Compare
Up to three tools. The table shows the data as-is, without picking a “best”.
| Field | Lychee | Miller | act |
|---|---|---|---|
| Platforms | Universal | Universal, MCP, Claude Code, Codex, Cursor | GitHub |
| Local support | Yes | Yes | Yes |
| Paid API | No | No | No |
| License | MIT OR Apache-2.0 | BSD-2-Clause | MIT |
| Stars | 4057 | 10051 | 72471 |
| Last activity | October 26, 2026 | October 21, 2026 | — |
| Install complexity | — | EASY | — |
| Category | Testing, Workflow | Workflow, Data | Testing, Git, DevOps |
| Best use | For documentation authors and small teams checking references locally or in CI. Start with a specific file and interpret findings; it does not establish complete site or login functionality. | 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. |