typomat – CLI typing practice that builds prompts from your own code

Hacker News

typomat is a minimalistic typing practice TUI. It retrieves words from a local directory's code files by extracting the lexical content from variables, strings, signatures etc. These words are then used to build short, randomized typing exercises. In essence, the app lets you practice the character patterns that will actually show up during your coding sessions. This enables relevant 'finger warmups' before work. typomat is .gitignore-friendly, caches results for quick loading times, and can be installed via Homebrew or Scoop. Created with golang/bubble tea. Enjoy!

Visit product View on Hacker NewsDec 31, 2025

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

73%73% 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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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