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Found 4 Skills
End-to-end project engineering — from understanding user intent to architecture design, incremental build with verification, and systematic debugging. Covers scheduled tasks (cron jobs), dashboards, web apps, APIs, scripts, and any software the user wants built. Replaces coder + preview-dev with a unified methodology.
[Implementation] ⚡⚡⚡ Implement a feature [step by step]
AI SDLC repository spec-driven development workflow. Use when an AI assistant receives a medium or large feature, refactor, API change, architecture change, provider integration change, or any request that must follow requirements, design, test cases, QA planning, tasks, implementation, and validation. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.
Production-grade engineering skills for AI coding agents - lifecycle commands, workflow automation, and best practices for software development.