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codewithmukesh
docker

Docker containerization for .NET 10 applications. Covers multi-stage builds, .NET container images, non-root user configuration, health checks, and .dockerignore. Load this skill when containerizing an application with a Dockerfile, optimizing image size, setting up Docker Compose for local development, or when the user mentions "Docker", "Dockerfile", "container", "docker-compose", "image", "multi-stage", "non-root", ".dockerignore", or "container health check". For Dockerfile-less SDK publishing (`dotnet publish /t:PublishContainer`), load the container-publish skill instead.

Overview

Publishercodewithmukesh
Repositorydotnet-claude-kit
Skill namedocker
Stars
721
Forks
170
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by codewithmukesh on GitHub. Read the source before you install it.

Installation

Install the Docker AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/codewithmukesh/dotnet-claude-kit.git /tmp/dotnet-claude-kit
mkdir -p .claude/skills
cp -r /tmp/dotnet-claude-kit/skills/docker .claude/skills/docker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Docker in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Docker on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Docker is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Docker

Core Principles

  1. Multi-stage builds always — Separate build and runtime stages. Build in the SDK image, run in the ASP.NET runtime image.
  2. Non-root by default — .NET container images support USER app by default since .NET 8. Never run as root in production.
  3. Layer caching matters — Copy .csproj files and restore before copying source code. This caches NuGet dependencies across builds.
  4. Health probes at the orchestrator level — Expose a /health/live endpoint and let Kubernetes/Compose probe it. Chiseled and default aspnet images have no shell or curl, so in-image HEALTHCHECK commands have nothing to run with.

Patterns

Multi-Stage Dockerfile for Web API

dockerfile
# Stage 1: Build
FROM mcr.microsoft.com/dotnet/sdk:10.0 AS build
WORKDIR /src

# Copy project files and restore (cached layer)
COPY ["src/MyApp.Api/MyApp.Api.csproj", "src/MyApp.Api/"]
COPY ["src/MyApp.Domain/MyApp.Domain.csproj", "src/MyApp.Domain/"]
COPY ["Directory.Build.props", "."]
COPY ["Directory.Packages.props", "."]
RUN dotnet restore "src/MyApp.Api/MyApp.Api.csproj"

# Copy everything and build
COPY . .
RUN dotnet publish "src/MyApp.Api/MyApp.Api.csproj" \
    -c Release \
    -o /app/publish \
    --no-restore

# Stage 2: Runtime
FROM mcr.microsoft.com/dotnet/aspnet:10.0 AS runtime
WORKDIR /app

# Non-root user (default in .NET 8+ images)
USER app

COPY --from=build /app/publish .

EXPOSE 8080

ENTRYPOINT ["dotnet", "MyApp.Api.dll"]

Container Health Probes

Prefer orchestrator-level probes (Kubernetes livenessProbe, Compose healthcheck) over a Dockerfile HEALTHCHECK — the standard aspnet and chiseled images ship no shell, no curl, and no wget, so there is nothing inside the container to run the probe with. Point the orchestrator at /health/live:

yaml
# docker-compose — probe from outside the app process
services:
  api:
    healthcheck:
      test: ["CMD-SHELL", "wget -qO- http://localhost:8080/health/live || exit 1"]
      interval: 30s
      timeout: 3s
      retries: 3
# Note: CMD-SHELL requires a shell + wget in the image. Use a non-chiseled
# variant for this, or better: let Kubernetes httpGet probes do it —
# they run from the kubelet, needing nothing inside the image.

If you must have an in-image HEALTHCHECK, base the runtime stage on a non-chiseled image that includes wget — never re-run the app binary as the probe command; that starts a second instance instead of checking the first.

