Docker

**Judgement:** Strong, high-signal Docker expertise skill. Well-suited as the primary assistant module for Dockerfiles, container builds, Compose stacks, networking/volumes, and production operations. It encodes many best practices and real-world failure modes that generic reasoning often misses. **Key strengths & benefits** - Emphasizes robust production practices: pinned images, minimal layers, non-root users, resource limits, and log rotation. - Explicitly documents common Docker, networking, and Compose traps (e.g., `depends_on` vs readiness, bridge DNS, anonymous volumes, build cache invalidation). - Offers concrete, actionable commands and diagnostics for debugging crashes, OOMs, and failed startups. - Covers lifecycle hygiene: pruning images, containers, networks, and volumes to control disk usage. **Risks & limitations** - Opinionated defaults (e.g., always setting memory limits, non-root, strict version pinning) may not match every user’s environment or constraints; the assistant must adapt recommendations instead of applying rules blindly. - Pruning and volume management guidance (e.g., `docker system prune`, `--volumes`) can be destructive if applied without clear user confirmation about data retention. - As Docker evolves, some details or recommended flags may drift from best current versions; cross-checking against user’s Docker version is prudent for advanced features. **Recommended scenarios** - Assisting with authoring, optimizing, or refactoring Dockerfiles and multi-stage builds. - Designing and debugging Docker Compose setups, including health checks, port bindings, and environment configuration. - Troubleshooting container startup failures, crashes, and resource issues in dev, CI, or production. - Advising on secure and maintainable container operations: non-root execution, minimal privileges, safe secret handling, and controlled resource and log behavior.