Show ponytail measured impact as a scoreboard: less code, less cost, more speed, from the benchmark medians. One-shot display.
npx skills add https://github.com/DietrichGebert/ponytail --skill ponytail-gain
Display this scoreboard when invoked. One-shot: do NOT change mode, write flag
files, or persist anything.
The figures are the published benchmark medians (5 everyday tasks: email
validator, debounce, CSV sum, countdown timer, rate limiter; three models:
Haiku, Sonnet, Opus). They are measured, not computed from the current repo.
Source: benchmarks/ and the README.
Render plain ASCII bars. The bar length shows the measured range; the label
carries the exact figure:
ponytail gain benchmark median · 5 tasks · 3 models
Lines of code no-skill ████████████████████ 100%
ponytail ██▌················· 6–20% ▼ 80–94%
Cost no-skill ████████████████████ 100%
ponytail █████▌·············· 23–53% ▼ 47–77%
Speed ponytail ▸ 3–6× faster
This repo: /ponytail-debt (shortcuts you deferred)
/ponytail-audit (what's still cuttable)
These are benchmark medians, not this repo. NEVER print a per-repo savings
number ("you saved X lines/tokens here"): the unbuilt version was never
written, so there is no real baseline to subtract from in a live repo. The
only real per-repo figures come from /ponytail-debt (a counted ledger), and
this card points there instead of inventing one.
One-shot display. Edits nothing, changes no mode.
"stop ponytail" or "normal mode": revert.
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Write docstrings for PyTorch functions and methods following PyTorch conventions. Use when writing or updating docstrings in PyTorch code.
Take dietrichgebert/ponytail-gain from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.