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.

14116

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.

5107

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.

2179

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.

587

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.

585

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.

670

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.

769

storage-networking

pluginagentmarketplace

Master Kubernetes storage management and networking architecture. Learn persistent storage, network policies, service discovery, and ingress routing.

663

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.

959

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.

1256

k8s-helm

rohitg00

Manage Helm charts, releases, and repositories. Use for Helm installations, upgrades, rollbacks, chart development, and release management.

857

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.

746

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.

646

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.

743

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.

1135

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.

342

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.

636

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.

536

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.

1030

machine-learning-ops-ml-pipeline

sickn33

Design and implement a complete ML pipeline for: $ARGUMENTS

436

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.

634

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.

333

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,

328

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.

327

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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+150 more — browse all skills.

Frequently asked

How do these skills affect my existing Docker configuration?
These skill files act as specialized system prompts for your AI agent. They do not automatically change your Dockerfiles unless you explicitly authorize the agent to perform write operations. They provide the agent with the necessary domain knowledge to suggest improvements or execute commands within your established container framework safely.
Can I combine multiple skills, such as secrets-management and gcp-cloud-run?
Yes, you can combine these skills to handle complex tasks. Many users apply multiple files to provide their agent with broader context. For instance, using the secrets-management skill alongside gcp-cloud-run allows the agent to understand both deployment requirements and your organization's specific security policies for handling sensitive environment variables.

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