing network isolation rules (e.g., loopback address, VPN) as a security best practice.
- Draft a basic `ContextEngine` plugin implementation using the new interface. Create a stub class that logs context lifecycle events (e.g., `on_sub_agent_spawn`, `on_rag_pipeline_start`) to demonstrate the new functionality and prepare for custom context management logic.

## 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

3,301 charactersCompatible with Claude Code & Codex CLI

MANUAL SETUP STEPS

01Scan the project for an existing OpenCLAW installation. If found, recommend updating to version `v2026.3.7-beta.1` or later by checking the project's dependency manager (e.g., `requirements.txt`, `package.json`). If not installed, clone the official GitHub repository for OpenCLAW.
02Review project dependencies and security logs for any mention of CVE-2026-25253. Advise pinning the OpenCLAW version to `v2026.3.7-beta.1` and implementing network isolation rules (e.g., loopback address, VPN) as a security best practice.
03Draft a basic `ContextEngine` plugin implementation using the new interface. Create a stub class that logs context lifecycle events (e.g., `on_sub_agent_spawn`, `on_rag_pipeline_start`) to demonstrate the new functionality and prepare for custom context management logic.

FIELD OPERATIONS

Per-User Contextual Agent

Build a multi-tenant Discord bot where each user gets a dedicated, isolated sub-agent spawned by the ContextEngine. The sub-agent will maintain a long-term memory of that specific user's conversation history using a custom SQLite-backed memory plugin, ensuring personalized and private interactions.

Cost-Optimizing RAG Pipeline

Create a RAG system that uses OpenCLAW's dual-engine routing. The ContextEngine first routes simple queries to a fast, cheap model (e.g., Gemini Flash) for initial document retrieval. If the task is complex or the response is low-confidence, it automatically fails over to a powerful, expensive model (e.g., Claude 3 Opus) for final synthesis, optimizing for both cost and quality.

STRATEGIC APPLICATIONS