Agentmind Openclaw

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

# 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.