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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | dsh-agent-teams | act | goose |
|---|---|---|---|
| Platforms | DeepSeek Harness | GitHub | Universal, MCP |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | MIT | MIT | Apache-2.0 |
| Stars | 2386 | 72437 | 55588 |
| Last activity | — | — | October 23, 2026 |
| Install complexity | يتطلب إصدار DSH متوافقًا وإعادة تشغيل | — | MEDIUM |
| Category | Multi-Agent, Workflow | Testing, Git, DevOps | Code Review, Multi-Agent, Workflow |
| Best use | For development work that can be divided into dependent tasks and reviewed as a plan before agents start. Monitor outputs and model costs; team state is not coordinated across separate processes. | Best for a developer or small team that repeatedly edits GitHub Actions workflows and wants to test a job before pushing. It provides a local run log, while a final GitHub check remains necessary. It is not suitable when exact hosted-runner parity is required. | Best for an individual developer or small team that wants an AI agent to complete an inspectable task in a working copy: understand files, make a bounded change, and run a test. Start with manual approval and scope the folder and tools. Do not give it broad access to production or sensitive data. |