Agent skill · software engineering · sickn33
langchain-architecture
Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration.
Why this skill is useful
Adds specific LangChain architecture patterns and executable scripts for building LLM applications that the AI wouldn't generate on its own.
What it needs
Requires langchain installed locally. About 5k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
Supporting material availability This catalog copy contains the inline guidance below, but does not include the following supporting paths. They are external prerequisites, not bundled files: <support-root>/references/agents.md <support-root>/references/memory.md <support-root>/references/chains.md <support-root>/references/document-processing.md <support-root>/references/callbacks.md <support-root>/assets/agent-template.py <support-root>/assets/memory-config.yaml <support-root>/assets/chain-example.py Ask for the original supporting material or an existing installation before using a step that depends on these paths; this catalog does not identify a verified download source for them. Resolve each path relative to that installation, inspect its contents, and verify any applicable license and execution prerequisites. Do not run a command or claim a referenced procedure was followed until its required file exists. Do not fabricate the missing scripts or treat an unrelated file with the same name as equivalent. Independent steps fully documented here can proceed within the user’s authorized scope; report any dependent step as unavailable. LangChain Architecture Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration. Do not use this skill when The task is unrelated to langchain architecture You need a different domain or tool outside this scope Instructions Clarify goals, constraints, and required inputs. Apply relevant best practices and validate outcomes. Provide actionable steps and verification. Use this skill when Building autonomous AI agents with tool access Implementing complex multi-step LLM workflows Managing conversation memory and state Integrating LLMs with external data sources and APIs Creating modular, reusable LLM application components Implementing document processing pipelines Building production-grade LLM applications Core Concepts 1. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/langchain-architecture--cbd777