Comprehensive toolkit for developing with the CocoIndex library. Use when users need to create data transformation pipelines (flows), write custom functions, or operate flows via CLI or API. Covers building ETL workflows for AI data processing, including embedding documents into vector databases, building knowledge graphs, creating search indexes, or processing data streams with incremental updates.
8.7
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Excellent comprehensive skill for CocoIndex ETL/data pipeline development. The Description clearly articulates when to use the skill (vector search, embeddings, knowledge graphs, live indexing). SKILL.md provides a well-structured workflow (understand requirements → setup → write flow → test) with critical guidance on environment setup, LLM API keys, type systems, and common pitfalls. Task knowledge is extensive, covering flow patterns, custom functions, CLI/API operations, built-in functions, sources/targets, and troubleshooting. Structure is clean with a concise main file and detailed references for patterns, custom functions, CLI, and API operations. Novelty is high: building incremental ETL pipelines with embeddings, LLM extraction, and vector databases requires significant domain expertise and many tokens for a CLI agent to accomplish from scratch. Minor improvements possible: slightly more explicit indexing of reference files in main overview, and perhaps a quickstart example earlier in the document.
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