Add Docs Page
langchain-ai/docs
Add, move, rename, or delete a page on the LangChain docs site.
Scaffold a minimal local LangChain agent in Python by following the official quickstart.
$ npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install langchain-ai/langchain-skills langchain-python-quickstart --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/langchain-ai/langchain-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/config/skills/langchain-python-quickstart .claude/skills/langchain-python-quickstart && 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 "langchain-python-quickstart" agent skill from https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstart into .claude/skills/langchain-python-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-python-quickstart", 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/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstartType 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 langchain-ai/langchain-skills --skill langchain-python-quickstart -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install langchain-ai/langchain-skills langchain-python-quickstart --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/config/skills/langchain-python-quickstart .agents/skills/langchain-python-quickstart && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "langchain-python-quickstart" agent skill from https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstart into .agents/skills/langchain-python-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-python-quickstart", 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 langchain-ai/langchain-skills --skill langchain-python-quickstart -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install langchain-ai/langchain-skills langchain-python-quickstart --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/config/skills/langchain-python-quickstart .cursor/skills/langchain-python-quickstart && 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 "langchain-python-quickstart" agent skill from https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstart into .cursor/skills/langchain-python-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-python-quickstart", 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/langchain-ai/langchain-skills.git --path config/skills/langchain-python-quickstart--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 langchain-ai/langchain-skills --skill langchain-python-quickstart -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install langchain-ai/langchain-skills langchain-python-quickstart --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/config/skills/langchain-python-quickstart .gemini/skills/langchain-python-quickstart && 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 "langchain-python-quickstart" agent skill from https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstart into .gemini/skills/langchain-python-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-python-quickstart", 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 langchain-ai/langchain-skills langchain-python-quickstartInstalls 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 langchain-ai/langchain-skills --skill langchain-python-quickstart -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/config/skills/langchain-python-quickstart .github/skills/langchain-python-quickstart && 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 "langchain-python-quickstart" agent skill from https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstart into .github/skills/langchain-python-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-python-quickstart", 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 langchain-ai/langchain-skills --skill langchain-python-quickstart -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install langchain-ai/langchain-skills langchain-python-quickstart --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/langchain-ai/langchain-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/config/skills/langchain-python-quickstart .opencode/skills/langchain-python-quickstart && 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 "langchain-python-quickstart" agent skill from https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstart into .opencode/skills/langchain-python-quickstart/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "langchain-python-quickstart", 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.
langchain-python-quickstartScaffold a minimal local LangChain agent in Python by following the official quickstart.
Langchain Python Quickstart is an agent skill from langchain-ai/langchain-skills, published by the product's own GitHub organization. Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally.
Its SKILL.md is about 370 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Building AI agents. It works with LangChain, Python and LangSmith. The licence is MIT.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 16a992f. It shows what the files ask for, not the result of running them.
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.
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.
Links to these hosts (documentation or services it may open):
docs.langchain.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Langchain Python Quickstart loads about 368 tokens when it runs. Until then it costs about 48 tokens; SKILL.md has 164 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.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
3. Only secret: the provider API key in `.env` (gitignored). No LangSmith / Tavily unless they ask. Prefer they edit `.eAutomated 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.
The full file from langchain-ai/langchain-skills at commit 16a992f, republished under its MIT licence (© langchain-ai). 164 words, ~368 tokens.
.claude/skills/langchain-python-quickstart/SKILL.md (or your agent's skills folder).Follow the live docs — do not invent an alternate API from memory:
https://docs.langchain.com/oss/python/langchain/quickstart
Fetch that page (Docs MCP or HTTP) and implement what it shows (weather agent + create_agent).
Apply these on top of the quickstart (they keep setup minimal and model-agnostic):
Ask which provider/model to use. Showcase that LangChain is model-agnostic. Suggested prompt:
Which model should this agent use? Pass a
provider:modelstring — e.g.openai:gpt-5.5,anthropic:claude-sonnet-5,google_genai:gemini-2.5-flash-lite. Default if you're unsure:anthropic:claude-sonnet-5.
Swap the quickstart's model string for their choice (or the default).
Create a new directory (e.g. langchain-agent/) and do all work there — do not pollute the open project.
Only secret: the provider API key in .env (gitignored). No LangSmith / Tavily unless they ask. Prefer they edit .env themselves — don't paste keys into chat.
Install the provider package needed for their model if the quickstart's base install isn't enough.
Run the example, show output, then stop. Point to langchain-fundamentals for next steps.
© langchain-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in config/skills/langchain-python-quickstart of langchain-ai/langchain-skills.
