Web Inspector – An extension for Chrome to easily inspect the Web

Hacker News

I created this extension because many people (mainly designers) asked me before if they could get the font family used on a certain website, or if it was possible to get the URL for a background image, among others. Usually to solve this problem I would use the developer tools provided by the browser and give them the information they needed. The problem is that I couldn't tell them how to get this information because the developer tools are not intuitive for regular users, so I had to keep doing it all the time. Since I was curious to know how Chrome extensions work I decided to create Web Inspector and now I'm curious to know what people think of it. Give it a try if you have time please. If you are a developer and you are curious about the implementation, on the extension page you will also find a URL for the Github project. Thank you for your time ;) https://chrome.google.com/webstore/detail/web-inspector/enibedkmbpadhfofcgjcphipflcbpelf?utm_source=chrome-ntp-icon

Visit product View on Hacker NewsJul 16, 2014

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

80%80% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: google, user · Missing: mac, agents, macos

69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: google, users · Missing: mobile apps, ios, personal

37%37% 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, io · Missing: https docs, excited, just released

34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

13%13% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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