URL Unshortener Pro – Reveal redirect chains and trackers from URLs

Hacker News

Hey HN I recently built URL Unshortener Pro, a free Chrome extension that: Expands shortened or obfuscated URLs (like bit.ly, t.co, etc) Reveals the entire redirect chain (handles HTTP, meta-refresh, JavaScript-based redirects) Flags known tracking domains Highlights and removes tracking parameters (utm_source, fbclid, etc) Works fast with smart caching 100% privacy-focused, with no tracking, ads, or external analytics. I built it out of personal frustration with opaque, tracking-heavy links on social media and news sites. Chrome Web Store link ( https://chromewebstore.google.com/detail/url-unshortener-pro... ) Would love any feedback, feature suggestions, or bug reports. Thanks!

Visit product View on Hacker NewsJun 24, 2025

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1points

Did not reach leaderboard

Launch Intel predictions

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

77%77% 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, new · Missing: mac, agents, macos

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

29%29% 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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: smart · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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