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Live, interactive architecture diagrams for open-source projects
Hacker NewsLive, interactive architecture diagrams for open-source projects
We auto-generate live interactive architecture diagrams from codebases. We've published free pages for NanoClaw, NemoClaw, Flask, Axios, Zod, Hono, and Pyramid - updated as the code evolves, no login required. The NanoClaw vs NemoClaw comparison is interesting - ~15 source files vs an enterprise sandbox wrapper around OpenClaw. Would love feedback on which repos to add next.
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Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: openclaw, code, open · Missing: mac, agents, macos73%73% 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.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released53%53% 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 HackersFits the IH revenue-focused audience · Strong signals: ios · Missing: supports, reddit linkedin, podcasting53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: ios · Missing: mobile apps, personal, entrepreneurs35%35% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue14%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, crypto11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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