Fi

Find dead links in your source files

Hacker News

Find dead links in your source files

Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
62%62% 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.
BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto
54%54% predicted probability of success on BetaList, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
51%51% 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 · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

LinkMedic
LinkMedic38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find dead links before your customers do.

Indie Hackers1analytics
R.
R.I.P.Link – Find dead links on the web57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

R.I.P.Link – Find dead links on the web

Hacker News4
Ca
Carl Jung's Seven Sermons to the Dead55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Carl Jung's Seven Sermons to the Dead

Hacker News1
I
I resurrected one of the top dead Show HNs53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I resurrected one of the top dead Show HNs

Hacker News8
I
I resurrected one of the top dead Show HNs53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I resurrected one of the top dead Show HNs

Hacker News5
Th
The Dead Sea Scrolls Visualized66%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Dead Sea Scrolls Visualized

Hacker News1
Vi
View your dead(404s) links in your stackoverflow answers60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

View your dead(404s) links in your stackoverflow answers

Hacker News2
A
A dead code killer for Erlang75%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A dead code killer for Erlang

Hacker News103
Ma
Mailto-links are dead. Long live mailto.id55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mailto-links are dead. Long live mailto.id

Hacker News14
Th
The Dead Web62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The Dead Web

Hacker News2