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Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | marimo | goose | act |
|---|---|---|---|
| Platforms | Universal | Universal, MCP | GitHub |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | Apache-2.0 | Apache-2.0 | MIT |
| Stars | 23382 | 56014 | 72501 |
| Last activity | October 29, 2026 | October 23, 2026 | — |
| Install complexity | EASY | MEDIUM | — |
| Category | Workflow, Data | Code Review, Multi-Agent, Workflow | Testing, Git, DevOps |
| Best use | Ideal for a data analyst, Python developer, or small team that wants reproducible experiments, clear Git review, and an interactive report or internal tool from the same source. It is not a replacement for governed BI or a production service requiring enterprise scaling and permissions. | 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 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. |