Ponytail He says nothing. He writes one line. It works. 54% less code (up to 94%) · 20% cheaper · 27% faster · 100% safe Measured on real Claude Code sessions editing a real open source repo (FastAPI + React), against the same agent with no skill. 54% is the mean across 12 feature tasks (Haiku 4.5, n=4); it reaches 94% where an agent over builds (a date picker) and is near zero where the code is already minimal. ponytail keeps every safety guard while a bare "write one liners" prompt drops one. (The earlier single shot benchmark reported 80 94% as a flat figure; against a fair agentic baseline that is the per task ceiling, not the average.) Full writeup · reproduce it . Español · 한국어 You know him. Long ponytail. Oval glasses. Has been at the company longer than the version control. You show him fifty lines; he looks at them, says nothing, and replaces them with one. Ponytail puts him inside your AI agent. Before / after You ask for a date picker. Your agent installs flatpickr, writes a wrapper component, adds a stylesheet, and starts a discussion about timezones. With ponytail: [安装/使用命令见下方] More survivors in examples/. Numbers The honest measurement is a real agent doing real work: a headless Claude Code session editing tiangolo's full stack fastapi template (a real FastAPI + React repo), scored on the git diff it leaves behind. Twelve feature tickets, the same agent with and without the skill, n=4, Haiku 4.5. vs no skill baseline LOC tokens cost time safe : : : : : ponytail 54% 22% 20% 27% 100% caveman (terse prose control) 20% +7% +3% +2% 100% "YAGNI + one liners" prompt 33% 14% 21% 30% 95% ponytail is the only arm that cuts every metric, and the only one that stays fully safe while doing it. The cut is biggest where there is a real over build trap (date picker 404 to 23 lines, color picker 287 to 23, because it reaches for a native instead of a component) and near zero on code that is already minimal. Full method, per task table