LangChain Skills is a collection of agent skills for building software agents with LangChain, LangGraph, and Deep Agents. Coding agents that support the Agent Skills specification, including Claude Code, Cursor, and Windsurf, can install and use these skills. The catalogue lists the project's skills and its Claude Code plugin.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add langchain-ai/langchain-skills --skill langgraph-cligit clone --depth 1 https://github.com/langchain-ai/langchain-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/langchain-ai/langchain-skills/langgraph-cli)<a href="https://agentmods.dev/skills/langchain-ai/langchain-skills/langgraph-cli"><img src="https://agentmods.dev/badge/skills/langchain-ai/langchain-skills/langgraph-cli/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/langchain-ai/langchain-skills/langgraph-cli"><img src="https://agentmods.dev/badge/skills/langchain-ai/langchain-skills/langgraph-cli.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 8 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 156 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 171 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 183 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 196 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- medium MCP Rug Pull · line 41 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium MCP Rug Pull · line 245 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
- medium Excessive Agency · line 54 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 133 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00048 | $0.02674 |
| Opus 5.5 | $0.00019 | $0.01070 |
| Sonnet 5.5 | $0.00010 | $0.00535 |
| Haiku 4.5 | $0.00005 | $0.00267 |
Grade A, and why
langgraph-cli scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Key commands:
langgraph new— Scaffold a project from a templatelanggraph dev— Run locally with hot reload (no Docker)langgraph build— Build a Docker imagelanggraph up— Launch locally via Docker Composelanggraph deploy— Ship to LangGraph Platformlanggraph dockerfile— Generate a Dockerfile
All commands (except new) read from a langgraph.json config file in the project root.
When to use
Use this skill when the user wants to:
- Scaffold a new LangGraph project
- Run a local development or production-like server
- Build or deploy a LangGraph application
- Understand or edit
langgraph.jsonconfiguration - Manage LangSmith Deployments (list, delete, view logs)
Installation
# 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)
Commands
langgraph new [PATH]
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
langgraph dev
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)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 247 lines · 48 tokens per session scan A 59bfeb9204cf
langgraph-cli is a skill published in the GitHub repository langchain-ai/langchain-skills (1,313 stars, last pushed 4d ago), licensed MIT. It adds 48 tokens to every session and 2,674 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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