ponytail  by DietrichGebert

AI agent code generation optimized for minimal output

Created 3 days ago

New!

3,732 stars

Top 12.8% on SourcePulse

GitHubView on GitHub
Project Summary

This project provides an AI agent persona designed to minimize code generation, promoting extreme efficiency and simplicity. Targeting developers who leverage AI for coding tasks, it aims to drastically reduce code volume, execution time, and cost by prioritizing existing solutions and minimal viable code.

How It Works

Ponytail operates on a strict, hierarchical decision-making process before generating any code. It first checks if the functionality is necessary (YAGNI), then if it exists in the standard library, native platform features, or installed dependencies. Only if these options are exhausted does it resort to writing a single line of code or the absolute minimum required to function. This "lazy, not negligent" approach ensures core aspects like security, validation, and accessibility are maintained while maximizing code reduction.

Quick Start & Requirements

Installation varies by AI agent framework:

  • Claude Code: /plugin marketplace add DietrichGebert/ponytail
  • Codex: codex plugin marketplace add DietrichGebert/ponytail or install via Open /plugins.
  • Pi agent harness: pi install git:github.com/DietrichGebert/ponytail
  • OpenCode: Add "plugin": ["./.opencode/plugins/ponytail.mjs"] to opencode.json.
  • Other agents (Cursor, Windsurf, Cline, Copilot, Aider, Kiro): Copy specific rule files from the repository to the agent's configuration directory. No default prerequisites beyond integration with supported AI agent platforms are explicitly listed.

Highlighted Details

  • Achieves 80-94% less code, 3-6x faster execution, and 47-77% lower cost compared to unconstrained agents, based on median results across multiple models and runs.
  • Employs the philosophy: "The best code is the code you never wrote."
  • Code shortcuts are explicitly marked with ponytail: comments, indicating potential upgrade paths.
  • Includes commands like /ponytail-review to identify and suggest code deletions within diffs.

Maintenance & Community

No specific details regarding maintainers, sponsorships, or community channels (e.g., Discord, Slack) are provided in the documentation. Development includes scripts to ensure alignment of rule text copies across different agent configurations.

Licensing & Compatibility

The project is released under the MIT license, described as "The shortest license that works," suggesting broad compatibility for commercial use and integration.

Limitations & Caveats

The agent's core philosophy may lead to resistance or slow generation if users insist on complex, multi-line solutions that Ponytail deems unnecessary. Claims of "Zero bugs, zero CVEs, 100% uptime" are strong assertions requiring independent verification. Effectiveness is dependent on the underlying AI model's capabilities.

Health Check
Last Commit

18 hours ago

Responsiveness

Inactive

Pull Requests (30d)
16
Issues (30d)
6
Star History
4,183 stars in the last 3 days

Explore Similar Projects

Starred by Zhiqiang Xie Zhiqiang Xie(Coauthor of SGLang), Eric Zhu Eric Zhu(Coauthor of AutoGen; Research Scientist at Microsoft Research), and
3 more.

Trace by microsoft

0%
742
AutoDiff-like tool for end-to-end AI agent training with general feedback
Created 2 years ago
Updated 6 months ago
Starred by Alex Yu Alex Yu(Research Scientist at OpenAI; Cofounder of Luma AI), Will Brown Will Brown(Research Lead at Prime Intellect), and
7 more.

avante.nvim by yetone

0.1%
18k
Neovim plugin emulating Cursor AI IDE for AI-driven code assistance
Created 1 year ago
Updated 23 hours ago
Starred by Shizhe Diao Shizhe Diao(Author of LMFlow; Research Scientist at NVIDIA), Jeff Hammerbacher Jeff Hammerbacher(Cofounder of Cloudera), and
4 more.

kilocode by Kilo-Org

0.9%
20k
VS Code AI agent for coding tasks
Created 1 year ago
Updated 10 hours ago
Feedback? Help us improve.