Markdown Viewer and Editor

Hacker News

I built an online viewer and editor for .md files where the file stays on your machine. Free to use and code is available under MIT License here: https://github.com/hattray/markdown-editor You can also install it as a Chrome/Edge app so that it works for files on your desktop by double-clicking. Supports standard .md files with formatting, syntax-highlighting for code, table of contents, Mermaid diagrams, LaTeX via KaTex. Also supports exporting to .html, .pdf and .png. Please give it a try and share your feedback for improvements.

Visit product View on Hacker NewsAug 31, 2026

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Actual performance

34points

20comments

Made the leaderboard

Launch Intel predictions

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

78%78% 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.

Hacker NewsStrong engagement from HN community · Missing: https docs, excited, just released

57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, code · Missing: agents, macos, agent

47%47% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

45%45% 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

23%23% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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