Ponytail is an always-on ruleset and plugin for AI coding agents (Claude, Codex, Gemini, Copilot, etc.) that enforces a step-by-step “ladder” to include only necessary code. Benchmarks show 80–94% less code, 3–6× faster responses, and 42–75% lower cost by preferring built-ins and one-liner solutions before adding dependencies.

This project packages four principles—Think Before Coding, Simplicity First, Surgical Changes, and Goal-Driven Execution—into a Claude Code plugin or CLAUDE.md file to curb LLM code pitfalls like overengineering and hidden assumptions. It enforces explicit reasoning, minimal edits, and test-driven success criteria to produce cleaner, more accurate AI-generated code.

This article explains how to set up a Telegram bot to work with Claude Code using an MCP server. It covers the steps from creating a bot with BotFather to configuring the server and pairing it with Claude for direct messaging. Key commands and configurations are detailed for effective integration.

This guide explains how to set up a Telegram bot with Claude Code using an MCP server. It covers creating a bot through BotFather, installing the necessary plugin, and the steps to configure and pair the bot with your Claude session.

This article explains how the Claude plugin generates distinctive, production-grade frontend designs using polished code. It emphasizes avoiding generic styles by establishing a design framework that considers purpose, audience, and aesthetics. Users can activate this feature by simply asking Claude to build specific interfaces.

This plugin embeds OpenAI Codex into your Claude Code workflow, letting you run standard, adversarial, or rescue reviews without switching tools. Install via Node.js, authenticate with your ChatGPT subscription or API key, then use /codex:review, /codex:adversarial-review, and /codex:rescue alongside status commands.

Feedback is valued and taken seriously, with an emphasis on user input for improvements. For detailed information on available qualifiers, users are directed to the documentation. An error occurred while loading the page, prompting a reload.

The Compounding Engineering plugin enhances development workflows by systematically improving the planning, execution, and review stages of coding. It leverages AI to create comprehensive issues, manage isolated tasks, and conduct thorough code reviews, ensuring that each unit of engineering work makes future tasks easier. By documenting processes and refining quality, this tool aims to build a more efficient development system over time.