PromptProof – CI gate for LLM outputs (schema/regex/cost; no API keys)

Hacker News

I built a tiny GitHub Action that fails PRs when LLM output breaks contracts. No live model calls in CI... it runs on recorded fixtures. What it does: Deterministic checks: JSON schema, regex, list/set equality, numeric bounds, file diff Snapshots + regression compare Cost budget gate PR comment + HTML report Try it in a minute: copy the Quick Start, open a PR, see red → fix → green. Links: Marketplace: https://github.com/marketplace/actions/promptproof-eval Demo repo: https://github.com/geminimir/promptproof-demo-project Sample report: https://geminimir.github.io/promptproof-action/reports/befor ... Looking for blunt feedback... Was onboarding smooth? Anything missing you expected? Is the report clear enough to make this a required check?

Visit product View on Hacker NewsAug 23, 2025

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, tiny, gemini · Missing: mac, agents, macos

84%84% 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 HackersIH features products with proven revenue · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

43%43% 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

32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% 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

23%23% 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

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

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

Correct prediction on native model

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