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DECK0 – a ~17 KB CLI that serves a Markdown file as a slide deck

Hacker News

DECK0 – a ~17 KB CLI that serves a Markdown file as a slide deck

Tired of PowerPoint overhead and reveal.js scaffolding for quick technical talks. DECK0 takes a plain .md file and serves it as a slide deck via a local Node HTTP server. `npx @tforster/deck0 your-talk.md` Slides split on ## headings. Syntax highlighting, Mermaid diagrams, GFM tables, and callouts. Also accepts a remote URL instead of a local file. No build step, no config, no framework. You can demo it with `npx @tforster/deck0 https://raw.githubusercontent.com/tforster/deck0/main/demo/p... `

Visit productView on Hacker NewsMar 25, 2026
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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, plain · Missing: mac, agents, macos
73%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: ide · Missing: https docs, excited, just released
52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
17%17% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
14%14% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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