Ponytail 技能修正自身基准，回应质疑并推动技能评估标准
原标题：Ponytail Agent Skill Corrects Its Own Benchmark After Contributor Challenge
AI 摘要
开源技能 Ponytail 通过注入规则集，指导 AI 编码代理遵循 YAGNI 原则，避免过度工程化，自发布以来已获超 8.2 万 GitHub 星标。其原始基准声称减少 80-94% 代码，但遭质疑后作者重建基准，公开修正为平均减少约 54% 代码，并补充了行为测试框架。该事件凸显了 AI 技能缺乏评估标准的问题，Ponytail 的回应被视为更持久的贡献。
正文节选
Ponytail, an open-source skill that instructs AI coding agents to behave like "the laziest senior dev in the room," has accumulated over 82,000 GitHub stars since its June 12 release, making it one of the fastest-growing repositories of the summer. The project addresses a complaint nearly every coding agent user shares: agents over-build. Ask for a date picker, and the agent installs a library, writes a wrapper component, adds a stylesheet, and starts a discussion about time zones. Ponytail's an