I
I graded HN on a11y wall of shame
Hacker NewsI graded HN on a11y wall of shame
There's a strong correlation between accessible content and machine-readable content, so a11y should also be on-topic for hacking. Many large tech companies treat a11y as a legal obligation. Many disabled people have enough of being viewed and talked about as a legal burden that has to be resolved. If you want to see more apps or websites being graded, please submit suggestions via feedback form or HN comments.
Share cardActual performance
8points
5comments
Made the leaderboard
Launch Intel predictions
Analyze your own launch →Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released62%62% 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 · Strong signals: apps · Missing: mobile apps, ios, personal48%48% 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, podcasting46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: mac, apps · Missing: agents, macos, agent45%45% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto18%18% predicted probability of success on BetaList, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Correct prediction on native model
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