
Ponytail Github answers a question every senior engineer has been asking since the AI-coding wave began: why does my agent write so much, when the standard library, the platform, or an installed dependency already covers it? The project packages a single decision-making persona — the laziest senior developer in the room — into a portable skill that any of the 14 supported coding agents can load on every prompt.
The skill is intentionally compact. The decision ladder has only six rungs: skip if the feature is not needed, reach for the standard library, reach for the platform, reach for an installed dependency, prefer a single-line implementation, and only then write the minimum amount of custom code that actually works. Critically, validation, error handling, security and accessibility are non-negotiable and are never trimmed. The two Node.js hooks that ship with the repository are used only by Claude Code and Codex to enable always-on activation; on every other agent the skill is delivered as a system prompt and stays entirely native.
The benchmark discipline is what makes Ponytail Github credible. Across twelve real feature tickets on a real FastAPI plus React codebase, Claude Code 4.5 with Ponytail Github produced 54% fewer lines, 22% fewer tokens, 20% lower cost and 27% faster runs while keeping 100% of its safety guards — beating both the no-skill baseline and competing terse-prose alternatives that lose either safety or token efficiency. Over-build traps such as date pickers and color pickers see reductions up to 94%. The full results, per-task tables, promptfoo configuration and reproduction instructions live in the benchmarks/ directory, and the entire project is MIT licensed.
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