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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | dsh-agent-teams | goose | Task |
|---|---|---|---|
| Platforms | DeepSeek Harness | Universal, MCP | Universal, GitHub |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | MIT | Apache-2.0 | MIT |
| Stars | 2386 | 55588 | 16277 |
| Last activity | — | October 23, 2026 | — |
| Install complexity | يتطلب إصدار DSH متوافقًا وإعادة تشغيل | MEDIUM | سهل / Easy |
| Category | Multi-Agent, Workflow | Code Review, Multi-Agent, Workflow | Workflow, DevOps |
| 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 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. | Best for a developer or small team whose project commands span languages, folders, and tools. It provides documented entry points that people and agents can use and review in Git. Existing scripts may be enough for a simple project; Task does not install project tools or sandbox their commands. |