What problem does it solve? AI coding agents fail when project knowledge lives in Slack threads, wikis, or people's heads instead of the repository. This Skill provides patterns for structuring a repo so agents can find context, follow architectural rules, and avoid replicating bad patterns. ## Core Features & Use Cases - Knowledge Hierarchy: Defines a layered documentation architecture with AGENTS.md, ARCHITECTURE.md, and a docs/ tree covering design docs, exec plans, product specs, and quality scores. - Progressive Disclosure: Organizes docs in three layers so agents start with minimal context and drill deeper via index files and cross-links. - Mechanical Enforcement: Shows how to encode architectural rules as custom linters with remediation messages, structural dependency tests, and layer boundary checks enforced in CI. - Entropy Management: Provides golden principles, automated violation scanning, quality scoring, and tech-debt tracking to prevent agent-generated code drift. - Use Case: When setting up a new project for agent-first development, use this Skill to create AGENTS.md and ARCHITECTURE.md, then add lint rules that fail CI when agents violate layer boundaries. ## Quick Start Ask the agent to restructure this repository for agent-first development, starting with an AGENTS.md entry point and an ARCHITECTURE.md codemap.