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GodScore CI – a CI gate that blocks risky changes before production

Hacker News

GodScore CI – a CI gate that blocks risky changes before production

Hi HN, I just released GodScore CI, a GitHub Action that adds a survivability-aware gate to CI. Most CI systems answer: “Does this change work right now?” GodScore CI asks: “Does this change reduce the system’s ability to survive, recover, or self-correct over time?” It runs in two modes: - Free: advisory warnings only - Paid ($10/month per repo): enforcement that can fail the build when risk crosses a threshold It’s intentionally opinionated and designed to catch slow, irreversible degradation that traditional tests miss. Repo: https://github.com/willshacklett/godscore-ci Marketplace: https://github.com/marketplace/actions/godscore-ci Happy to answer questions or hear skepticism.

Visit productView on Hacker NewsJan 29, 2026
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: just released, io · Missing: https docs, excited, exist
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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
29%29% 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
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

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