agentmind-openclaw
# AgentMind for OpenClaw
What this skill does
# AgentMind for OpenClaw Self-learning memory system that makes AI agents understand you better over time. Automatically detects your preferences, workflows, and code style from interactions. ## Trigger Use when user asks about learned preferences, wants to review agent behavior patterns, or when starting a session that should leverage previously learned knowledge. ## Commands - `/agentmind status` — Show learning overview - `/agentmind instincts` — List learned behaviors - `/agentmind evolve` — Trigger evolution cycle - `/agentmind preferences` — Show detected preferences - `/agentmind approve <id>` — Approve a learned behavior - `/agentmind reject <id>` — Reject a learned behavior ## How It Works (OpenClaw Mode) Unlike the Claude Code plugin which uses lifecycle hooks, the OpenClaw adaptation works through: 1. **Memory Analysis**: Reads `memory/*.md` files and conversation history to detect patterns 2. **Bootstrap Injection**: High-confidence instincts are injected via BOOTSTRAP.md 3. **Periodic Learning**: A cron job runs `analyze` to discover new patterns from recent interactions 4. **Manual Feedback**: Users can approve/reject instincts through chat commands ## Setup ```bash # Install as OpenClaw skill cp -r skills/agentmind-openclaw ~/.openclaw/skills/agentmind/ # Create cron for periodic learning (every 6 hours) openclaw cron create --name "AgentMind Learn" \ --schedule "0 */6 * * *" \ --task "Run AgentMind analysis on recent memory files" ``` ## Data Location - Instincts: `~/.openclaw/workspace/agentmind/instincts.json` - Observations: `~/.openclaw/workspace/agentmind/observations/` ## Integration with OpenClaw Memory AgentMind complements OpenClaw's built-in `memory_search` (pull-based) with push-based injection — high-confidence instincts are automatically included in the agent's context without needing to search for them.
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