Anonymous Instagram story viewer with no ads or tracking

Hacker News

Built https://www.spybroski.com/ after getting frustrated with existing Instagram story viewers that were either broken, ad-heavy, or required sketchy permissions. Technical approach: Server-side requests to avoid CORS issues No user data storage or tracking Clean vanilla JS frontend, minimal dependencies Download functionality using blob URLs Why this exists: Instagram's web interface requires login to view stories, but sometimes you just want to check something quickly without the social graph implications. existing tools were either unreliable or loaded with ads and trackers. Current stats: ~10k users organically No monetization yet (considering premium features) Hosting costs are minimal thanks to efficient caching The technical challenge was mostly around Instagram's API changes and rate limiting. had to implement some clever request batching to stay under their radar. Happy to discuss the technical implementation or answer questions about building tools in this space. also curious if others have tackled similar social media API challenges. Code isn't open source yet but considering it if there's interest.

Visit product View on Hacker NewsJun 23, 2025

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

86%86% 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: user, using, code · Missing: mac, agents, macos

66%66% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: users · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Strong signals: host, interface, efficient · Missing: plus, platform, intuitive

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, open source, existing · Missing: https docs, excited, just released

39%39% 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 · 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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