Code Principles¶
Engineering guidance that adapts to the project¶
A self-contained, language-agnostic knowledge base and policy system for AI coding agents — presented here as a browsable engineering handbook.
Principles¶
Canonical engineering ideas with explicit applicability, rejected interpretations, trade-offs, conflicts, examples, and AI guidance.
Core Skills¶
Decision procedures that combine principles into practical modes for clarity, abstraction, testing, compatibility, reliability, performance, and more.
Project profiles¶
Start from what you are building: application, library, service, worker, pipeline, plugin, prototype, CLI, real-time system, infrastructure tool, and more.
Technology refinements¶
See how generic policy is refined for JavaScript, TypeScript, Python, PHP, Go, C++, React, Next.js, Vue, Nuxt, Angular, Symfony, and Drupal.
How the policy model works¶
The website is a generated view
Canonical YAML and normative Markdown in the repository remain authoritative. This site is rebuilt from those sources and is never an independent source of policy.
Learn by example¶
The repository includes executable evaluation scenarios that test profile selection, modifiers, language and framework refinements, conflict decisions, and forbidden overengineering. They are useful both as tests and as worked examples of the policy model.
Reference¶
For the complete system contracts and architecture, continue with the Specification, Architecture, Knowledge Model, and Conflict Resolution.