aiready-best-practices

Guidelines for writing AI-friendly code. Detects semantic duplicates, context fragmentation, naming inconsistencies. Use when writing new code, reviewing PRs, refactoring for AI adoption, or debugging AI assistant confusion. Helps minimize context waste and improve AI comprehension.

AIReady Best Practices

Guidelines for writing AI-friendly codebases that AI coding assistants can understand and maintain effectively. Based on analysis of thousands of repositories and common AI model failure patterns. Covers pattern detection, AI signal clarity, context optimization, change amplification, agent grounding, consistency checking, documentation, testability, and dependency management.

Core Capabilities

AI Signal Clarity: Principles for reducing ambiguity in code.
Context Optimization: Strategies for minimizing context window waste.
Pattern Detection: Identifying and consolidating semantic duplicates.
Consistency: Maintaining uniform naming and architectural patterns.
Health Assessment: Using aiready scan for proactive codebase auditing.

Usage for Agents

Full instructions are available in AGENTS.md.

[!NOTE] AGENTS.md is automatically generated from individual rules in the rules/ directory. Contributors should modify the source rules rather than the compiled file.

Quick Commands (via npx)

Measure Health: npx @aiready/cli scan .
Check Consistency: npx @aiready/cli consistency .
Detect Duplicates: npx @aiready/cli patterns .