Flagged: installs a background service. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by unohee · Claude Skill · ★ 840
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🔒 Is OpenSwarm safe to install? View the security audit →
OpenSwarm Autonomous AI agent orchestrator — Claude, GPT, Codex, and local models (Ollama/LMStudio/llama.cpp) OpenSwarm orchestrates multiple AI agents as autonomous code workers. It picks up Linear issues, runs Worker/Reviewer pair pipelines, reports to Discord, and retains long-term memory via LanceDB. Supports Claude Code, OpenAI GPT, Codex, and local open-source models via Ollama, LMStudio, or llama.cpp. Quick Start That's it. with no arguments launches the TUI chat interface immediately. TUI keyboard shortcuts Status bar shows: provider · model · message count · cumulative cost CLI Commands bash openswarm # TUI chat (default) openswarm chat [session] # Simple readline chat openswarm start # Start full daemon (requires config.yaml) openswarm run
| Stars | 840 |
| Forks | 146 |
| Language | TypeScript |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 66.8470010548986/100 |
| Last Updated | 2026-08-31 |
| Created | 2026-02-23 |
| Platforms | claude-code, cli, node |
| Est. Tokens | ~18k |
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OpenSwarm is OpenSwarm — Autonomous AI dev team orchestrator powered by Claude Code CLI. Discord control, Linear integration, cognitive memory.. It is categorized as a Claude Skill with 840 GitHub stars.
OpenSwarm is primarily written in TypeScript. It covers topics such as ai-agents, ai-coding, autonomous-agents.
You can find installation instructions and usage details in the OpenSwarm GitHub repository at github.com/unohee/OpenSwarm. The project has 840 stars and 146 forks, indicating an active community.
OpenSwarm is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to OpenSwarm on Agent Skills Hub include OpenSwarm, agent-of-empires, boluobobo-ai-court-tutorial. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: