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Grepai Chunking

Checked
yoanbernabeu·vlatest·other·MIT

Grepai Chunking efficiently breaks down large text into manageable segments for analysis and processing, boosting workflow speed.

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-chunking -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.

Commit
382d40261c
Manifest
skills/indexing/grepai-chunking/SKILL.md
Scanned
1 file, 286 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-chunking skill allows you to split large text inputs into smaller, more manageable chunks. This is useful for processing documents that exceed the context window limitations of language models or when specific sections need individual analysis. It helps improve performance and accuracy by breaking down complex tasks into simpler steps.

When to use it

  • Summarizing long documents: Break a lengthy report into sections before summarizing each part individually.
  • Analyzing large codebases: Divide a codebase into smaller files or functions for better understanding and error detection.
  • Processing legal contracts: Split a complex contract into clauses for detailed review and analysis.
  • Extracting information from books: Segment a book chapter by chapter to extract key themes or characters.

Key capabilities

  • Text chunking based on specified size.
  • Handles large text inputs exceeding context window limits.
  • Enables processing of documents in smaller, more manageable pieces.

Example prompts

  • "Chunk this document into sections of 500 tokens."
  • "Divide the following code file into functions for analysis."
  • "Split this legal contract into individual clauses."

Tips & gotchas

  • Ensure your AI agent has sufficient memory to handle the resulting chunks.
  • Consider overlap between chunks to maintain context and avoid information loss.