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secondsky
bun-docker

Use for Docker with Bun, Dockerfiles, oven/bun image, containerization, and deployments.

Overview

Publishersecondsky
Repositoryclaude-skills
Skill namebun-docker
Stars
219
Forks
31
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 secondsky on GitHub. Read the source before you install it.

Installation

Install the Bun 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/secondsky/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/plugins/bun/skills/bun-docker .claude/skills/bun-docker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bun 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 Bun 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 Bun 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.

Bun Docker

Deploy Bun applications in Docker containers using official images.

Official Images

bash
# Latest stable
docker pull oven/bun

# Specific version
docker pull oven/bun:1

# Variants
oven/bun:latest       # Full image (~100MB)
oven/bun:slim         # Minimal image (~80MB)
oven/bun:alpine       # Alpine-based (~50MB)
oven/bun:distroless   # Distroless (~60MB)
oven/bun:debian       # Debian-based (~100MB)

Basic Dockerfile

dockerfile
FROM oven/bun:1 AS base

WORKDIR /app

# Install dependencies
COPY package.json bun.lockb ./
RUN bun install --frozen-lockfile

# Copy source
COPY . .

# Run
EXPOSE 3000
CMD ["bun", "run", "src/index.ts"]

Multi-Stage Build (Production)

dockerfile
# Build stage
FROM oven/bun:1 AS builder

WORKDIR /app

COPY package.json bun.lockb ./
RUN bun install --frozen-lockfile

COPY . .
RUN bun run build

# Production stage
FROM oven/bun:1-slim AS production

WORKDIR /app

# Copy only production dependencies
COPY package.json bun.lockb ./
RUN bun install --frozen-lockfile --production

# Copy built assets
COPY --from=builder /app/dist ./dist

# Run as non-root
USER bun

EXPOSE 3000
CMD ["bun", "run", "dist/index.js"]

Alpine Image

dockerfile
FROM oven/bun:1-alpine

WORKDIR /app

# Alpine uses apk for packages
RUN apk add --no-cache git

COPY package.json bun.lockb ./
RUN bun install --frozen-lockfile

COPY . .

CMD ["bun", "run", "src/index.ts"]

Distroless Image

dockerfile
# Build stage
FROM oven/bun:1 AS builder

WORKDIR /app
COPY . .
RUN bun install --frozen-lockfile
RUN bun build src/index.ts --compile --outfile=app

# Runtime stage
FROM gcr.io/distroless/base

COPY --from=builder /app/app /app

ENTRYPOINT ["/app"]

Docker Compose

yaml
# docker-compose.yml
version: "3.8"

services:
  app:
    build: .
    ports:
      - "3000:3000"
    environment:
      - NODE_ENV=production
      - DATABASE_URL=postgres://db:5432/app
    depends_on:
      - db
    restart: unless-stopped

  db:
    image: postgres:16-alpine
    environment:
      POSTGRES_DB: app
      POSTGRES_USER: user
      POSTGRES_PASSWORD: password
    volumes:
      - postgres_data:/var/lib/postgresql/data

volumes:
  postgres_data:

Hot Reload in Development

yaml
# docker-compose.dev.yml
version: "3.8"

services:
  app:
    build:
      context: .
      dockerfile: Dockerfile.dev
    ports:
      - "3000:3000"
    volumes:
      - ./src:/app/src
      - ./package.json:/app/package.json
    command: bun --hot run src/index.ts
dockerfile
# Dockerfile.dev
FROM oven/bun:1

WORKDIR /app

COPY package.json bun.lockb ./
RUN bun install

# Source mounted as volume
CMD ["bun", "--hot", "run", "src/index.ts"]

Compiled Binary

dockerfile
FROM oven/bun:1 AS builder

WORKDIR /app
COPY . .
RUN bun install --frozen-lockfile
RUN bun build src/index.ts --compile --outfile=server

# Minimal runtime
FROM ubuntu:22.04

# Install runtime dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
    ca-certificates \
    && rm -rf /var/lib/apt/lists/*

COPY --from=builder /app/server /usr/local/bin/server

USER nobody
EXPOSE 3000
CMD ["server"]

SQLite with Docker

dockerfile
FROM oven/bun:1

WORKDIR /app

COPY package.json bun.lockb ./
RUN bun install --frozen-lockfile

COPY . .

