rag-content-chunker
CommunityEfficiently split documents into optimal chunks for RAG pipelines.
Authorlabrat-0
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill automates the process of dividing large texts and web documents into manageable, token-aware chunks, facilitating faster and more accurate retrieval-augmented generation.
Core Features & Use Cases
- Structured Text Chunking: Supports strategies like recursive, Markdown-aware, and sentence-based splitting tailored for diverse content types.
- Deterministic ID Generation: Produces consistent, SHA-256-based identifiers for incremental updates in vector databases.
- Use Case: Perfect for breaking down lengthy web pages or documentation before embedding for search indexing or conversational agents.
Quick Start
Use the chunker to process a lengthy Markdown file, producing token-sized segments ready for embedding.
Dependency Matrix
Required Modules
tiktokenhtml.parserhashlib
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: rag-content-chunker Download link: https://github.com/labrat-0/rag-content-chunker/archive/main.zip#rag-content-chunker Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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