Vim friendly TUI for todos that works with existing md files

Hacker News

I'm spending more time in the terminal (ghostty) since moving to claude code. I wanted a quick way to edit a todo.md alongside claude in a tmux pane that I check into my repo. lazytodo is a terminal UI that treats any markdown checkbox file as a todo list. No syncing, no database. Just point it at your existing todo.md. Features: - Vim-style navigation (j/k, g/G, dd, u/Ctrl+r for undo/redo) - Visual line selection (V) for bulk toggling - Inline editing with Tab/Shift+Tab for indentation - External editor support ($EDITOR or vim) - Auto-reloads when the file changes externally - Renders markdown formatting in task text (bold, links, code) GitHub: https://github.com/magdyksaleh/lazytodo

Visit product View on Hacker NewsJan 31, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, visual, code · Missing: mac, agents, macos

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

45%45% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: host, friendly · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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