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Langchain Agent Builder

Checked
cnn-cnn-creatoe·vlatest·ai-ml

Build custom LangChain agents with pre-configured tools and memory for complex task automation.

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 cnn-cnn-creatoe/ai-health-assistant --skill langchain-agent-builder -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

cnn-cnn-creatoe

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 cnn-cnn-creatoe/ai-health-assistant at f1ab475a52.

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

Commit
f1ab475a52
Manifest
.cursor/skills/langchain-agent-builder/SKILL.md
Scanned
1 file, 246 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.
What each check looks for →

About this skill

What it does

The langchain-agent-builder skill facilitates the creation and configuration of LangChain agents. It allows users to define agent tools, prompts, and overall behavior through a structured process. This simplifies the development of complex AI agents capable of performing specific tasks by automating much of the setup.

When to use it

  • Rapid Agent Prototyping: Quickly build and test different agent configurations without extensive manual coding.
  • Complex Task Automation: Develop agents that can handle multi-step processes requiring interaction with various tools and data sources.
  • Customizable AI Assistants: Create specialized assistants tailored to specific domains or workflows, such as healthcare or customer service.
  • Agent Tool Integration: Easily integrate new tools into existing agent architectures by defining their capabilities within the builder.

Key capabilities

  • Agent tool definition
  • Prompt engineering and management
  • Automated agent configuration
  • Structured agent behavior design

Example prompts

  • "Create an agent that can summarize medical research papers."
  • "Build a customer service agent with access to our knowledge base and ticketing system."
  • "Configure an agent to monitor social media for brand mentions and report sentiment."

Tips & gotchas

  • Requires familiarity with LangChain concepts and terminology.
  • The effectiveness of the built agents depends heavily on the quality of defined tools and prompts.