What this skill does

# AgentMemory Skill Persistent memory system for AI agents. Remember facts, learn from experience, and track entities across sessions. ## Installation ```bash clawdhub install agent-memory ``` ## Usage ```python from src.memory import AgentMemory mem = AgentMemory() # Remember facts mem.remember("Important information", tags=["category"]) # Learn from experience mem.learn( action="What was done", context="situation", outcome="positive", # or "negative" insight="What was learned" ) # Recall memories facts = mem.recall("search query") lessons = mem.get_lessons(context="topic") # Track entities mem.track_entity("Name", "person", {"role": "engineer"}) ``` ## When to Use - **Starting a session**: Load relevant context from memory - **After conversations**: Store important facts - **After failures**: Record lessons learned - **Meeting new people/projects**: Track as entities ## Integration with Clawdbot Add to your AGENTS.md or HEARTBEAT.md: ```markdown ## Memory Protocol On session start: 1. Load recent lessons: `mem.get_lessons(limit=5)` 2. Check entity context for current task 3. Recall relevant facts On session end: 1. Extract durable facts from conversation 2. Record any lessons learned 3. Update entity information ``` ## Database Location Default: `~/.agent-memory/memory.db` Custom: `AgentMemory(db_path="/path/to/memory.db")`