# Create data directory
RUN mkdir -p /app/data

# Volume for SQLite database
VOLUME /app/data

ENV DATABASE_PATH=/app/data/app.sqlite

CMD ["bun", "run", "src/index.ts"]

Health Checks

dockerfile
FROM oven/bun:1

WORKDIR /app
COPY . .
RUN bun install --frozen-lockfile

EXPOSE 3000

HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
  CMD curl -f http://localhost:3000/health || exit 1

CMD ["bun", "run", "src/index.ts"]
typescript
// Health endpoint
app.get("/health", (c) => c.json({ status: "ok" }));

Environment Variables

dockerfile
FROM oven/bun:1

WORKDIR /app

# Build-time args
ARG NODE_ENV=production
ARG API_URL

# Runtime env
ENV NODE_ENV=${NODE_ENV}
ENV API_URL=${API_URL}

COPY . .
RUN bun install --frozen-lockfile

CMD ["bun", "run", "src/index.ts"]
bash
# Build with args
docker build --build-arg API_URL=https://api.example.com -t myapp .

# Run with env
docker run -e DATABASE_URL=postgres://... myapp

Caching Optimization

dockerfile
FROM oven/bun:1 AS base

WORKDIR /app

# Cache dependencies separately
FROM base AS deps
COPY package.json bun.lockb ./
RUN bun install --frozen-lockfile

# Build
FROM deps AS builder
COPY . .
RUN bun run build

# Production
FROM base AS runner
COPY --from=deps /app/node_modules ./node_modules
COPY --from=builder /app/dist ./dist
COPY package.json ./

USER bun
CMD ["bun", "run", "dist/index.js"]

Secure Installation

When installing packages in Docker builds, follow supply chain security best practices:

  • Block post-install scripts — Bun disables them by default; allow specific packages via trustedDependencies
  • Pin dependency versions — Use exact versions in package.json for reproducible builds
  • Audit before installing — Run socket package score npm <pkg> to check packages before they reach your image

Load the dependency-upgrade skill for full security configuration including Socket CLI integration, cooldown setup, lockfile validation, and CI enforcement.

Security Best Practices

dockerfile
FROM oven/bun:1-slim

WORKDIR /app

# Don't run as root
USER bun

# Copy with correct ownership
COPY --chown=bun:bun package.json bun.lockb ./
RUN bun install --frozen-lockfile --production

COPY --chown=bun:bun . .

# Read-only filesystem
# (use with: docker run --read-only)

EXPOSE 3000
CMD ["bun", "run", "src/index.ts"]

.dockerignore

node_modules
.git
.gitignore
*.md
Dockerfile*
docker-compose*
.env*
.DS_Store
coverage
dist
.bun

Common Commands

bash
# Build
docker build -t myapp .

# Run
docker run -p 3000:3000 myapp

# Run with env file
docker run --env-file .env -p 3000:3000 myapp

# Interactive shell
docker run -it oven/bun sh

# Check Bun version
docker run oven/bun bun --version

Common Errors

ErrorCauseFix
bun.lockb not foundMissing lockfileRun bun install locally
EACCES permissionFile ownershipUse --chown=bun:bun
OOM killedMemory limitIncrease container memory
No space leftLarge layersUse multi-stage builds

When to Load References

Load references/optimization.md when:

  • Image size reduction
  • Layer caching
  • Build performance

Load references/kubernetes.md when:

  • K8s deployment
  • Horizontal scaling
  • Service mesh

Frequently asked questions

What does the Bun Docker AI skill do?

Use for Docker with Bun, Dockerfiles, oven/bun image, containerization, and deployments.

Why use Bun Docker on TypingMind?

Because you install it once and use it with any model. Bun 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 Bun Docker in TypingMind?

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

Which AI models can use Bun 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 Bun Docker?

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

Is the Bun Docker AI skill free?

Yes. It is published on GitHub by secondsky 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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