Agent skill · software engineering · secondsky
cloudflare-vectorize
Cloudflare Vectorize vector database for semantic search and RAG. Use for vector indexes, embeddings, similarity search, or encountering dimension mismatches, filter errors.
Why this skill is useful
Adds executable scripts for managing vector indexes and performing semantic searches that are not commonly found in public documentation.
What it needs
Requires wrangler installed locally. Requires cloudflare account access. About 7k tokens when loaded. Last updated 2026-08-06. 204 stars on the source repository.
What this skill does
Cloudflare Vectorize Complete implementation guide for Cloudflare Vectorize - a globally distributed vector database for building semantic search, RAG (Retrieval Augmented Generation), and AI-powered applications with Cloudflare Workers. Status: Production Ready ✅ Last Updated: 2025-11-21 Dependencies: cloudflare-worker-base (for Worker setup), cloudflare-workers-ai (for embeddings) Latest Versions: wrangler@4.81.0, @cloudflare/workers-types@4.20260408.0 Token Savings: ~65% Errors Prevented: 8 Dev Time Saved: ~3 hours What This Skill Provides Core Capabilities ✅ Index Management: Create, configure, and manage vector indexes ✅ Vector Operations: Insert, upsert, query, delete, and list vectors ✅ Metadata Filtering: Advanced filtering with 10 metadata indexes per index ✅ Semantic Search: Find similar vectors using cosine, euclidean, or dot-product metrics ✅ RAG Patterns: Complete retrieval-augmented generation workflows ✅ Workers AI Integration: Native embedding generation with @cf/baai/bge-base-en-v1.5 ✅ OpenAI Integration: Support for text-embedding-3-small/large models ✅ Document Processing: Text chunking and batch ingestion pipelines Templates Included 1. basic-search.ts - Simple vector search with Workers AI 2. rag-chat.ts - Full RAG chatbot with context retrieval 3. document-ingestion.ts - Document chunking and embedding pipeline 4. metadata-filtering.ts - Advanced filtering examples Critical Setup Rules ⚠️ MUST DO BEFORE INSERTING VECTORS Why: Metadata indexes MUST exist before vectors are inserted. Vectors added before a metadata index was created won't be filterable on that property. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills secondsky/cloudflare-vectorize