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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | dsh-agent-teams | DuckDB | Miller |
|---|---|---|---|
| Platforms | DeepSeek Harness | Universal | Universal, MCP, Claude Code, Codex, Cursor |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | MIT | MIT | BSD-2-Clause |
| Stars | 2386 | 42451 | 10049 |
| Last activity | — | September 28, 2026 | October 21, 2026 |
| Install complexity | يتطلب إصدار DSH متوافقًا وإعادة تشغيل | سهل — حزمة Python أو ملف CLI تنفيذي واحد | EASY |
| Category | Multi-Agent, Workflow | Database | Workflow, Data |
| 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 analyst, developer, or small team that needs to inspect and join large data files and rerun analysis locally. It adds reviewable SQL without database-server setup. It is not a multi-user transactional database for many small concurrent writes from 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. |