$ loading_
Provide coding rules and engineering guidance for AI coding agents.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "agent-rules-books" yet — see the docs or source repo.
Please refactor this Python code following the clean code, refactoring, and clear architecture principles emphasized in agent-rules-books, and explain what you improved.
Returns cleaner, more maintainable code with a brief refactoring explanation.
Based on the rules in agent-rules-books, create a development guideline for this new feature, focusing on naming, module boundaries, error handling, and testability.
Outputs an actionable checklist of development rules to keep implementation consistent.
Please review this AI-generated TypeScript code using the agent-rules-books approach, identify violations of clean code or architecture principles, and suggest fixes.
Provides a structured review with issues found and recommended improvements.
Developers using Codex, Cursor, or Claude Code can use these rules to standardize coding style and implementation habits, reducing differences across agents.
Before asking AI to generate or modify code, teams can provide these rules so implementations better align with clean code, refactoring, DDD, and clean architecture practices.
When reviewing AI-generated code or refactoring legacy code, this skill can serve as a consistent review baseline to spot structural and maintainability issues.
It is a set of rules or skill instructions for AI coding agents, intended for Codex, Cursor, and Claude Code. It is inspired by programming books such as Clean Code, Refactoring, DDD, Clean Architecture, and DDIA.
The provided description explicitly mentions Codex, Cursor, and Claude Code. For compatibility with other agents, see the source repository.
The provided information does not include installation or integration steps. For exact usage, file structure, or prerequisites, see the source repository.
Auto-detect tech stacks and generate consistent coding rules for AI assistants.
Learn provider-neutral agent design best practices across coding agent environments.
Helps AI coding assistants produce production-grade ROS robotics software and tests.
Standardize planning, memory, verification, and review across AI coding agents.
Access reusable skills, commands, and scripts for coding agents and teamwork.
Give AI coding agents design direction, UI code guidance, and critique.