Context Engineering

About

An expert system designed to handle complex context management within AI workflows through the C = A(c₁-c₆) framework. It enables users to classify, create, and validate context files systematically, ensuring high-quality inputs for Claude through rigorous analysis of relevance, completeness, consistency, and efficiency. Whether you are building a new knowledge base from scratch or auditing existing documentation for contradictions, this skill provides a structured approach to context engineering with built-in quality grading, semantic versioning, and automated discrepancy detection.

Key Features

• Contradiction and discrepancy detection across context portfolios
• Automated classification of content into standardized components (c₁-c₆)
• Semantic versioning for evolutionary context maintenance
• Multi-dimensional quality analysis using the α-β-γ-δ framework
• 0 GitHub stars
• Structured reporting via standardized quality and discrepancy templates

Use Cases

• Auditing existing context files for internal inconsistencies and information gaps
• Organizing raw project documentation into a structured, AI-ready context system
• Maintaining a high-quality knowledge repository with clear version control and grading