Open the folder on GitHubat commit 16a992f
Langchain Python Quickstart 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 |
|---|---|---|---|---|---|---|
| Langchain Python Quickstart this skilllangchain-ai/langchain-skills | 1.3k | — | ~368 | Automated safety check: Notes | MIT | |
| Add Docs Pagelangchain-ai/docs | 424 | — | ~2k | Automated safety check: Pass | MIT | |
| Deepagents Setup Configurationsoba-labs/langchain-agent-skills | 107 | — | ~1.9k | Automated safety check: Pass | MIT | |
| Langgraph Testing Evaluationsoba-labs/langchain-agent-skills | 107 | — | ~2.3k | Automated safety check: Pass | MIT | |
| LangSmith Trace DebuggingComposioHQ/awesome-claude-skills | 77k | 9 repos | ~2.7k | Automated safety check: Pass | None | |
| Add Example AgentGetBindu/Bindu | 10k | — | ~1.1k | Automated safety check: Notes | Custom licence |
langchain-ai/docs
Add, move, rename, or delete a page on the LangChain docs site.
soba-labs/langchain-agent-skills
Initialize, validate, and troubleshoot Deep Agents projects in Python or JavaScript using the deepagents package.
soba-labs/langchain-agent-skills
A skill your agent uses when you need to test or evaluate LangGraph/LangChain agents: writing unit or integration tests, generating test scaffolds, mocking LLM/tool behavior, running trajectory…
ComposioHQ/awesome-claude-skills
Debugs LangChain and LangGraph agents by pulling recent execution traces with the langsmith-fetch CLI and reporting errors, tool calls, timings and token use.
GetBindu/Bindu
Add a new self-contained example agent under examples/. An agent skill from GetBindu/Bindu.
FailproofAI/failproofai
Helps instrument a custom Python or TypeScript agent to record events for Failproof AI, verify what gets written, and run an evaluator worker that scores the runs.
langchain-ai/langchain-skills
Builds agent evaluations in stages: inspect the repository and traces, agree a Task Spec with you, then build, audit and run a Harbor task with an independent verifier.
langchain-ai/langchain-skills
INVOKE THIS SKILL when implementing human-in-the-loop patterns, pausing for approval, or handling errors in LangGraph.
langchain-ai/langchain-skills
Fans a list of independent items out to subagents in parallel, merges the results back into a table and supports retrying only the rows that failed.
langchain-ai/langchain-skills
Routes LangGraph agents with typed decision models that return probabilities, and finds LLM calls that only exist to produce a routing decision.
langchain-ai/langchain-skills
Explains how to build agents with the Deep Agents framework: create_deep_agent, the built-in middleware, the harness, SKILL.md format and configuration options.
langchain-ai/langchain-skills
INVOKE THIS SKILL when setting up a new project or when asked about package versions, installation, or dependency management for LangChain, LangGraph, LangSmith, or Deep Agents.
Categories
Scaffold a minimal local LangChain agent in Python by following the official quickstart. Langchain Python Quickstart is an agent skill from langchain-ai/langchain-skills, published by the product's own GitHub organization. Scaffold a minimal local LangChain agent in Python by following the official quickstart.
Langchain Python Quickstart fits situations like: the user wants to quickly build; try a LangChain agent locally.
Run `npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -a claude-code`. Or copy the skill folder (config/skills/langchain-python-quickstart in langchain-ai/langchain-skills) into .claude/skills/langchain-python-quickstart in your project. Claude Code loads it when a task matches its description.
Run `npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -a codex`. Or copy the skill folder (config/skills/langchain-python-quickstart in langchain-ai/langchain-skills) into .agents/skills/langchain-python-quickstart in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/langchain-python-quickstart, .gemini/skills/langchain-python-quickstart, .github/skills/langchain-python-quickstart and .opencode/skills/langchain-python-quickstart in your project.
SKILL.md names no scripts, command-line tools or credentials: Langchain Python Quickstart is instructions for the agent only. Our summary lists: Python 3.
SKILL.md names 1 domain. As links in the text: docs.langchain.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Langchain Python Quickstart is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 368 tokens (SKILL.md is roughly 1.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Langchain Python Quickstart: Add Docs Page (langchain-ai/docs, 424 stars), Deepagents Setup Configuration (soba-labs/langchain-agent-skills, 107 stars), Langgraph Testing Evaluation (soba-labs/langchain-agent-skills, 107 stars) and LangSmith Trace Debugging (ComposioHQ/awesome-claude-skills, 77k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
langchain-ai (a GitHub organization, an official publisher) maintains it in langchain-ai/langchain-skills, which has 1,270 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 5, 2026.
Source: langchain-ai/langchain-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.