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Defuddle, an HTML-to-Markdown alternative to Readability

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Defuddle, an HTML-to-Markdown alternative to Readability

Defuddle is an open-source JS library I built to parse and extract the main content and metadata from web pages. It can also return the content as Markdown. I built Defuddle while working on Obsidian Web Clipper[1] (also MIT-licensed) because Mozilla's Readability[2] appears to be mostly abandoned, and didn't work well for many sites. It's still very much a work in progress, but I thought I'd share it today, in light of the announcement that Mozilla is shutting down Pocket. This library could be helpful to anyone building a read-it-later app. Defuddle is also available as a CLI: https://github.com/kepano/defuddle-cli [1] https://github.com/obsidianmd/obsidian-clipper [2] https://github.com/mozilla/readability

Visit productView on Hacker NewsMay 22, 2025
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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released
73%73% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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.

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