Agent skill · software engineering · aiskillstore
cocoindex
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.
Why this skill is useful
Adds executable scripts for building ETL workflows and managing data transformation pipelines that are not commonly found in public documentation.
What it needs
Requires cocoindex installed locally. About 9k tokens when loaded. Last updated 2026-08-07. 405 stars on the source repository.
What this skill does
CocoIndex Overview CocoIndex is an ultra-performant real-time data transformation framework for AI with incremental processing. This skill enables building indexing flows that extract data from sources, apply transformations (chunking, embedding, LLM extraction), and export to targets (vector databases, graph databases, relational databases). Core capabilities: 1. Write indexing flows - Define ETL pipelines using Python 2. Create custom functions - Build reusable transformation logic 3. Operate flows - Run and manage flows using CLI or Python API Key features: Incremental processing (only processes changed data) Live updates (continuously sync source changes to targets) Built-in functions (text chunking, embeddings, LLM extraction) Multiple data sources (local files, S3, Azure Blob, Google Drive, Postgres) Multiple targets (Postgres+pgvector, Qdrant, LanceDB, Neo4j, Kuzu) For detailed documentation: <https://cocoindex.io/docs/> Search documentation: <https://cocoindex.io/docs/search?q=url%20encoded%20keyword> When to Use This Skill Use when users request: "Build a vector search index for my documents" "Create an embedding pipeline for code/PDFs/images" "Extract structured information using LLMs" "Build a knowledge graph from documents" "Set up live document indexing" "Create custom transformation functions" "Run/update my CocoIndex flow" Flow Writing Workflow Step 1: Understand Requirements Ask clarifying questions to understand: Data source: Where is the data? (local files, S3, database, etc.) What file types? (text, PDF, JSON, images, code, etc.) How often does it change? (one-time, periodic, continuous) Transformations: What processing is needed? (chunking, embedding, extraction, etc.) Which embedding model? (SentenceTransformer, OpenAI, custom) Any custom logic? (filtering, parsing, enrichment) Target: Where should results go? (Postgres, Qdrant, Neo4j, etc.) What schema? (fields, primary keys, indexes) Vector search needed? (specify similarity metric) Step 2: Se …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills aiskillstore/cocoindex--f7cc59