Skills

Chapter 11 of 22

LangChain Python Quickstart

Scaffold a minimal local LangChain agent in Python by following the official quickstart.

1 minute · 166 words · 1 sections

Follow the live docs — do not invent an alternate API from memory:

https://docs.langchain.com/oss/python/langchain/quickstart (opens in a new tab)

Fetch that page (Docs MCP or HTTP) and implement what it shows (weather agent + create_agent).

Local setup constraints

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:model string — 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.

Install this repository

$ npx skills add langchain-ai/langchain-skills

» /plugin marketplace add langchain-ai/langchain-skills

Skills install per repository, not per chapter — the CLI has no documented per-skill form, so we do not print one.

About this skill

Trigger

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.

The verbatim description from this skill’s front matter — the string an agent matches on to decide whether to load it.

Colophon for this issue

Colophon

How this issue was made

Source

github.com/langchain-ai/langchain-skills, branch main, last pushed 7 August 2026.

Licence

Discovery

22 chapters found by walking the repository tree for SKILL.md, not by matching a directory convention. One layout observed: config/skills/*/SKILL.md.

Issue colours

Resolved from a curated brand profile — hue 224°, chroma 0.190. Two accent tones are generated per issue and each is proven against its own ground before it ships: a single accent that passes AA on both light and dark paper is arithmetically impossible.

Heading repairs

1 repair applied to this chapter so the document has one h1 and no skipped levels:

Removed “LangChain Python quickstart”, a leading h1 that duplicated the chapter title.

Spec compliance

Every chapter satisfies the Agent Skills specification’s frontmatter rules.

Images

Images inside a chapter come from the upstream repository. Where the author gave no alternative text we mark the image decorative rather than inventing a description — a plausible caption we made up is worse than none for the reader who depends on it.

Marketplace

A plugin manifest is published at .claude-plugin/marketplace.json by LangChain, declaring 1 plugin. It is read for editorial metadata only — never as the skill index, which is always the repository tree.

Signal

Install counts come from skills.sh. They measure downloads, not quality, and an unranked repository is not an unread one.

Agent surfaces

The whole issue is available as one markdown document at /langchain-ai/langchain-skills.md, and each chapter at its own .md URL.

Publication

Set by Skills Docs from the source repository. Body text is Literata at the reader’s chosen size and measure; code is Geist Mono. Nothing on this page was written by us except this paragraph.

Local setup constraints

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:model string — 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.