A
A drop-anywhere C++17 REPL (like pry/pdb)
Hacker NewsA drop-anywhere C++17 REPL (like pry/pdb)
Share cardActual performance
6points
Did not reach leaderboard
Launch Intel predictions
Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos76%76% 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.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto49%49% predicted probability of success on BetaList, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive36%36% 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, revenue23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting7%7% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Incorrect prediction on native model
Similar products
Dr
Drop-in caching for R functions42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Drop-in caching for R functions
Hacker News1Dr
Drop-in sticky headers and footers for UICollectionView44%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Drop-in sticky headers and footers for UICollectionView
Hacker News1DROP22%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
DROP — Find your next users.
Indie Hackerscommitment-full-timeWe
WeChat-like QRCode reader, drop-in version52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
WeChat-like QRCode reader, drop-in version
Hacker News3Ki
Kinda like posterous?43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Kinda like posterous?
Hacker News53"I
"I'm Like..." - Texting With More Feeling47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
"I'm Like..." - Texting With More Feeling
Hacker News1Su
Succinctly manipulate dom-like trees from java50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Succinctly manipulate dom-like trees from java
Hacker News2Sp
Spritz like bookmarklet37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Spritz like bookmarklet
Hacker News8En
Endorfyn: Everything You Like59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
Endorfyn: Everything You Like
Hacker News14Mo
More Like This Bookmarklet33%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.
More Like This Bookmarklet
Hacker News20