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ponytail vs taste-skill

Agent Skills rivals. Both tagged agent-skills, ai-agents, claude-code. Six rounds of real GitHub data, an AI referee, and the crowd picks a side.

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DietrichGebert/ponytail: 188,787 stars, JavaScript. Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.
Leonxlnx/taste-skill: 113,255 stars, JavaScript. Agent skills that give coding agents taste: art direction, reference images and a browser check instead of generic AI pages

ponytail vs taste-skill: tale of the tape

GitHub data as of November 11, 2026

ponytail has 1.7 times as many GitHub stars as taste-skill (188,787 vs 113,255). In the last 6 days, ponytail gained more stars: +3,863 (+2.1%) against +2,876 (+2.6%) for taste-skill. ponytail saw more development in the last 52 weeks with 361 commits, against 269 for taste-skill. taste-skill is the older project (created February 2026), ponytail started in June 2026. Both are written mainly in JavaScript.

DietrichGebert/ponytailLeonxlnx/taste-skill
Stars188,787113,255
Stars gained, last 6 days+3,863+2,876
Growth, last 6 days+2.1%+2.6%
Avg. stars per day since creation1,242427
Forks10,4937,623
Commits, last 52 weeks361269
Open issues2115
Best Repocharts rank today#2 in Dev Tools#13 in JavaScript
LanguageJavaScriptJavaScript
LicenseMITMIT
CreatedJun 12, 2026Feb 19, 2026
Last pushOct 29, 2026Nov 8, 2026

Quick answers

Which is more popular, ponytail or taste-skill?

ponytail has 1.7 times as many GitHub stars as taste-skill (188,787 vs 113,255) (Repocharts data as of November 11, 2026).

Which is growing faster, ponytail or taste-skill?

In the last 6 days, ponytail gained more stars: +3,863 (+2.1%) against +2,876 (+2.6%) for taste-skill.

Which is more actively developed?

ponytail saw more development in the last 52 weeks with 361 commits, against 269 for taste-skill.

What languages are ponytail and taste-skill written in?

Both are written mainly in JavaScript.

How does RepoClash compare ponytail and taste-skill?

RepoClash scores both repositories in six rounds (popularity, momentum, activity, community, maintenance and freshness) from public GitHub data, adds an AI referee's verdict and lets developers vote for their favorite. Star counts are updated daily.

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