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Langchain Architecture

Checked
wshobson·vlatest·ai-ml·MIT

Designs and optimizes LangChain application architectures, including agents, chains, and memory structures, for improved performance.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add wshobson/agents --skill langchain-architecture -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

wshobson

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned wshobson/agents at 46891e7e60.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
46891e7e60
Manifest
plugins/llm-application-dev/skills/langchain-architecture/SKILL.md
Scanned
2 files, 607 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

What it does

The langchain-architecture skill provides a framework for building and managing AI agents using LangChain, enabling modular, scalable, and customizable agent architectures. It supports integration with various language models, memory systems, and tools to create complex workflows.

When to use it

  • When designing an AI agent that requires multiple steps or decision points.
  • To integrate different components like chat models, databases, or APIs into a single agent workflow.
  • For projects requiring reusable agent modules or custom agent logic.
  • When building applications that need persistent memory or state management for agents.

Key capabilities

  • Modular agent design with LangChain components
  • Integration with multiple language models and tools
  • Support for memory systems to retain context across interactions
  • Customizable agent behavior through prompt engineering

Example prompts

  • "Create an AI agent that fetches weather data using a specific API."
  • "Design an agent workflow that includes a chat model, database query tool, and memory system."
  • "Build an agent that can handle multi-step tasks with decision-making logic."

Tips & gotchas

  • Ensure LangChain is properly installed and configured before using this skill.
  • Complex agent workflows may require careful tuning of prompts and tools for optimal performance.