ponytail-improved — repository deleted, archived audit

Quick Facts

About ponytail-improved

Ponytail He says nothing. He writes one line. It works. Install  ·  Before / after  ·  How it works  ·  Numbers  ·  Commands  ·  FAQ You know him. Long ponytail. Oval glasses. Been at the company longer than the version control. You show him fifty lines; he says nothing and replaces them with one. Ponytail puts him inside your AI agent.

Compatible Skills

These tools work well together with ponytail-improved for enhanced workflows:

• ponytail — semantic(0.71)+complementary+rare_topics+same_lang+shared_platform (70%)
• openclaw-optimization-guide — semantic(0.17)+complementary+rare_topics+same_lang+similar_pop+shared_platform (60%)
• cesiumjs-skills — semantic(0.28)+complementary+same_lang+similar_pop+shared_platform (60%)

ponytail-improved alternative? Top 6 similar tools

Looking for a ponytail-improved alternative? If you're comparing ponytail-improved with other claude skill tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.

• ponytail-lite by ilindaniel · ⭐ 229

  Stop agents from over-engineering. Inspired by Ponytail, but without the plugin madness. Just one AGENTS.md fi

• Chisle by JayPokale · ⭐ 710

  Cut your AI coding agent's token bill on three axes: terse prose, YAGNI-first code, and tool-output compressio

• skills by wondelai · ⭐ 2.6k

  Wondel.ai Agent Skills — Business, Marketing, UX & Coding Frameworks from Bestselling Books. 50 skills + 12 gu

• claude-code-workflows by shinpr · ⭐ 709

  Development workflows for Claude Code that keep broad exploration focused on the outcome you approved.

• claude-skills by OneWave-AI · ⭐ 355

  200+ production-ready Claude Code skills for sales, marketing, design, engineering, and AI agent architecture.

• prompt-architect by ckelsoe · ⭐ 329

  Claude Code skill that transforms vague prompts into structured, expert-level prompts using 7 research-backed

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How this security grade is produced

Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.

The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.

Sources & who's responsible:

• SlowMist agent-security taxonomy
• Liu et al., An Empirical Study of Agent Skill Security (2026)
• Our census dataset (DOI 10.5281/zenodo.21292799) · Hugging Face mirror
• How we grade: all 42 rules, the source tiers and known limits
• Full methodology & who runs this