TS Package to Convert Final Cut, Premiere, Resolve and OpenTimelineIO

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A small TypeScript library that imports and exports FCPXML, FCP7/xmeml, and OTIO, plus a CLI. You can use it for reading, writing, and converting video-editing timelines with frame-accurate timing. e.g: npx @chatoctopus/timeline convert edit.fcpxml --to otio Features: - Format conversion - Import/parse/Export - Give it clip paths (+ optional trims); it probes them with FFprobe and assembles a timeline - Programmatic timeline construction Caveats: it moves the structure of an edit (cuts, clips, timing, media) but not effects, color, titles, or audio mixing. Transitions only survive into OTIO (they flatten to cuts in FCPXML/xmeml), and on the Final Cut side, it reads Resolve-style asset-clip timelines rather than FCP's compound/multicam/title containers. Contributions: Looking for some real-world test files of FCP, Premiere, and Resolve to find and fix any remaining bugs.

Visit product View on Hacker NewsJun 24, 2026

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

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

37%37% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

29%29% predicted probability of success on BetaList, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 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

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Correct prediction on native model

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