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[STUB - Not implemented] Intelligent document chunking and ingestion with multiple strategies for Vertex AI RAG Engine. PROACTIVELY activate for: [TODO: Define on implementation]. Triggers: [TODO: Define on implementation]
How this skill is triggered — by the user, by Claude, or both
Slash command
/rag-tools:intelligent-ingestionThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
> **STUB: This skill is not yet implemented**
STUB: This skill is not yet implemented
This placeholder preserves the documented plugin structure. See parent plugin README for planned capabilities.
npx claudepluginhub agentient/vibekit --plugin rag-toolsDocument chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user mentions chunking, text splitting, document segmentation, RAG optimization, or chunk evaluation.
Provides chunking strategies for RAG document processing pipelines: fixed-size, semantic, recursive methods with Python examples, document-type recommendations, and best practices.
Generates chunking strategies for RAG systems: 256-1024 token sizes, 10-20% overlaps, semantic boundaries; validates coherence and evaluates precision/recall metrics. For vector DBs and large documents.