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Found 384 Skills
Use when setting up CI/CD, Docker, deployment pipelines, monitoring, alerting, infrastructure, or debugging production issues
Author ZenML pipelines: @step/@pipeline decorators, type hints, multi-output steps, dynamic vs static pipelines, artifact data flow, ExternalArtifact, YAML configuration, DockerSettings for remote execution, custom materializers, metadata logging, secrets management, and custom visualizations. Use this skill whenever asked to write a ZenML pipeline, create ZenML steps, make a pipeline work on Kubernetes/Vertex/SageMaker, add Docker settings, write a materializer, create a custom visualization, handle "works locally but fails on cloud" issues, or configure pipeline YAML files. Even if the user doesn't explicitly mention "pipeline authoring", use this skill when they ask to build an ML workflow, data pipeline, or training pipeline with ZenML.
Docker expert for containers, Compose, Dockerfiles, and debugging
Quick health checks for a Dockerized VPS. Use to verify services are running, check container status, view logs, or get a system overview (disk, memory, CPU). Read-only by design — anything that would change state is routed through the clipboard for the user to paste.
Generate an offline-first dependency overview across services in a Docker-compose monorepo. Reports image tags & pinning quality, Dockerfile base images, runtime hints (Node/Python via .nvmrc, .python-version, package.json engines, pyproject.toml), and lockfile presence. Use when you want a single report of "what am I running and where are my update surfaces?" — no network calls, no pulls.
Set up and manage local Kubernetes clusters using KIND (Kubernetes IN Docker). Use when testing Kubernetes applications locally or developing cloud-native workloads.
Dockerfile Generator - Auto-activating skill for DevOps Basics. Triggers on: dockerfile generator, dockerfile generator Part of the DevOps Basics skill category.
Optimizes PHP-FPM configuration in Docker containers. Tunes process manager, request handling, and resource allocation for production workloads.
Create Dockerfiles, docker-compose configurations, and container workflows for Python projects with UV. Use when containerizing applications, setting up development environments, or deploying with Docker.
WHEN: Dockerfile review, multi-stage builds, layer optimization, docker-compose WHAT: Image optimization + Layer caching + Security scanning + Compose best practices + Build efficiency WHEN NOT: Kubernetes → k8s-reviewer, Terraform → terraform-reviewer
Deploy projects to Vercel, Railway, or Docker with platform-specific best practices. Use when deploying applications, configuring deployment settings, debugging deployment failures, or setting up CI/CD pipelines. Triggers on "deploy to vercel", "railway deployment", "docker build", "deployment failed", "configure vercel.json".
Guide for using Docker - a containerization platform for building, running, and deploying applications in isolated containers. Use when containerizing applications, creating Dockerfiles, working with Docker Compose, managing images/containers, configuring networking and storage, optimizing builds, deploying to production, or implementing CI/CD pipelines with Docker.