deep-agents-core
INVOKE THIS SKILL when building ANY Deep Agents application. Covers create_deep_agent(), harness architecture, SKILL.md format, and configuration options.
INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.
$ npx -y skills add langchain-ai/langchain-skills --skill langgraph-cli --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/langgraph-cliContext preview
The summary Claude sees to decide when to auto-load this skill.
INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration.
name: langgraph-cli description: "INVOKE THIS SKILL when using the langgraph CLI to scaffold, develop, build, or deploy LangGraph applications. Covers langgraph new, dev, build, up, deploy, and langgraph.json configuration."
<overview> The `langgraph` CLI manages the full lifecycle of LangGraph applications — from scaffolding a new project to deploying it to LangGraph Platform (LangSmith Deployments).
Key commands:
All commands (except `new`) read from a `langgraph.json` config file in the project root. </overview>
Use this skill when the user wants to:
# Python pip install 'langgraph-cli[inmem]' # includes langgraph dev support pip install langgraph-cli # without dev server (build/up/deploy only) # if using UV as package manager uv add "langgraph-cli[inmem]" # includes langgraph dev support uv add langgraph-cli # without dev server (build/up/deploy only) # JavaScript npx @langchain/langgraph-cli # use on demand npm install -g @langchain/langgraph-cli # install globally (available as langgraphjs)
Scaffold a new project from a template.
langgraph new # interactive template selection langgraph new ./my-agent # create in specific directory langgraph new --template agent-python # skip prompt, use template directly
Available templates: `deep-agent-python`, `deep-agent-js`, `agent-python`, `new-langgraph-project-python`, `new-langgraph-project-js`
Run a local development server with hot reloading. No Docker required.
langgraph dev # default: localhost:2024 langgraph dev --port 8000 # custom port langgraph dev --config ./langgraph.json # explicit config path langgraph dev --no-reload # disable hot reload langgraph dev --no-browser # don't auto-open LangGraph Studio langgraph dev --host 0.0.0.0 # bind to all interfaces (trusted networks only) langgraph dev --tunnel # expose via Cloudflare tunnel for remote access langgraph dev --debug-port 5678 # enable remote debugger (requires debugpy) langgraph dev --n-jobs-per-worker 20 # max concurrent jobs per worker (default: 10)
Build a Docker image for the LangGraph API server.
langgraph build -t my-image # required: tag the image langgraph build -t my-image --no-pull # use locally-built base images langgraph build -t my-image -c langgraph.json # explicit config langgraph build -t my-image --base-image langchain/langgraph-server:0.2.18 # pin base version
Launch the LangGraph API server via Docker Compose (includes Postgres).
langgraph up # default port 8123 langgraph up --port 8000 # custom port langgraph up --watch # restart on file changes langgraph up --recreate # force fresh build (useful for pre-deploy validation) langgraph up --postgres-uri postgresql://... # external Postgres langgraph up --no-pull # use local images (after langgraph build) langgraph up --image my-image # skip build, use pre-built image langgraph up -d docker-compose.yml # add extra Docker services langgraph up --debugger-port 8124 # serve debugger UI langgraph up --wait # block until services are healthy
Build and deploy to LangGraph Platform (LangSmith Deployments). Requires Docker. On Apple Silicon (M1/M2/M3), Docker Buildx is also required for cross-compiling to `linux/amd64`.
langgraph deploy # deploy, name defaults to directory name langgraph deploy --name my-agent # explicit deployment name langgraph deploy --deployment-type prod # production deployment (default: dev) langgraph deploy --tag v1.2.0 # custom image tag (default: latest) langgraph deploy --deployment-id <id> # update an existing deployment by ID langgraph deploy --config ./langgraph.json # explicit config path langgraph deploy --no-wait # don't wait for deployment status langgraph deploy --verbose # show detailed server logs
Prereq: `LANGSMITH_API_KEY` in environment or `.env`.
`langgraph deploy` also accepts build flags: `--base-image`, `--pull`/`--no-pull`.
langgraph deploy list # list all deployments langgraph deploy list --name-contains bot # filter by name
langgraph deploy delete <deployment-id> # interactive confirmation langgraph deploy delete <deployment-id> --force # skip confirmation
langgraph deploy logs # runtime logs, last 100 langgraph deploy logs --name my-agent # by deployment name langgraph deploy logs --deployment-id <id> # by deployment ID langgraph deploy logs --type build # build logs instead of runtime langgraph deploy logs -f # follow/stream logs langgraph deploy logs --level error # filter by level (debu
⚠️ — This project is in early development. APIs and skill content may change. Agent skills for building agents with LangChain, LangGraph, and Deep Agents. For LangSmith-specific trace and dataset workflows, use langsmith-skills.
Repo: langchain-ai/langchain-skills
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