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Termstage – Animated terminal SVGs from YAML, no screen recording

Hacker News

Termstage – Animated terminal SVGs from YAML, no screen recording

I built termstage because I was tired of screen-recording CLI demos and ending up with heavy GIFs that look bad in READMEs. termstage lets you describe a terminal session in YAML and renders it as an animated SVG — lightweight, crisp at any size, embeds directly in GitHub READMEs. Example: steps: - cmd: "notes list" output: "#1 Fix the login bug" - cmd: "notes done 1" output: "Marked #1 as done" Run `termstage render demo.yaml --animated` and you get an SVG you can drop anywhere. Install: pipx install termstage GitHub: https://github.com/saikatkumardey/termstage PyPI: https://pypi.org/project/termstage/

Visit product View on Hacker NewsFeb 26, 2026

Actual performance

2points

4comments

Did not reach leaderboard

Launch Intel predictions

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

79%79% 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.

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

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

35%35% 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

35%35% 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.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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