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langchain-ai/docs

SkillsMP has collected 9 skills from langchain-ai/docs. Open a skill to review its source and details.

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skills collected
9
GitHub stars
402
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2,660

Skills in this repository

2 occupation categories · 89% classified

Showing 9 of 9 collected skills.

occupation
unclassified
description

Fetches and references LangGraph Python documentation to build stateful agents, create multi-agent workflows, and implement human-in-the-loop patterns. Use when the user asks about LangGraph, graph agents, state machines, agent orchestration, LangGraph API,…

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occupation
Software Developers
description

Use this skill when migrating inline code samples from LangChain docs (MDX files) into external, testable code files that are extracted by this repo’s snippet scripts and used as Mintlify snippets. Applies when extracting code blocks from documentation,…

updated
occupation
Software Developers
description

Process open LangChain docs integration PRs against the hosted-guide featuring policy (50K monthly downloads or maintainer feature override). Rebase an integration PR, convert to external YAML, feature an integration, or check package downloads for docs…

updated
occupation
Software Developers
description

Build agents with a prebuilt architecture and integrations for any model or tool. Use when creating tool-calling agents, switching model providers, or adding structured output.

updated
occupation
Software Developers
description

Build batteries-included agents with planning, context management, subagent delegation, and sandboxed execution. Use for complex, multi-step tasks that need built-in capabilities.

updated
occupation
Software Developers
description

Build stateful, durable agent workflows with LangGraph. Use when you need custom graph-based control flow, human-in-the-loop, persistence, or multi-agent orchestration.

updated
occupation
Data Scientists
description

Common pandas and matplotlib patterns for data analysis and visualization

updated
occupation
Software Developers
description

Trace, evaluate, and deploy AI agents and LLM applications with LangSmith. Use when adding observability, running evaluations, engineering prompts, or deploying agents to production.

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occupation
Software Developers
description

Use when the user wants the current date and time written to a file via the bundled script inside the sandbox.

updated
Showing 9 of 9 collected skills.