Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.
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Automated security scan — not a certification.
# Add to your Claude Code skills
git clone https://github.com/DietrichGebert/ponytailGuides for using ai agents skills like ponytail.
Last scanned: 6/12/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-06-12T08:25:45.029Z",
"npmAuditRan": true,
"pipAuditRan": true,
"promptInjectionRan": true
}See how ponytail compares with popular alternatives.
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.
Two things the chart does not show: in a blind comparison, Ponytail 5's replies beat the previous Ponytail's 110 to 67. And on the six security tasks (SQL injection, path traversal, forged tokens, rate limiting, malformed CSV rows, caching) it passed all 30 runs: less code, no less safe. Method, per-task tables and limits: benchmarks/results/2026-10-07-agentic.md.
The rule was never "fewest tokens." It is: write only what the task needs, and never cut validation, error handling, security, or accessibility. The code ends up small because it is necessary, not golfed. Lower cost and latency are a side effect.
You ask for a date picker. Without Ponytail, the agent installs a date picker library or builds a whole calendar by hand: 335 lines. Ponytail 5 first looks at what is already there: the repo has an Input component, and every browser has a date picker. It puts the two together. 10 lines.
More survivors in examples/.
/ponytail-review used to look only for code to cut. Now it reviews like the senior dev who gets paged when it breaks: it reads the code your change touches, not just the diff, and checks bugs, security, real load, missing tests, speed, and what to cut. Each finding says what the code does, what goes wrong, how to fix it, and what happens if you don't.
/ponytail-audit runs the same checks on the whole repo. It maps the code first: entry points, how data moves, what load the project expects. Then it ranks what it finds and tells you what to fix first. The old audit only listed what to delete.
In Claude Code, ponytail now shows a band above the prompt: what the current task costs, how many tokens and how much agent time it used, how often it reused existing code instead of writing new code, and whether the tests passed after the last change. Its buttons switch the level, run /ponytail-review or /ponytail-audit, copy the task as Markdown, and fold the band into one line. Don't want it? /ponytail band hides it, the same command brings it back. Needs Claude Code 2.1.290 or later, in the terminal or the desktop app. It does not show in the VS Code chat panel, cloud sessions or claude -p.
Board opens a local page with every task across your projects: cost, agent time and tokens over time, every session with its tests, and the days you worked. By default, everything stays on your machine, in ~/.config/ponytail/band/. /ponytail band import adds your past Claude Code sessions to it, with their cost, agent time and tokens.
The ladder runs after it understands the problem, not instead of it: it reads the code the change touches and traces the real flow before picking a rung. Lazy about the solution, never about reading.
Lazy, not negligent: trust-boundary validation, data-loss handling, security, and accessibility are never on the chopping block.
Logic with a branch, a loop, a parser, money or security leaves one small test behind. Every reply ends with what was skipped or not checked and any risk you should know.
Ponytail is one prompt: skills/ponytail/SKILL.md. The compact version, for agents that read a rules file, is [
ponytail is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by DietrichGebert. Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote. It has 175,698 GitHub stars.
Yes. ponytail passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/DietrichGebert/ponytail" and add it to your Claude Code skills directory (see the Installation section above).
ponytail is primarily written in JavaScript. It is open-source under DietrichGebert on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh ponytail against similar tools.
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