ScaleLighthouse – Bulk Lighthouse, Playwright smoke tests, CrUX metrics

Hacker News

I kept running into the same problems across web projects — JS errors silently breaking pages, no visibility into per-page SEO or performance, and Lighthouse only auditing one URL at a time. So I built ScaleLighthouse. It's a config-driven platform that runs Lighthouse audits, Playwright smoke tests (JS errors, missing DOM elements, broken flows), and CrUX real-user metrics across your entire site. Works on localhost, staging, or production — including authenticated pages. No test code to write. pnpm monorepo, Vue 3 dashboard, MIT licensed.

Visit product View on Hacker NewsJan 26, 2026

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Launch Intel predictions

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

82%82% 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: including · Missing: supports, reddit linkedin, podcasting

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

28%28% 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

21%21% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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