What problem does it solve? Onboarding an AI agent (or a new engineer) to an unfamiliar repository requires manually discovering the tech stack, monorepo layout, folder conventions, test setup, CI/CD, and architectural risks. This Skill automates that first-contact analysis and persists the findings in a shared project registry so every future session starts with full context. ## Core Features & Use Cases - 7-Step Scan Pipeline: Detects language, frameworks, monorepo type (pnpm/npm workspaces, Nx, Turborepo), entry points, data layer, auth model, testing stack, and CI/CD provider. - 12-Section Project Profile: Generates a structured project_profile.md plus an auto-filled architecture.md in a global registry (Level 1.5), shared across worktrees and sessions. - Architectural Red Flags: Flags god packages, circular imports, raw SQL outside migrations, missing tests, and hardcoded secrets with evidence. - Use Case: The first time Che touches a new repository, run the X-Ray scan once; every later agent session reads the persisted profile instead of re-scanning the codebase. ## Quick Start Run the che-xray scan on this repository to detect its stack and structure and generate the project profile in the registry.