What problem does it solve? AI agents lack reliable project context when entering a repository, leading to guessed commands, invented conventions, and missed stacks in multi-ecosystem monorepos. This Skill builds a sourced, confidence-classified project reference so every subsequent agent decision is grounded in evidence. ## Core Features & Use Cases - Read-only repository discovery: Inventories git metadata, manifests, configs, CI, tests, and docs without executing project code or reading secrets. - Deep workspace scanning: Runs a bundled filesystem sweep script to surface every project root, then classifies each stack (Node, Flutter, Go, Rust, Python, and more) so monorepo stacks are never collapsed into one. - Structured artifacts: Produces .agents/PRJ_REFERENCE.md from a template with executive summary, tech stack, business rules, commands, and unknowns, plus a merged .agents/settings.yaml that preserves user values. - Use Case: An agent joins a monorepo containing a Next.js app and a Flutter app. Running this Skill scans the filesystem, records both stacks separately with their own commands, and flags undocumented conventions as unknowns for user confirmation. ## Quick Start Ask the agent to initialize or refresh the project reference and settings for this repository using the init skill.