ponytail-debt
An AI agent skill from DietrichGebert/ponytail, scored 57 out of 100 by code.
Code score by group
It loses the most points in Procedure (15), the group that checks whether the steps are numbered, read the context first and say what to do when something fails.
What the author says it does
List every `shortcut:` comment (and older `ponytail:` ones) as a debt ledger. One-shot report, changes nothing. Use for "ponytail debt", "what did ponytail defer", "list the shortcuts", /ponytail-debt.
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- DietrichGebert/ponytail
- Folder
- skills/ponytail-debt
- License
- MIT
- GitHub stars
- 189,409
- SKILL.md lines
- 45
- Other files
- 0
Add ponytail-debt to your agent
npx skills add DietrichGebert/ponytail --skill ponytail-debt
The command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
More skills from DietrichGebert/ponytail
-
ponytail-review
Quality review of a change: is the logic right, is it safe, does it hold under real load, is risky code tested, is it fast enough, and is every line needed. Reads the connected co…
65C -
ponytail
Lazy senior dev mode: the smallest change that fully solves the task, and a reply a busy human understands in one read. Use on any coding task (writing, fixing, refactoring, revie…
59C -
ponytail-audit
Quality audit of a whole repo: bugs, security holes, what breaks under real load, risky code without tests, slow paths, and what to delete, merge or split. Ranked, each finding ex…
59C -
ponytail-gain
Show ponytail's measured savings (code, cost, speed) from the benchmark. One-shot display. Use for /ponytail-gain, "what does ponytail save", "ponytail impact".
50D -
ponytail-help
Quick reference for ponytail levels, skills and commands. One-shot display. Use for /ponytail-help, "ponytail help", "how do I use ponytail".
50D
All skills in DietrichGebert/ponytail
Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.