Docx-to-Markdown – layout-aware Word to Markdown converter

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Hey HN, I’m the author of the https://github.com/eigenpal/docx-editor , it’s an SDK that implements Word-compatible layout engine in Typescript. Today, we are releasing Word to markdown converter library. It’s open source and published under Apache 2.0 license. It uses our layout engine, so it can return accurate, per-page markdown blocks (with headers, footers, and image references). We also handle fonts (Google fonts as fallback) or let you pass your font files upfront for accurate content measurement. To our surprise, Word to per-page Markdown conversion is not a solved problem even in 2026! We initially faced this friction when preprocessing Word documents for agentic workflows. For our use case, it was important to represent per-page content in markdown. Initially, we ended up using LibreOffice sidecar to convert to PDF and then using .pdf -> .md library. This was not ideal given that LibreOffice sidecar that was sitting idle most of the time. This issue is addressed with docx-to-markdown library. it can be used directly in your Typescript ingestion pipeline. Try with your docs at https://www.docx-editor.dev/solutions/word-to-markdown . (if you catch any bugs please let us know in the comments / or file gh issues)

Visit product View on Hacker NewsSep 16, 2026

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

72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

46%46% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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