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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | dsh-agent-teams | Miller | Task |
|---|---|---|---|
| Platforms | DeepSeek Harness | Universal, MCP, Claude Code, Codex, Cursor | Universal, GitHub |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | MIT | BSD-2-Clause | MIT |
| Stars | 2386 | 10049 | 16277 |
| Last activity | — | October 21, 2026 | — |
| Install complexity | يتطلب إصدار DSH متوافقًا وإعادة تشغيل | EASY | سهل / Easy |
| Category | Multi-Agent, Workflow | Workflow, Data | 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. | Ideal for developers, data analysts, and operators who need to clean a CSV export, inspect JSON Lines, or summarize a large file from the terminal without starting a Python project. Use it for quick, repeatable file processing; concurrent transactions and advanced visual analysis still call for a database or complementary analytics tool. | 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. |