What problem does it solve? AI coding agents often produce inconsistent code because they lack knowledge of a project's specific technology versions, conventions, and critical rules. This Skill captures those unobvious implementation details into a single project-context.md file that agents read before writing code. ## Core Features & Use Cases - Guided Discovery Workflow: Scans architecture documents, package files, and configuration files to identify the technology stack, coding patterns, and conventions. - Collaborative Rule Generation: Walks through rule categories (language, framework, testing, quality, workflow, anti-patterns) with user approval at each step via an A/P/C menu. - LLM-Optimized Output: Produces a lean, structured markdown file with frontmatter tracking, designed for efficient consumption by AI agents. - Use Case: A team adopting AI-assisted development on a NestJS/Next.js monorepo runs this workflow once to document TypeScript strict-mode rules, testing conventions, and commit patterns so every agent-generated PR follows the same standards. ## Quick Start Ask the AI to generate project context for this repository and follow the guided discovery and rule-generation steps.
