Code Annotation Patterns

About

Code Annotation Patterns provides a standardized framework for embedding rich metadata directly into your source code to optimize AI-assisted development workflows. By using structured semantic tags like @ai-security or @ai-performance, developers can provide explicit context to Claude Code about architectural decisions, known limitations, and critical safety requirements. This skill bridges the gap between raw code and developer intent, facilitating more accurate code reviews, automated documentation, and proactive risk identification across various programming languages.

Key Features

• Accessibility (a11y) and test coverage markers for automated compliance auditing
• Standardized semantic tags for tracking tech debt, security risks, and performance bottlenecks
• Structured metadata support using JSON blocks for complex tool integration
• Language-specific annotation patterns for TypeScript, Python, Java, Go, and Rust
• Change impact and dependency markers to prevent breaking changes during refactoring
• 39 GitHub stars

Use Cases

• Documenting complex architectural patterns and technical debt to guide future AI-led refactoring
• Providing performance constraints and profiling data to help Claude suggest better optimizations
• Flagging security-sensitive code blocks with specific CWE references and mitigation strategies