Chorus Model Card
这是可索引项目报告证据页：它保留 Chorus Model Card 的源材料入口、机制线索和限制提醒；正文仍需 reader/editor 与 academic public-copy review 后才能当作最终结论引用。
Chorus Model Card
| Field | Value |
|---|---|
| Repository | Chorus-AIDLC/Chorus |
| Category | AI-Human Collaboration Harness |
| Stars / forks snapshot | 909 / 84 |
| Language | TypeScript |
| License | AGPL-3.0 |
| Raw capture | raw-github/chorus-aidlc_chorus.md |
| Updated by | hourly public metadata update, 2026-05-26 09:12 +0800 |
1. Role in Self Evolve
Chorus is an AI-human collaboration harness that manages session lifecycle, task state, sub-agent orchestration, permissions, observability and failure recovery around LLM agents. It matters because self-evolving agents need reliable harnesses, memory/skill surfaces, feedback evidence and benchmark loops before any improvement claim can be trusted.
2. Working Principle
requirements/task state -> sub-agent orchestration -> permissions/context injection -> observability/failure recovery -> OpenSpec archival
3. Evidence Path
web-observed GitHub page showed 909 stars, 84 forks, 471 commits, AGPL-3.0 license, TypeScript primary language, v0.8.2 latest on 2026-05-21, and README sections for lifecycle hooks, permissions, task state, context injection and OpenSpec mode. 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 AI-Human Collaboration Harness: it shows which part of the agent improvement stack is made operational, and where evaluator, policy, memory, skill, task-state or artifact evidence enters the loop.
5. Limits
The repository was not cloned in this iteration; no benchmark, install flow, workflow run, policy audit, memory experiment, OpenClaw run, or agent loop was executed. Counts and claims are visible public-page/search signals unless independently revalidated later.