> Persistent memory system for AI agents
Scanned 9/7/2026
Install to Claude Code
npx -y skills add Demerzels-lab/elsamultiskillagent --skill agent-memory --agent claude-codeInstalls into .claude/skills of the current project.
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# AgentMemory Skill
> Persistent memory system for AI agents
## Overview
AgentMemory enables AI agents to retain information across sessions. It provides fact storage, experience learning, and entity tracking with zero external dependencies.
## Key Features
- **Fact storage** via `remember()` with tagging capabilities
- **Experience learning** through `learn()` method
- **Memory retrieval** using `recall()` for facts and `get_lessons()` for experiences
- **Entity tracking** for people and projects
- **Semantic search** using FTS5
- **Auto-cleanup** for stale information
## Installation
```bash
# Via ClawHub (recommended)
clawdhub install agent-memory
# Or clone
git clone https://github.com/openclaw/skills
cp -r skills/dennis-da-menace/agent-memory ~/.clawdbot/skills/
```
## Storage
Default location: `~/.agent-memory/memory.db`
Custom path supported via configuration.
## Core API
### Remember Facts
```python
from memory import AgentMemory
mem = AgentMemory()
# Store a fact
mem.remember(
"User prefers dark mode",
tags=["preference", "ui"],
confidence=0.9
)
# Store with entity link
mem.remember(
"John's birthday is March 15",
tags=["personal"],
entity="john"
)
```
### Learn from Experience
```python
mem.learn(
action="Deployed to production without tests",
context="Friday evening rush",
outcome="failure",
insight="Always run tests before deploy, especially on Fridays"
)
```
### Recall Memories
```python
# Search facts
facts = mem.recall("user preferences")
# Get lessons
lessons = mem.get_lessons(context="deployment", outcome="failure")
```
### Track Entities
```python
mem.track_entity("john", {
"role": "client",
"company": "Acme Inc",
"preferences": ["email", "brief updates"]
})
```
## Integration Protocol
Recommended workflow for agent configuration:
```yaml
memory_protocol:
session_start:
- Load recent lessons
- Check entity context
during_session:
- Extract durable facts
- Learn from outcomes
session_end:
- Update entity information
- Record session summary
```
## Dependencies
- Python 3.8+
- SQLite (built-in)
No external packages required.
## License
MIT
## Author
Dennis Da Menace - Built for the OpenClaw community
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