langchain-ai/langchain-python-quickstart
config/skills/langchain-python-quickstart/SKILL.md
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.
$ install --global
skillsauthnpx skillsauth add langchain-ai/langchain-skills langchain-python-quickstartInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
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CrowdStrikeAdvanced threat intelligence
50%
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OSV-ScannerOpen Source Vulnerability database check
50%
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OWASP Dep-Check
50%
Last scanned: Jul 30, 2026, 2:05 AM286.1s1 file scanned
SKILL.md
- name:
- langchain-python-quickstart
- description:
- 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.
LangChain Python quickstart
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).
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: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.envthemselves — 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-fundamentalsfor next steps.
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