What problem does it solve? Docker builds often fail due to wrong build contexts, poor layer caching, oversized images, or missing files, and debugging them wastes significant time. This Skill provides structured guidance for writing, fixing, and optimizing Dockerfiles and image builds for any project type. ## Core Features & Use Cases - Dockerfile Authoring & Optimization: Applies multi-stage builds, lockfile-first layer ordering for cache reuse, pinned base images, non-root runtime users, and .dockerignore hygiene for Node, Python, Go, and Java projects. - Build Debugging: Diagnoses failures by locating the failing stage, checking build context versus Dockerfile paths, verifying lockfile and package manager compatibility, and using --progress=plain or --no-cache when needed. - Bootstrap Scripts: Generates a starter Dockerfile and .dockerignore tailored to detected project type (Node, Python, or generic) via executable scripts. - Use Case: Your FastAPI build fails with "COPY requirements.txt not found" even though the file exists in backend/. The Skill identifies the build context mismatch and recommends running docker compose build or fixing the COPY path. ## Quick Start Ask the AI to containerize your project or fix a failing Docker build, for example: "Improve my Dockerfile caching and give me the right docker build command for my Node app."