Building a Small Terminal Command Helper with an LLM

I regularly lose time to terminal muscle memory.

I work across Windows and Unix-like shells, so I will remember the right command in the wrong environment, transpose a Git subcommand, or use a valid binary with an invalid subcommand. The fix is usually easy to find. The interruption is the costly part: stop, search, translate the answer back into the current shell, and try again.

The idea is not new. There are projects that help with failed commands, as well as terminal-integrated LLMs such as aichat. However, I wanted something that does one thing well: fix commands in a seamless workflow powered by an LLM.

I wanted a deliberately narrow tool: when a command fails, suggest the command I probably meant, let me inspect it, and run it only after confirmation.

During a Fable promotion period, I used an LLM coding agent to see how far a well-scoped prompt could get me. With very little steering, it produced a usable Go prototype in roughly an hour.

The project is now open source:

I am continuing to use it as a real terminal workflow rather than treating it as a one-off demo. That is the real test for this kind of project: not whether an LLM can generate a repository, but whether the resulting tool remains useful after the novelty wears off.