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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | goose | Miller | act |
|---|---|---|---|
| Platforms | Universal, MCP | Universal, MCP, Claude Code, Codex, Cursor | GitHub |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | Apache-2.0 | BSD-2-Clause | MIT |
| Stars | 55590 | 10049 | 72437 |
| Last activity | October 23, 2026 | October 21, 2026 | — |
| Install complexity | MEDIUM | EASY | — |
| Category | Code Review, Multi-Agent, Workflow | Workflow, Data | Testing, Git, DevOps |
| Best use | 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. | 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 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. |