IfThisThenThat Linter (IFTTT-Lint)

Hacker News

An open‑source implementation of Google's internal IfThisThenThat (IFTTT) linter tool. Enforce atomic pull requests by declaring file dependencies in your code: If this file changes, then that file or region must also change. -- Disclosure: I work at OpenAI. I've been missing IFTTT this since leaving Google, esp. for working in large repos. Wrote this over the weekend w/ codex; so don't judge too harshly. JS seemed like the right language for it, but I know basically zero. Happily, that's no longer a blocker for small projects like this one.

Visit product View on Hacker NewsApr 23, 2025

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2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, codex, openai · Missing: mac, agents, macos

91%91% 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 NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

61%61% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

50%50% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

21%21% 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

18%18% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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