Th

The File You Didn't Know You Needed

Hacker News

The File You Didn't Know You Needed

To prevent against accidentally deleting the content of an important folder when doing rm -rf * create a file named -i . This way rm command will prompt before proceeding to delete everything. Here is how you create a file with that weird name: touch -- -i -i is the name of the file when * is expanded -i is passed to the rm command as a flag. You should probably do this in your ~ now.

Share card

Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
59%59% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released
46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
28%28% 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
20%20% 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
14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Li
ListToSQL, the extension you didn't know you needed23%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

ListToSQL, the extension you didn't know you needed

Hacker News1
jared.so
jared.so50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI that monitors convos & proactively jumps in when needed

Product Hunt+307Productivity
MoviePong
MoviePong21%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The actor–movie game you didn't know you needed

Product Hunt+261Movies
know
know
BetaList
Kn
Know when your ssl certs are about to expire58%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Know when your ssl certs are about to expire

Hacker News1
I
I wrote a guidebook on everything I know about applying to Y Combinator49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I wrote a guidebook on everything I know about applying to Y Combinator

Hacker News177
Wh
Who Will I Know There?38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Who Will I Know There?

Hacker News2
Sh
Show HN - Pixels: Know the pixels you see.57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Show HN - Pixels: Know the pixels you see.

Hacker News2
Ho
How Well You Know Me?38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

How Well You Know Me?

Hacker News4
Ho
How Well You Know Me?38%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

How Well You Know Me?

Hacker News2