Compare
Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | dsh-agent-teams | Miller | goose |
|---|---|---|---|
| Platforms | DeepSeek Harness | Universal, MCP, Claude Code, Codex, Cursor | Universal, MCP |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | MIT | BSD-2-Clause | Apache-2.0 |
| Stars | 2387 | 10049 | 55592 |
| Last activity | — | October 21, 2026 | October 23, 2026 |
| Install complexity | يتطلب إصدار DSH متوافقًا وإعادة تشغيل | EASY | MEDIUM |
| Category | Multi-Agent, Workflow | Workflow, Data | 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. | 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 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. |