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Persistent memory system for AI agents — remember facts, learn from experience, and track entities across sessions.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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| name | agent-memory |
| description | Persistent memory system for AI agents — remember facts, learn from experience, and track entities across sessions. |
Persistent memory system for AI agents. Remember facts, learn from experience, and track entities across sessions.
clawdhub install agent-memory
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"})
Add to your AGENTS.md or HEARTBEAT.md:
## 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
Default: ~/.agent-memory/memory.db
Custom: AgentMemory(db_path="/path/to/memory.db")