What problem does it solve? Adopting spec-driven development in an existing brownfield project requires manually analyzing the codebase, writing initial specifications, and configuring AI coding assistants — a slow, error-prone setup process that this Skill automates end to end. ## Core Features & Use Cases - Deep Codebase Analysis: Explores structure, architecture, domains, quality standards, and security posture, with an optional knowledge-graph mode using tree-sitter AST parsing and Leiden community detection. - OpenSpec Initialization: Runs openspec init, populates openspec/config.yaml with project context and per-artifact rules, and seeds behavioral specs per discovered domain. - Multi-Tool AI Configuration: Generates agent definitions and instruction files for GitHub Copilot, Claude Code, OpenAI Codex, Cursor, and Windsurf in each tool's native format. - Use Case: A team inheriting a legacy repository runs this Skill once to produce a populated openspec/ directory, CLAUDE.md, .github/agents/, and scoped rule files, then immediately starts proposing spec-driven changes. ## Quick Start Ask the AI to bootstrap OpenSpec for this repository and generate agent instructions for the AI coding tools your team uses.