Octopoda-OS
Reduces AI agent failures and data loss through persistent memory and crash recovery, enabling reliable deployment of autonomous systems in production enviro…
The open-source memory operating system for AI agents. Persistent memory, semantic search, loop detection, agent messaging, crash recovery, and real-time observability.
- Ask Claude to retrieve relevant project context from persistent memory before starting code review.
- Generate semantic search queries to find related documentation across agent conversations and logs.
- Automate crash detection and recovery workflows to resume interrupted development tasks seamlessly.
Reduces AI agent failures and data loss through persistent memory and crash recovery, enabling reliable deployment of autonomous systems in production environments where continuity is critical.
Engineering teams building multi-agent AI systems requiring fault tolerance, state persistence, and real-time debugging capabilities.
https://github.com/RyjoxTechnologies/Octopoda-OS
By RyjoxTechnologies
How to Get It
claude plugins install RyjoxTechnologies/Octopoda-OS
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Retrieve relevant project context from persistent memory before starting code review
Trust Signals Auto-scanned
Community Pulse Active
Discussed on Hacker News, Reddit
- Octopoda open source agent OS with memory, loop detection, and audit trails — Hacker News · 5 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 505 GitHub stars; 6 contributors; last commit 10d ago; license no license.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
How to evaluate tools before deploying →
Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.
Evaluation
Scored from trust signals (evidence-eval-v1): 505 GitHub stars; 6 contributors; last commit 10d ago; license no license.