omega-memory/omega-memory
openclaw-skill/SKILL.md
Persistent memory for AI coding agents. Semantic search, auto-capture, checkpoint/resume across sessions.
$ install --global
skillsauthnpx skillsauth add omega-memory/omega-memory omega-memoryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last scanned: Apr 9, 2026, 2:42 AM4.9s1 file scanned
SKILL.md
- name:
- omega-memory
- description:
- Persistent memory for AI coding agents. Semantic search, auto-capture, checkpoint/resume across sessions.
- version:
- 1.0.0
- requires_binaries:
- ["python3", "pip3"]
- requires_env:
- []
OMEGA Memory
Persistent memory for AI coding agents. Your agent remembers decisions, learns from mistakes, and picks up where it left off.
Installation
pip3 install omega-memory[server]
omega setup
The omega setup command auto-configures your MCP client (Claude Code, Cursor, Windsurf, or Zed). No API keys needed — runs fully local with CPU-only embeddings.
What It Does
OMEGA gives your agent a persistent memory layer across coding sessions:
- Decisions & context carry forward — no re-explaining
- Lessons learned from errors are recalled before you repeat them
- Checkpoint/resume lets you pause complex tasks and pick up later
- Semantic search over all stored memories with contextual re-ranking
MCP Tools (12 tools)
| Tool | Purpose |
|------|---------|
| omega_welcome | Session briefing with recent memories and profile |
| omega_protocol | Retrieve operating rules and behavioral guidelines |
| omega_store | Store typed memory (decision, lesson, error, preference, summary) |
| omega_query | Semantic or phrase search with tag filters and re-ranking |
| omega_lessons | Cross-session lessons ranked by access count |
| omega_profile | Read or update the user profile |
| omega_checkpoint | Save task state for cross-session continuity |
| omega_resume_task | Resume a previously checkpointed task |
| omega_memory | Manage a specific memory (edit, delete, feedback, similar, traverse) |
| omega_remind | Set, list, or dismiss time-based reminders |
| omega_maintain | System housekeeping (health, consolidate, compact, backup, restore) |
| omega_stats | Analytics: type breakdown, session stats, weekly digest, access rates |
Usage Pattern
At the start of every session:
- Call
omega_welcome()for context briefing - Call
omega_protocol()for operating instructions - Follow the protocol it returns
During work:
- Before non-trivial tasks:
omega_query()to check for prior context - After completing tasks:
omega_store(content, "decision")to save key outcomes - When context is getting full:
omega_checkpoint()to save state
Links
- PyPI: https://pypi.org/project/omega-memory/
- GitHub: https://github.com/omega-memory/omega-memory
- Website: https://omegamax.co
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