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Skills agent-memory

Full AI agent memory stack — Mem0 unified memory engine with vector search (Qdrant) and knowledge graph (Neo4j), plus SQLite for structured data. Complete setup script and tools. Give your OpenClaw agent a real brain with semantic recall, entity relationships, and structured storage.

install
source · Clone the upstream repo
git clone https://github.com/openclaw/skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/aiwithabidi/agent-memory-pro" ~/.claude/skills/openclaw-skills-agent-memory && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/aiwithabidi/agent-memory-pro" ~/.openclaw/skills/openclaw-skills-agent-memory && rm -rf "$T"
manifest: skills/aiwithabidi/agent-memory-pro/SKILL.md
tags
#memory-management#vector-database#knowledge-graph#sqlite#semantic-search
source content

Agent Memory 🧠

Full intelligence layer: vector memory + knowledge graph + structured database.

When to Use

  • Storing and recalling facts semantically ("remember that Abidi prefers...")
  • Managing structured data: projects, contacts, tasks, bookmarks
  • Setting up the brain stack after container rebuild
  • Batch seeding memory with key facts

Usage

Memory Engine (Mem0 — vectors + graph)

# Store a fact
python3 {baseDir}/scripts/memory_engine.py add "Abidi's business focuses on Voice AI"

# Semantic recall
python3 {baseDir}/scripts/memory_engine.py search "what does Abidi's business do"

# List all memories
python3 {baseDir}/scripts/memory_engine.py get-all

# Test connections (Qdrant, Neo4j, Langfuse)
python3 {baseDir}/scripts/memory_engine.py test

Structured Database (SQLite)

# List tables
python3 {baseDir}/scripts/structured_db.py tables

# Insert data
python3 {baseDir}/scripts/structured_db.py insert projects '{"name":"MyProject","status":"active"}'

# Query
python3 {baseDir}/scripts/structured_db.py query "SELECT * FROM projects"

Setup & Seeding

# Install Python deps after container rebuild
bash {baseDir}/scripts/setup_brain.sh

# Batch seed with key facts
python3 {baseDir}/scripts/seed_mem0.py

Architecture

  • Mem0 — Unified AI memory (auto fact extraction, dedup, multi-level recall)
  • Qdrant — Vector database for semantic search
  • Neo4j — Knowledge graph for entities & relationships
  • SQLite — Structured data (projects, contacts, tasks, bookmarks)
  • Langfuse — Observability tracing on all operations

Credits

Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.

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