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 examines how AGENTS.md files impact AI coding agents, showing that well-structured agent docs can boost code quality by up to 15% while poorly designed ones can hurt performance. It outlines seven patterns that work—like progressive disclosure, step-by-step workflows, decision tables, real-code examples, and pairing “don’ts” with “dos”—and warns against overexploration from excessive context or warnings.