A Claude Code mod that waits for the 5-hour usage limit window to reset and automatically submits "continue" so the session carries on.
✳︎ auto-continue
└─ Make every conversation easier
352 mods for Claude Code workflow mods, ordered by the votes people give them on ClaudeMods. A good place to start: ruflo-loop-workers,ruflo-adr or code-modernization.
Each entry links to its original repository or post, and shows how to install it.
352A Claude Code mod that waits for the 5-hour usage limit window to reset and automatically submits "continue" so the session carries on.
I installed and tested 6 Claude Code 'modes' myself. I'll show you the ones that worked well and the ones that were worse than expected, exactly as they appeared on screen.
Challenge: 100 Consecutive Days of Sharing Claude Code Tips Day 45 | Ask It to Make a Mod with One Sentence This week Claude Code's mods videos keep getting shared, and yesterday I also spent a while asking it "what exactly are mods." To put it plainly, a mod is a small program that runs inside Claude Code: it can add a line of information above the input box, open a panel on the side, or add your own /command. And you don't have to write it yourself—just say what you want: Make a mod that shows the current git branch above the input box It will write the file into ~/.claude/dev-mods/, then ask whether you want to enable hot reload for this session. Choose Enable for this session, and it will appear after this run finishes. If you don't like it, keep talking, and it will auto-reload after changes. Two pitfalls. The mod it writes only lives in this one conversation. If you want to keep it, move that folder out, and later start it with claude --plugin-dir plus that path. Also, a mod is a program running with your permissions, so it can read your files and keys. If someone else shares one, review it before installing.
If I were to follow two repos first, I'd pick official sources: Anthropic Claude Code Releases/CHANGELOG (https://github.com/anthropics/claude-code/releases); OpenAI Codex repo (https://github.com/openai/codex). When updates are frequent, follow releases first; leave commits for tracking specific behavior changes; for Skills/MCP examples, go back to README, source code, and issues to verify, avoiding treating demos as stable practices.