Langgraph
davila7/claude-code-templates
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications.
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications.
Install Langgraph
$ npx skills add sickn33/agentic-awesome-skills --skill langgraph -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sickn33/agentic-awesome-skills langgraph --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/langgraph .claude/skills/langgraph && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "langgraph" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/langgraph into .claude/skills/langgraph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langgraph", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/langgraphType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add sickn33/agentic-awesome-skills --skill langgraph -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sickn33/agentic-awesome-skills langgraph --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/langgraph .agents/skills/langgraph && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "langgraph" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/langgraph into .agents/skills/langgraph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langgraph", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill langgraph -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sickn33/agentic-awesome-skills langgraph --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/langgraph .cursor/skills/langgraph && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "langgraph" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/langgraph into .cursor/skills/langgraph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langgraph", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/sickn33/agentic-awesome-skills.git --path skills/langgraph--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add sickn33/agentic-awesome-skills --skill langgraph -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sickn33/agentic-awesome-skills langgraph --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/langgraph .gemini/skills/langgraph && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "langgraph" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/langgraph into .gemini/skills/langgraph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langgraph", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install sickn33/agentic-awesome-skills langgraphInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add sickn33/agentic-awesome-skills --skill langgraph -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/langgraph .github/skills/langgraph && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "langgraph" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/langgraph into .github/skills/langgraph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langgraph", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill langgraph -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install sickn33/agentic-awesome-skills langgraph --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/langgraph .opencode/skills/langgraph && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "langgraph" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/langgraph into .opencode/skills/langgraph/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langgraph", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
langgraph- GitHub stars
- 47k
- Used in
- 2 other repos
- Token cost
- ~639 tokens
- SKILL.md length
- 282 words
- Files
- 2 (incl. references)
- Skills in repo
- 1,354
- Repo updated
- First seen
- Licence
- MIT
At a glance
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications.
- Tasks that involve Building AI agents
- SKILL.md covers Detailed Guide, Prerequisites, When to Use and Limitations
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Tasks that involve State management
What it does
Langgraph is an agent skill from sickn33/agentic-awesome-skills. Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern.
Its SKILL.md is about 640 tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/detailed-guide.md`).
It sits in AI & LLM Engineering, covering Building AI agents, State management and Human-in-the-loop approvals. It works with LangGraph and React. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.
When your agent uses it
- Tasks that involve Building AI agents
- Tasks that involve State management
- Tasks that involve Human-in-the-loop approvals
Example prompts
- “/langgraph”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit ec02547. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Langgraph loads about 639 tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 67 tokens; SKILL.md has 282 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from sickn33/agentic-awesome-skills at commit ec02547, republished under its MIT licence (© sickn33). 282 words, ~639 tokens.
Download SKILL.mdSave it as
.claude/skills/langgraph/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- langgraph
- description
- Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern.
- risk
- critical
- source
- vibeship-spawner-skills (Apache 2.0)
- date_added
- 2026-02-27
LangGraph
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents.
Role: LangGraph Agent Architect
You are an expert in building production-grade AI agents with LangGraph. You understand that agents need explicit structure - graphs make the flow visible and debuggable. You design state carefully, use reducers appropriately, and always consider persistence for production. You know when cycles are needed and how to prevent infinite loops.
Expertise
- Graph topology design
- State schema patterns
- Conditional branching
- Persistence strategies
- Human-in-the-loop
- Tool integration
- Error handling and recovery
Detailed Guide
Read the detailed guide before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.
Prerequisites
- 0: Python proficiency
- 1: LLM API basics
- 2: Async programming concepts
- 3: Graph theory fundamentals
- Required skills: Python 3.9+, langgraph package, LLM API access (OpenAI, Anthropic, etc.), Understanding of graph concepts
When to Use
- User mentions or implies: langgraph
- User mentions or implies: langchain agent
- User mentions or implies: stateful agent
- User mentions or implies: agent graph
- User mentions or implies: react agent
- User mentions or implies: agent workflow
- User mentions or implies: multi-step agent
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file (references) in skills/langgraph of sickn33/agentic-awesome-skills.
- SKILL.md
- references/detailed-guide.md
Open the folder on GitHubat commit ec02547
Used in 2 other repositories
We found 13 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Langgraph next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Langgraph this skillsickn33/agentic-awesome-skills | 47k | 2 repos | ~639 | Automated safety check: Pass | MIT | |
| Langgraphdavila7/claude-code-templates | 32k | 6 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Langgraphmagnus919/agent-skills | 113 | — | ~2.8k | Automated safety check: Pass | MIT | |
| Dive Into LangGraphluochang212/dive-into-langgraph | 457 | — | ~837 | Automated safety check: Notes | Custom licence | |
| Langgraph Human In The Looplangchain-ai/langchain-skills | 1.3k | 2 repos | ~4.1k | Automated safety check: Pass | MIT | |
| Deep Agents Corelangchain-ai/langchain-skills | 1.3k | 1 repos | ~3.1k | Automated safety check: Pass | MIT |
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Questions about Langgraph
What does Langgraph do?
Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Langgraph is an agent skill from sickn33/agentic-awesome-skills. Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications.
When should I use Langgraph?
Langgraph fits situations like: tasks that involve Building AI agents; tasks that involve State management; tasks that involve Human-in-the-loop approvals.
How do I install Langgraph in Claude Code?
Run `npx skills add sickn33/agentic-awesome-skills --skill langgraph -a claude-code`. Or copy the skill folder (skills/langgraph in sickn33/agentic-awesome-skills) into .claude/skills/langgraph in your project. Claude Code loads it when a task matches its description.
How do I install Langgraph in Codex?
Run `npx skills add sickn33/agentic-awesome-skills --skill langgraph -a codex`. Or copy the skill folder (skills/langgraph in sickn33/agentic-awesome-skills) into .agents/skills/langgraph in your project. Codex loads it when a task matches its description.
Can I use Langgraph in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill langgraph -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langgraph, .gemini/skills/langgraph, .github/skills/langgraph and .opencode/skills/langgraph in your project.
What does Langgraph need to run?
SKILL.md names no scripts, command-line tools or credentials: Langgraph is instructions for the agent only. Our summary lists: Python 3.
Does Langgraph access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Langgraph safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Langgraph use?
Langgraph is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Langgraph use?
About 639 tokens (SKILL.md is roughly 2.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.8k tokens, read only when the agent opens those files.
What are the alternatives to Langgraph?
Skills that share tags, products or a category with Langgraph: Langgraph (davila7/claude-code-templates, 32k stars), Langgraph (magnus919/agent-skills, 113 stars), Dive Into LangGraph (luochang212/dive-into-langgraph, 457 stars) and Langgraph Human In The Loop (langchain-ai/langchain-skills, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Langgraph?
sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,343 GitHub stars. The repository holds 1,354 skills in this directory. The repository was last updated on October 7, 2026.
Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.