PlaintextOffenders API and Searchable Database

Hacker News

based on the work of the from plaintextoffenders.com - guys (@omervk and @hmemcpy, see more here: https://news.ycombinator.com/item?id=7943365) i build a browseable and searchable page (https://8ack.de/plato/) for easier access to the entries. there is an api included ( https://8ack.de/plato/info/#api ) that should serve app/browser-extension-builders who'd like to retrieve the whole list at once. short docu is available ( https://8ack.de/plato/info/ ) thoughts and comments appreciated p.s.: be gentle, it's my first time :D

Visit product View on Hacker NewsJun 26, 2014

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

66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Strong signals: mcp, new, plain · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

41%41% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

38%38% 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.

Correct prediction on native model

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