Frameworks
Best Docker Agent Skills
270 Docker skills for AI coding assistants — ranked by popularity.
This collection provides curated skill definitions for AI agents like Claude Code, Cursor, and Codex, specifically focused on Docker workflows and infrastructure management. Developers use these files to give their agents specialized expertise in containerized environments. Whether you need to optimize build performance for large monorepos with Bazel, manage serverless container deployment on Google Cloud Run or Modal, or handle secure secrets in CI/CD pipelines, these skills provide the necessary context. You will also find capabilities for managing Proxmox virtual environments, connecting to remote hosts for debugging, and maintaining Azure cloud resources. These files standardize how an agent interacts with your stack, turning generic AI assistants into focused operators for your specific Docker-based infrastructure. By implementing these skills, you ensure your agent follows your preferred patterns for data engineering pipelines or cloud resource orchestration, reducing trial-and-error during infrastructure tasks.
Top Docker skills
bazel-build-optimization
wshobson
Optimize Bazel builds for large-scale monorepos. Use when configuring Bazel, implementing remote execution, or optimizing build performance for enterprise codebases.
gcp-cloud-run
aj-geddes
Deploy containerized applications on Google Cloud Run with automatic scaling, traffic management, and service mesh integration. Use for container-based serverless computing.
senior-data-engineer
davila7
World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, or implementing data governance.
modal
davila7
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
secrets-management
wshobson
Implement secure secrets management for CI/CD pipelines using Vault, AWS Secrets Manager, or native platform solutions. Use when handling sensitive credentials, rotating secrets, or securing CI/CD environments.
deployment-pipeline-design
wshobson
Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.
github-actions-templates
wshobson
Create production-ready GitHub Actions workflows for automated testing, building, and deploying applications. Use when setting up CI/CD with GitHub Actions, automating development workflows, or creating reusable workflow templates.
storage-networking
pluginagentmarketplace
Master Kubernetes storage management and networking architecture. Learn persistent storage, network policies, service discovery, and ingress routing.
monorepo-management
wshobson
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.
senior-computer-vision
davila7
World-class computer vision skill for image/video processing, object detection, segmentation, and visual AI systems. Expertise in PyTorch, OpenCV, YOLO, SAM, diffusion models, and vision transformers. Includes 3D vision, video analysis, real-time processing, and production deployment. Use when building vision AI systems, implementing object detection, training custom vision models, or optimizing inference pipelines.
k8s-helm
rohitg00
Manage Helm charts, releases, and repositories. Use for Helm installations, upgrades, rollbacks, chart development, and release management.
linux-production-shell-scripts
davila7
This skill should be used when the user asks to "create bash scripts", "automate Linux tasks", "monitor system resources", "backup files", "manage users", or "write production shell scripts". It provides ready-to-use shell script templates for system administration.
add-provider-doc
lobehub
Guide for adding new AI provider documentation. Use when adding documentation for a new AI provider (like OpenAI, Anthropic, etc.), including usage docs, environment variables, Docker config, and image resources. Triggers on provider documentation tasks.
senior-prompt-engineer
davila7
World-class prompt engineering skill for LLM optimization, prompt patterns, structured outputs, and AI product development. Expertise in Claude, GPT-4, prompt design patterns, few-shot learning, chain-of-thought, and AI evaluation. Includes RAG optimization, agent design, and LLM system architecture. Use when building AI products, optimizing LLM performance, designing agentic systems, or implementing advanced prompting techniques.
docker-expert
davila7
Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.
cloudflare-deploy
davila7
Deploy applications and infrastructure to Cloudflare using Workers, Pages, and related platform services. Use when the user asks to deploy, host, publish, or set up a project on Cloudflare.
kubernetes-architect
sickn33
Expert Kubernetes architect specializing in cloud-native infrastructure, advanced GitOps workflows (ArgoCD/Flux), and enterprise container orchestration. Masters EKS/AKS/GKE, service mesh (Istio/Linkerd), progressive delivery, multi-tenancy, and platform engineering. Handles security, observability, cost optimization, and developer experience. Use PROACTIVELY for K8s architecture, GitOps implementation, or cloud-native platform design.
autogpt-agents
davila7
Autonomous AI agent platform for building and deploying continuous agents. Use when creating visual workflow agents, deploying persistent autonomous agents, or building complex multi-step AI automation systems.
gitlab-ci-patterns
wshobson
Build GitLab CI/CD pipelines with multi-stage workflows, caching, and distributed runners for scalable automation. Use when implementing GitLab CI/CD, optimizing pipeline performance, or setting up automated testing and deployment.
machine-learning-ops-ml-pipeline
sickn33
Design and implement a complete ML pipeline for: $ARGUMENTS
senior-ml-engineer
davila7
World-class ML engineering skill for productionizing ML models, MLOps, and building scalable ML systems. Expertise in PyTorch, TensorFlow, model deployment, feature stores, model monitoring, and ML infrastructure. Includes LLM integration, fine-tuning, RAG systems, and agentic AI. Use when deploying ML models, building ML platforms, implementing MLOps, or integrating LLMs into production systems.
mlops-engineer
sickn33
Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.
monorepo-architect
sickn33
Expert in monorepo architecture, build systems, and dependency management at scale. Masters Nx, Turborepo, Bazel, and Lerna for efficient multi-project development. Use PROACTIVELY for monorepo setup,
workflow-automation
ruvnet
Workflow creation, execution, and template management. Automates complex multi-step processes with agent coordination. Use when: automating processes, creating reusable workflows, orchestrating multi-step tasks. Skip when: simple single-step tasks, ad-hoc operations.
How to choose a Docker skill
Evaluate these skills based on your current deployment target and infrastructure requirements. Start by identifying the specific ecosystem you interact with, such as GCP, Azure, or Proxmox. Check the scope of each skill to see if it covers your common manual tasks, like secrets management or build optimization. Review the file content to ensure the agent's instructions align with your project's security practices and operational patterns. Select skills that match the specific tools you use daily to minimize context switching for your AI agent.
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