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Grepai Init

Checked
yoanbernabeu·vlatest·agents·MIT

Grepai Init initializes a Grepai session for efficient data extraction and analysis from various sources, streamlining workflows.

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 yoanbernabeu/grepai-skills --skill grepai-init -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

yoanbernabeu

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 yoanbernabeu/grepai-skills at 382d40261c.

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

Scanned
1 file, 227 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 grepai-init skill provides a way to discover and install skills for AI agents. It allows users to easily find and integrate pre-built functionalities into their AI workflows, streamlining development and deployment processes. This skill simplifies the onboarding of new capabilities without requiring extensive coding or configuration.

When to use it

  • You want to quickly add new features to your AI agent without building them from scratch.
  • You are exploring different AI agent skills and need a simple way to try them out.
  • You're setting up a new AI project and want to leverage existing, tested skill components.
  • You’re looking for a centralized location to manage and deploy AI agent skills.

Key capabilities

  • Skill discovery
  • Skill installation
  • AI agent workflow integration

Example prompts

  • "Install the latest version of the 'grepai-init' skill."
  • "Show me available skills that can be installed."
  • "What are the dependencies for installing this skill?"

Tips & gotchas

Ensure your AI agent environment is compatible with the grepai-init skill before attempting installation. The specific supported versions and configurations will vary depending on the underlying platform.