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Grepai Quickstart

Listed
yoanbernabeu·vlatest·other·MIT

Grepai Quickstart rapidly generates and executes complex GrepAI queries for instant data extraction and analysis.

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 yoanbernabeu/grepai-skills --skill grepai-quickstart -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 failed 2 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: ollama.com.

    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.

    Hosts contacted

    raw.githubusercontent.comsource hostollama.comundeclared

    What it found

    • skills/getting-started/grepai-quickstart/SKILL.md:57contacts ollama.com
      curl -fsSL https://ollama.com/install.sh | sh

  • No pipe-to-shell installers: failed

    Runs code fetched at install time in 2 places.

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

    What it found

    • skills/getting-started/grepai-quickstart/SKILL.md:33remote script piped into a shell
      curl -sSL https://raw.githubusercontent.com/yoanbernabeu/grepai/main/install.sh | sh
    • skills/getting-started/grepai-quickstart/SKILL.md:57remote script piped into a shell
      curl -fsSL https://ollama.com/install.sh | sh

  • 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 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.

  • 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.

Commit
382d40261c
Manifest
skills/getting-started/grepai-quickstart/SKILL.md
Scanned
1 file, 225 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

This skill provides a quick-start foundation for integrating GrepAI capabilities into AI agents, enabling rapid setup and configuration of text search and retrieval workflows. It streamlines the initial deployment process to help agents efficiently locate and analyze specific information within large codebases or document sets.

When to use it

  • You need to rapidly prototype an AI agent that performs semantic search over unstructured text data.
  • Your project requires a lightweight entry point for implementing GrepAI logic without extensive boilerplate code.
  • You are setting up a new repository and want to establish standard GrepAI configuration practices immediately.
  • You need to validate GrepAI integration patterns before scaling to more complex, production-grade retrieval architectures.

Key capabilities

  • Rapid initialization of GrepAI environments for AI agents.
  • Simplified configuration workflows for text indexing and querying.
  • Foundation support for semantic search operations within agent workflows.
  • Standardized setup patterns for consistent agent behavior across projects.

Example prompts

  • "Initialize a new GrepAI quickstart environment for my code analysis agent."
  • "Configure the basic retrieval pipeline using the grepai-quickstart skill for document search."
  • "Set up a minimal GrepAI instance to index and query my project documentation."

Tips & gotchas

Ensure your AI agent has access to the necessary text indexing libraries before relying on this quick-start configuration. While this skill accelerates setup, complex retrieval scenarios may require additional customization beyond the initial defaults.