RALPH.md is a skill-like format for reusable agent loops. It defines the outer loop around an agent run: the agent command, the commands to run between iterations, the arguments for steering, and the prompt body. That makes it possible to package and share loops that run repeatedly until stopped. I’ve been writing down example patterns and use cases in the cookbook as I learn what works well: https://ralphify.co/docs/cookbook/
Point it at a code project directory to get a file tree and content, optionally with a git diff, copied to the clipboard - ready for copy pasting into ChatGPT.
It is very true that this only works for small projects, as you will bloat the LLM’s context with large codebases.
My solution to this is two files you can use to steer the tool’s behavior:
- .copconignore: For ignoring specific files and directories.
- .copcontarget: For targeting specific files and directories (applied before .copconignore).
These two files provide great control over what to include and exclude in the copied context.