skills/noise/docker_patterns/SKILL.md
Best practices for Docker containerization and multi-stage builds
npx skillsauth add langchain-ai/skills-benchmarks docker-patternsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Build efficient, secure Docker images using modern patterns.
Always use multi-stage builds to minimize image size:
# Build stage
FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
# Production stage
FROM node:20-alpine
WORKDIR /app
COPY --from=builder /app/node_modules ./node_modules
COPY . .
USER node
CMD ["node", "server.js"]
USER directivelatestdocker scout or Trivy.dockerignore to exclude sensitive filesHEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD curl -f http://localhost:3000/health || exit 1
services:
app:
build:
context: .
target: production
environment:
- NODE_ENV=production
deploy:
resources:
limits:
memory: 512M
development
INVOKE FIRST for any LangChain / LangGraph / Deep Agents agent building project before consulting other skills or writing any agent code. Required starting point for up to date info on framework selection (LangChain vs LangGraph vs Deep Agents vs hybrid composition), agent patterns, install, environment setup, and which skill to load next.
tools
INVOKE THIS SKILL when working with LangSmith tracing OR querying traces. Covers adding tracing to applications and querying/exporting trace data. Uses the langsmith CLI tool.
tools
INVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2) Defining Run Functions - how to capture outputs and trajectories from your agent; (3) Running Evaluations - locally with evaluate() or auto-run via LangSmith. Uses the langsmith CLI tool.
testing
Unit testing and integration testing best practices