Implementing Patio11's "Dangerous Professional" as a Claude Code Plugin

Hacker News

Howdy HN! My recent dive into home ownership has brought me a whole new world to navigate w.r.t contractors, insurance claims, etc. I've been leaning heavily on the Dangerous Professional concept for clearer communication. It fits very cleanly as a plugin and has been very high-ROI for me. This is a community implementation. No affiliation with patio11, just a fan of his work. Repo: https://github.com/Tetra-Research/dangerous-professional-plu... Install: `npx skills add Tetra-Research/dangerous-professional-plugin`

Visit product View on Hacker NewsApr 28, 2026

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Actual performance

3points

1comments

Did not reach leaderboard

Launch Intel predictions

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

62%62% 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.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% 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

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

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

26%26% 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

18%18% 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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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