容器开发

docker-development

by alirezarezvani

Docker and container development agent skill and plugin for Dockerfile optimization, docker-compose orchestration, multi-stage builds, and container security hardening. Use when: user wants to optimize a Dockerfile, create or improve docker-compose configurations, implement multi-stage builds, audit container security, reduce image size, or follow container best practices. Covers build performance, layer caching, secret management, and production-ready container patterns.

3.7kDevOps未扫描2026年3月23日

安装

claude skill add --url github.com/openclaw/skills/tree/main/skills/alirezarezvani/docker-development

文档

Docker Development

Smaller images. Faster builds. Secure containers. No guesswork.

Opinionated Docker workflow that turns bloated Dockerfiles into production-grade containers. Covers optimization, multi-stage builds, compose orchestration, and security hardening.

Not a Docker tutorial — a set of concrete decisions about how to build containers that don't waste time, space, or attack surface.


Slash Commands

CommandWhat it does
/docker:optimizeAnalyze and optimize a Dockerfile for size, speed, and layer caching
/docker:composeGenerate or improve docker-compose.yml with best practices
/docker:securityAudit a Dockerfile or running container for security issues

When This Skill Activates

Recognize these patterns from the user:

  • "Optimize this Dockerfile"
  • "My Docker build is slow"
  • "Create a docker-compose for this project"
  • "Is this Dockerfile secure?"
  • "Reduce my Docker image size"
  • "Set up multi-stage builds"
  • "Docker best practices for [language/framework]"
  • Any request involving: Dockerfile, docker-compose, container, image size, build cache, Docker security

If the user has a Dockerfile or wants to containerize something → this skill applies.


Workflow

/docker:optimize — Dockerfile Optimization

  1. Analyze current state

    • Read the Dockerfile
    • Identify base image and its size
    • Count layers (each RUN/COPY/ADD = 1 layer)
    • Check for common anti-patterns
  2. Apply optimization checklist

    code
    BASE IMAGE
    ├── Use specific tags, never :latest in production
    ├── Prefer slim/alpine variants (debian-slim > ubuntu > debian)
    ├── Pin digest for reproducibility in CI: image@sha256:...
    └── Match base to runtime needs (don't use python:3.12 for a compiled binary)
    
    LAYER OPTIMIZATION
    ├── Combine related RUN commands with && \
    ├── Order layers: least-changing first (deps before source code)
    ├── Clean package manager cache in the same RUN layer
    ├── Use .dockerignore to exclude unnecessary files
    └── Separate build deps from runtime deps
    
    BUILD CACHE
    ├── COPY dependency files before source code (package.json, requirements.txt, go.mod)
    ├── Install deps in a separate layer from code copy
    ├── Use BuildKit cache mounts: --mount=type=cache,target=/root/.cache
    └── Avoid COPY . . before dependency installation
    
    MULTI-STAGE BUILDS
    ├── Stage 1: build (full SDK, build tools, dev deps)
    ├── Stage 2: runtime (minimal base, only production artifacts)
    ├── COPY --from=builder only what's needed
    └── Final image should have NO build tools, NO source code, NO dev deps
    
  3. Generate optimized Dockerfile

    • Apply all relevant optimizations
    • Add inline comments explaining each decision
    • Report estimated size reduction
  4. Validate

    bash
    python3 scripts/dockerfile_analyzer.py Dockerfile
    

/docker:compose — Docker Compose Configuration

  1. Identify services

    • Application (web, API, worker)
    • Database (postgres, mysql, redis, mongo)
    • Cache (redis, memcached)
    • Queue (rabbitmq, kafka)
    • Reverse proxy (nginx, traefik, caddy)
  2. Apply compose best practices

    code
    SERVICES
    ├── Use depends_on with condition: service_healthy
    ├── Add healthchecks for every service
    ├── Set resource limits (mem_limit, cpus)
    ├── Use named volumes for persistent data
    └── Pin image versions
    
    NETWORKING
    ├── Create explicit networks (don't rely on default)
    ├── Separate frontend and backend networks
    ├── Only expose ports that need external access
    └── Use internal: true for backend-only networks
    
    ENVIRONMENT
    ├── Use env_file for secrets, not inline environment
    ├── Never commit .env files (add to .gitignore)
    ├── Use variable substitution: ${VAR:-default}
    └── Document all required env vars
    
    DEVELOPMENT vs PRODUCTION
    ├── Use compose profiles or override files
    ├── Dev: bind mounts for hot reload, debug ports exposed
    ├── Prod: named volumes, no debug ports, restart: unless-stopped
    └── docker-compose.override.yml for dev-only config
    
