Orkas
Reduces vendor lock-in and latency by running AI agents locally while orchestrating multiple coding tools through a single commander LLM, enabling offline-ca…
Orkas is an open-source, local-first AI desktop app: a commander LLM directs specialist sub-agents, and runs your installed coding CLIs — Claude Code, Codex, OpenCode, OpenClaw, Hermes — as local sessions. Agents self-evolve via reflection and skill crystallization. BYO keys. macOS / Windows / Linux.
- Automate repetitive coding tasks by directing specialist agents to run CLI commands locally.
- Set up development environments across multiple projects without manual command-line work.
- Execute complex workflows combining Claude Code with other coding tools in one session.
Reduces vendor lock-in and latency by running AI agents locally while orchestrating multiple coding tools through a single commander LLM, enabling offline-capable workflows without external API dependencies.
Engineering teams standardizing on local AI workflows and needing to coordinate multiple coding assistants across macOS, Windows, or Linux environments.
https://github.com/Orkas-AI/Orkas
By Orkas-AI
How to Get It
claude plugins install Orkas-AI/Orkas
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:
Help me automate repetitive coding tasks by directing specialist agents to run CLI commands locally
Trust Signals Auto-scanned
Community Pulse Quiet
No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 2,141 GitHub stars; contributors unknown; last commit 0d ago; license MIT.
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.
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Evaluation
Scored from trust signals (evidence-eval-v1): 2,141 GitHub stars; contributors unknown; last commit 0d ago; license MIT.