.dockerignore

**/.git
**/.vs
**/bin
**/obj
**/node_modules
**/Dockerfile*
**/docker-compose*
**/tests

Docker Compose for Local Development

Key .NET-specific concerns — pass connection strings via environment, use depends_on with health checks:

yaml
services:
  api:
    build:
      context: .
      dockerfile: src/MyApp.Api/Dockerfile
    ports:
      - "5000:8080"
    environment:
      - ASPNETCORE_ENVIRONMENT=Development
      - ConnectionStrings__Default=Host=postgres;Database=myapp;Username=postgres;Password=postgres
      - ConnectionStrings__Redis=redis:6379
    depends_on:
      postgres:
        condition: service_healthy
  # Add postgres/redis services with healthcheck — standard boilerplate

Optimized Build with .slnx

For solutions with multiple projects, restore only the necessary projects.

dockerfile
FROM mcr.microsoft.com/dotnet/sdk:10.0 AS build
WORKDIR /src

# Copy solution and all project files
COPY *.slnx .
COPY Directory.Build.props .
COPY Directory.Packages.props .
COPY src/**/*.csproj ./src/

# Restore project structure
RUN for file in src/**/*.csproj; do \
    mkdir -p $(dirname $file) && mv $file $(dirname $file)/; \
    done
RUN dotnet restore

COPY . .
RUN dotnet publish src/MyApp.Api -c Release -o /app/publish --no-restore

Health Check Endpoint

csharp
// In Program.cs — lightweight health endpoint for Docker
app.MapGet("/health/live", () => Results.Ok("healthy"))
    .ExcludeFromDescription();

Anti-patterns

Don't Use SDK Image for Runtime

dockerfile
# BAD — SDK image is 900MB+, includes compilers
FROM mcr.microsoft.com/dotnet/sdk:10.0
COPY . .
RUN dotnet run

# GOOD — separate build and runtime, runtime image is ~200MB
FROM mcr.microsoft.com/dotnet/aspnet:10.0

Don't Copy Everything Before Restore

dockerfile
# BAD — any source change invalidates the NuGet cache
COPY . .
RUN dotnet restore

# GOOD — copy only project files first, then restore
COPY ["src/MyApp.Api/MyApp.Api.csproj", "src/MyApp.Api/"]
RUN dotnet restore "src/MyApp.Api/MyApp.Api.csproj"
COPY . .

Don't Run as Root

dockerfile
# BAD — running as root (security risk)
FROM mcr.microsoft.com/dotnet/aspnet:10.0
COPY --from=build /app .
ENTRYPOINT ["dotnet", "MyApp.Api.dll"]

# GOOD — use the built-in non-root user
FROM mcr.microsoft.com/dotnet/aspnet:10.0
USER app
COPY --from=build /app .
ENTRYPOINT ["dotnet", "MyApp.Api.dll"]

Decision Guide

ScenarioRecommendation
Web API containerMulti-stage build with aspnet runtime image
Worker serviceMulti-stage build with dotnet/runtime image
Local developmentDocker Compose with service dependencies
CI buildsMulti-stage build (self-contained)
Image size optimizationUse Alpine variant + trimming for small images
Health monitoring/health endpoint + orchestrator probe (K8s httpGet / Compose healthcheck)
SecretsEnvironment variables or mounted secrets, never in image

Frequently asked questions

What does the Docker AI skill do?

Docker containerization for .NET 10 applications. Covers multi-stage builds, .NET container images, non-root user configuration, health checks, and .dockerignore. Load this skill when containerizing an application with a Dockerfile, optimizing image size, setting up Docker Compose for local development, or when the user mentions "Docker", "Dockerfile", "container", "docker-compose", "image", "multi-stage", "non-root", ".dockerignore", or "container health check". For Dockerfile-less SDK publishing (`dotnet publish /t:PublishContainer`), load the container-publish skill instead.

Why use Docker on TypingMind?

Because you install it once and use it with any model. Docker is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Docker in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/codewithmukesh/dotnet-claude-kit/tree/main/skills/docker. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Docker?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Docker?

As many as you like. As long as a model supports skills, you can use Docker with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Docker AI skill free?

Yes. It is published on GitHub by codewithmukesh under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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