  3. Generate compose file

    • Output docker-compose.yml with healthchecks, networks, volumes
    • Generate .env.example with all required variables documented
    • Add dev/prod profile annotations

/docker:security — Container Security Audit

  1. Dockerfile audit

    CheckSeverityFix
    Running as rootCriticalAdd USER nonroot after creating user
    Using :latest tagHighPin to specific version
    Secrets in ENV/ARGCriticalUse BuildKit secrets: --mount=type=secret
    COPY with broad globMediumUse specific paths, add .dockerignore
    Unnecessary EXPOSELowOnly expose ports the app uses
    No HEALTHCHECKMediumAdd HEALTHCHECK with appropriate interval
    Privileged instructionsHighAvoid --privileged, drop capabilities
    Package manager cache retainedLowClean in same RUN layer
  2. Runtime security checks

    CheckSeverityFix
    Container running as rootCriticalSet user in Dockerfile or compose
    Writable root filesystemMediumUse read_only: true in compose
    All capabilities retainedHighDrop all, add only needed: cap_drop: [ALL]
    No resource limitsMediumSet mem_limit and cpus
    Host network modeHighUse bridge or custom network
    Sensitive mountsCriticalNever mount /etc, /var/run/docker.sock in prod
    No log driver configuredLowSet logging: with size limits
  3. Generate security report

    code
    SECURITY AUDIT — [Dockerfile/Image name]
    Date: [timestamp]
    
    CRITICAL: [count]
    HIGH:     [count]
    MEDIUM:   [count]
    LOW:      [count]
    
    [Detailed findings with fix recommendations]
    

Tooling

scripts/dockerfile_analyzer.py

CLI utility for static analysis of Dockerfiles.

Features:

  • Layer count and optimization suggestions
  • Base image analysis with size estimates
  • Anti-pattern detection (15+ rules)
  • Security issue flagging
  • Multi-stage build detection and validation
  • JSON and text output

Usage:

bash
# Analyze a Dockerfile
python3 scripts/dockerfile_analyzer.py Dockerfile

# JSON output
python3 scripts/dockerfile_analyzer.py Dockerfile --output json

# Analyze with security focus
python3 scripts/dockerfile_analyzer.py Dockerfile --security

# Check a specific directory
python3 scripts/dockerfile_analyzer.py path/to/Dockerfile

scripts/compose_validator.py

CLI utility for validating docker-compose files.

Features:

  • Service dependency validation
  • Healthcheck presence detection
  • Network configuration analysis
  • Volume mount validation
  • Environment variable audit
  • Port conflict detection
  • Best practice scoring

Usage:

bash
# Validate a compose file
python3 scripts/compose_validator.py docker-compose.yml

# JSON output
python3 scripts/compose_validator.py docker-compose.yml --output json

# Strict mode (fail on warnings)
python3 scripts/compose_validator.py docker-compose.yml --strict

Multi-Stage Build Patterns

Pattern 1: Compiled Language (Go, Rust, C++)

dockerfile
# Build stage
FROM golang:1.22-alpine AS builder
WORKDIR /app
COPY go.mod go.sum ./
RUN go mod download
COPY . .
RUN CGO_ENABLED=0 go build -ldflags="-s -w" -o /app/server ./cmd/server

# Runtime stage
FROM gcr.io/distroless/static-debian12
COPY --from=builder /app/server /server
USER nonroot:nonroot
ENTRYPOINT ["/server"]

Pattern 2: Node.js / TypeScript

dockerfile
# Dependencies stage
FROM node:20-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci --production=false

# Build stage
FROM deps AS builder
COPY . .
RUN npm run build

# Runtime stage
FROM node:20-alpine
WORKDIR /app
RUN addgroup -g 1001 -S appgroup && adduser -S appuser -u 1001
COPY --from=builder /app/dist ./dist
COPY --from=deps /app/node_modules ./node_modules
COPY package.json ./
USER appuser
EXPOSE 3000
CMD ["node", "dist/index.js"]

Pattern 3: Python

dockerfile
# Build stage
FROM python:3.12-slim AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir --prefix=/install -r requirements.txt

# Runtime stage
FROM python:3.12-slim
WORKDIR /app
RUN groupadd -r appgroup && useradd -r -g appgroup appuser
COPY --from=builder /install /usr/local
COPY . .
USER appuser
EXPOSE 8000
CMD ["python", "-m", "uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

