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Barrel Export

Checked
forge-town·vlatest·frontend·MIT

This skill exports data from a barrel object to various formats for seamless integration and analysis.

Install on your platform

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

Installs under a different name. Its SKILL.md names it forge_check-barrel-export, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add forge-town/skills --skill forge_check-barrel-export -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

forge-town

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 forge-town/skills at ebab1e170c.

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

Scanned
2 files, 29 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 barrel-export skill allows you to discover and install skills for AI agents. It provides a platform for finding, installing, and managing these agent capabilities. This facilitates the expansion of an AI agent's functionality through reusable components.

When to use it

  • You want to extend your AI agent’s capabilities with pre-built functionalities.
  • You are looking for skills created by other developers to integrate into your projects.
  • You need a centralized location to manage and track the skills used by your AI agents.
  • You're exploring ways to modularize and reuse components within your AI agent workflows.

Key capabilities

  • Skill discovery: Find available skills from various creators.
  • Skill installation: Easily integrate selected skills into an AI agent environment.
  • Skill management: Track and organize the installed skills.

Example prompts

  • "Find me skills related to data analysis."
  • "Install the latest version of a skill for image recognition."
  • "Show me all available skills from forge-town."

Tips & gotchas

The platform requires an understanding of AI agent architecture and how to integrate external components. Ensure compatibility between installed skills and your existing agent environment before deployment.