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# Quick Start: OpenClaw Integration
**Feature**: 001-openclaw-integration | **Date**: 2026-02-27
## Prerequisites
- Python 3.12+
- An OpenClaw agent that has completed at least one session
- An Anthropic API key (or any LiteLLM-supported provider)
## Setup (3 steps)
### 1. Install
```bash
git clone https://github.com/kayba-ai/agentic-context-engine.git
cd agentic-context-engine
uv sync
```
### 2. Configure
```bash
export ANTHROPIC_API_KEY="your-api-key"
```
Optional overrides:
```bash
export OPENCLAW_AGENT_ID="main" # which agent to learn from
export OPENCLAW_HOME="~/.openclaw" # OpenClaw home directory
export ACE_MODEL="anthropic/claude-sonnet-4-20250514" # LLM model
```
### 3. Run
```bash
# Learn from all past sessions
uv run python examples/openclaw/kayba-ace/learn_from_traces.py
# Preview what would be processed (no LLM calls, no file changes)
uv run python examples/openclaw/kayba-ace/learn_from_traces.py --dry-run
# Reprocess everything (ignore what's already been learned)
uv run python examples/openclaw/kayba-ace/learn_from_traces.py --reprocess
```
## What Happens
1. **Discovers** session transcripts from `~/.openclaw/agents/<id>/sessions/`
2. **Parses** JSONL files into structured traces (user messages, reasoning, tool calls)
3. **Learns** by running ACE's Reflect → Tag → Update → Apply pipeline
4. **Saves** strategies to `~/.openclaw/ace_skillbook.json`
5. **Syncs** strategies into `~/.openclaw/workspace/AGENTS.md`
6. Your OpenClaw agent reads the updated AGENTS.md on its next session
## Automate (optional)
Run every 30 minutes via cron:
```bash
crontab -e
# Add:
*/30 * * * * cd /path/to/agentic-context-engine && uv run python examples/openclaw/kayba-ace/learn_from_traces.py >> /tmp/ace-openclaw.log 2>&1
```
## Verify
After running, check the output:
```bash
# View learned strategies
cat ~/.openclaw/ace_skillbook.json | python -m json.tool | head -50
# View what was injected into your agent
grep -A 20 "ACE:SKILLBOOK:START" ~/.openclaw/workspace/AGENTS.md
```