@vikingmute: Found that Ponytail and Codex are a perfect match https://github.com/DietrichGebert/ponytail… GPT is addicted to writing fallback code; without clear instructions, it always writes a ton of defensive code, which is heartbreaking to read. Its core philosophy is “The…

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Summary

Ponytail is an AI agent skill that significantly reduces over-engineering by forcing the agent to first check whether new code is needed, claiming to reduce code volume by 80-94% and cost by 42-75%. The author recommends using it with Codex and has open-sourced it on GitHub.

Found that Ponytail and Codex are a perfect match https://github.com/DietrichGebert/ponytail… GPT is addicted to writing fallback code; without clear instructions, it always writes a ton of defensive code, which is heartbreaking to read. Its core philosophy is “The best code is the code you never wrote.” By forcing the agent to first check whether new code is really needed, it greatly reduces over-engineering. Official data says: 80-94% less code, 42-75% less cost, and 3-6× faster than a no-skill agent. Today I'll install it and see if it works well. It already has a lot of stars.
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Ponytail

He says nothing. He writes one line. It works.

80-94% less code · 3-6× faster · 42-75% cheaper Per-task code, latency, and cost on the Claude API, not your plan’s quota. Median across Haiku, Sonnet, and Opus (10 runs for code and latency, 30 for the re-verified cost). Results vary by model and prompt: the ruleset re-injects each turn, so on a short prompt or a terse reasoning model that overhead can outweigh the savings. Reproduce it yourself.

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This article introduces a GitHub project named ponytail, which acts as a plugin for Codex, forcing the AI to assess whether code truly needs to be written before coding, thereby reducing 90% of useless code, lowering token consumption, and improving code quality.

DietrichGebert/ponytail

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Ponytail is a developer tool that integrates with AI agents to significantly reduce code output, cost, and execution time while maintaining safety, as demonstrated in benchmarks with Claude Code.

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