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OpenCode plugin for interactive plan annotation

Hacker News

OpenCode plugin for interactive plan annotation

I found myself constantly wanting to annotate verbose plans. I've also wanted to copy and share plans on occasion - gathering others' feedback. So I built this. Sharing plans is private and was inspired by the recently featured textarea.my Markup your plans like a google doc. Plannotator works via hooks and therefore it's fully integrated with the OpenCode planning mode capability. If you're on desktop, play here: https://share.plannotator.ai/ Or watch a video demo: https://www.youtube.com/watch?v=_N7uo0EFI-U https://github.com/backnotprop/plannotator

Visit productView on Hacker NewsDec 31, 2025
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, code, open · Missing: mac, agents, macos
65%65% 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.
TrustMRRFits verified-revenue profile · Strong signals: video, google · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
51%51% predicted probability of success on AppSumo, 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
46%46% 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 · Strong signals: active · Missing: arr, mrr, revenue
14%14% 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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