OpenSwarm Multi-Agent Orchestration Framework Model Card
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OpenSwarm Multi-Agent Orchestration Framework Model Card
| Field | Value |
|---|---|
| Repository | openswarm-ai/openswarm |
| Category | Multi-Agent Swarm Orchestration Framework with Lightweight Runtime Control |
| Stars / forks snapshot | 129 / 16 |
| Language | Python |
| License | MIT |
| Raw capture | raw-github/openswarm-ai_openswarm.md |
| Updated by | hourly public metadata update, 2026-06-02 01:55 +0800 |
1. Role in Self Evolve
openswarm-ai/openswarm provides lightweight multi-agent orchestration primitives for building swarm-style autonomous workflows. It matters because self-evolving agents need repeatable harness control, measurable feedback loops, and reusable skill procedures before claiming stable improvement.
2. Working Principle
assemble multiple role-specific agents into swarm workflows -> dispatch tasks across shared control boundaries -> coordinate context and handoff logic through lightweight runtime primitives -> support reproducible multi-agent execution loops in production-like settings
3. Evidence Path
web-observed GitHub page showed 129 stars, 16 forks, 91 commits, MIT license, and explicit lightweight multi-agent orchestration framing. Shell GitHub API access remained blocked by DNS and local gh auth was invalid, so this card treats the snapshot as web-observed rather than API-verified.
4. Teaching Use
Use this card to explain Multi-Agent Swarm Orchestration Framework with Lightweight Runtime Control: it shows how harness/runtime/benchmark layers convert agent behavior into reproducible and auditable engineering workflows.
5. Limits
The repository was not cloned in this iteration; no benchmark run, plugin install, workflow execution, or agent loop experiment was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.