Base Image Decision Tree

code
Is it a compiled binary (Go, Rust, C)?
├── Yes → distroless/static or scratch
└── No
    ├── Need a shell for debugging?
    │   ├── Yes → alpine variant (e.g., node:20-alpine)
    │   └── No → distroless variant
    ├── Need glibc (not musl)?
    │   ├── Yes → slim variant (e.g., python:3.12-slim)
    │   └── No → alpine variant
    └── Need specific OS packages?
        ├── Many → debian-slim
        └── Few → alpine + apk add

Proactive Triggers

Flag these without being asked:

  • Dockerfile uses :latest → Suggest pinning to a specific version tag.
  • No .dockerignore → Create one. At minimum: .git, node_modules, __pycache__, .env.
  • COPY . . before dependency install → Cache bust. Reorder to install deps first.
  • Running as root → Add USER instruction. No exceptions for production.
  • Secrets in ENV or ARG → Use BuildKit secret mounts. Never bake secrets into layers.
  • Image over 1GB → Multi-stage build required. No reason for a production image this large.
  • No healthcheck → Add one. Orchestrators (Compose, K8s) need it for proper lifecycle management.
  • apt-get without cleanup in same layerrm -rf /var/lib/apt/lists/* in the same RUN.

Installation

One-liner (any tool)

bash
git clone https://github.com/alirezarezvani/claude-skills.git
cp -r claude-skills/engineering/docker-development ~/.claude/skills/

Multi-tool install

bash
./scripts/convert.sh --skill docker-development --tool codex|gemini|cursor|windsurf|openclaw

OpenClaw

bash
clawhub install cs-docker-development

Related Skills

  • senior-devops — Broader DevOps scope (CI/CD, IaC, monitoring). Complementary — use docker-development for container-specific work, senior-devops for pipeline and infrastructure.
  • senior-security — Application security. Complementary — docker-development covers container security, senior-security covers application-level threats.
  • autoresearch-agent — Can optimize Docker build times or image sizes as measurable experiments.
  • ci-cd-pipeline-builder — Pipeline construction. Complementary — docker-development builds the containers, ci-cd-pipeline-builder deploys them.

相关 Skills

可观测性设计

by alirezarezvani

Universal
热门

面向生产系统规划可落地的可观测性体系,串起指标、日志、链路追踪与 SLI/SLO、错误预算、告警和仪表盘设计,适合搭建监控平台与优化故障响应。

把监控、日志、链路追踪串起来,帮助团队从设计阶段构建可观测性,排障更快、系统演进更稳。

DevOps
未扫描9.0k

资深开发运维

by alirezarezvani

Universal
热门

覆盖 CI/CD 流水线生成、Terraform 基建脚手架和自动化部署,适合在 AWS、GCP、Azure 上搭建云原生发布流程,管理 Docker/Kubernetes 基础设施并持续优化交付。

把CI/CD、基础设施即代码、容器与监控串成一条交付链,尤其适合AWS/GCP/Azure多云团队高效落地。

DevOps
未扫描9.0k

环境密钥管理

by alirezarezvani

Universal
热门

统一梳理dev/staging/prod的.env和密钥流程,自动生成.env.example、校验必填变量、扫描Git历史泄漏,并联动Vault、AWS SSM、1Password、Doppler完成轮换。

统一管理环境变量、密钥与配置,减少泄露和部署混乱,安全治理与团队协作一起做好,DevOps 场景很省心。

DevOps
未扫描9.0k

相关 MCP 服务

kubefwd

编辑精选

by txn2

热门

kubefwd 是让 AI 帮你批量转发 Kubernetes 服务到本地的开发神器。

微服务开发者最头疼的本地调试问题,它一键搞定——自动分配 IP 避免端口冲突,还能用自然语言查询状态。但依赖 AI 工作流,纯命令行爱好者可能觉得不够直接。

DevOps
4.1k

Cloudflare

编辑精选

by Cloudflare

热门

Cloudflare MCP Server 是让你用自然语言管理 Workers、KV 和 R2 等云资源的工具。

这个工具解决了开发者频繁切换控制台和文档的痛点,特别适合那些在 Cloudflare 上部署无服务器应用、需要快速调试或管理配置的团队。不过,由于它依赖多个子服务器,初次设置可能有点繁琐,建议先从 Workers Bindings 这类核心功能入手。

DevOps
3.6k

Terraform

编辑精选

by hashicorp

Terraform MCP Server 是让 AI 助手直接操作 Terraform Registry 和 HCP Terraform 的桥梁。

如果你经常在 Terraform 里翻文档找模块配置,这个服务器能省不少时间——直接问 Claude 就能生成准确的代码片段。最适合管理多云基础设施的团队,但注意它目前只适合本地使用,别在生产环境里暴露 HTTP 端点。

DevOps
1.3k

评论