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Found 1,637 Skills
Apply when implementing fulfillment, invoice, or tracking logic for VTEX marketplace seller connectors. Covers the External Seller fulfillment protocol: fulfillment simulation (checkout and indexation), order placement with reservation id, order dispatch (authorize fulfillment), OMS invoice and tracking APIs, and partial invoicing. Use for seller-side services that must answer within the simulation SLA and integrate with VTEX marketplace order management.
Configure Qdrant vector database for GrepAI. Use this skill for high-performance vector search.
Migrate phase directories to globally sequential numbering, fixing duplicate numeric prefixes across milestones. Triggers include "migrate phases", "fix phase numbers", "renumber phases", "phase collision", "fix phase collisions", "fix duplicate phases", "phase numbering migration".
File and directory management tool. Create, read, write, delete, move, copy files. Search for files, list directories, get file information. Keywords: file, directory, create, delete, copy, move, search, list
Apply quantization to reduce memory by 4-32x. Enable HNSW indexing for 150x faster search. Configure caching strategies and implement batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors. Deploy these optimizations to achieve 12,500x performance gains.
Anthropic's Contextual Retrieval technique for improved RAG. Use when chunks lose context during retrieval, implementing hybrid BM25+vector search, or reducing retrieval failures.
PostgreSQL-based semantic and hybrid search with pgvector and ParadeDB. Use when implementing vector search, semantic search, hybrid search, or full-text search in PostgreSQL. Covers pgvector setup, indexing (HNSW, IVFFlat), hybrid search (FTS + BM25 + RRF), ParadeDB as Elasticsearch alternative, and re-ranking with Cohere/cross-encoders. Supports vector(1536) and halfvec(3072) types for OpenAI embeddings. Triggers: pgvector, vector search, semantic search, hybrid search, embedding search, PostgreSQL RAG, BM25, RRF, HNSW index, similarity search, ParadeDB, pg_search, reranking, Cohere rerank, pg_trgm, trigram, fuzzy search, LIKE, ILIKE, autocomplete, typo tolerance, fuzzystrmatch
Implementing providers for Beluga AI v2 registries. Use when creating LLM, embedding, vectorstore, voice, or any other provider.
Write Playwright tests for Hyvä themes with Alpine.js components. This skill should be used when writing e2e tests, creating page objects, or debugging selector issues in Playwright tests for Hyvä Magento storefronts. Trigger phrases include "write playwright test", "playwright alpine", "test hyva page", "e2e test", "playwright selector".
Minimize unnecessary React re-renders when consuming external state (XState, @xstate/store, Zustand, Redux, Nanostores, context). Prefer selector-based subscriptions over useState(wholeObject). Use when dealing with external state in React, optimizing re-renders, choosing state patterns, or integrating with these libraries.
Full safety mode: destructive command warnings + directory-scoped edits. Combines /careful (warns before rm -rf, DROP TABLE, force-push, etc.) with /freeze (blocks edits outside a specified directory). Use for maximum safety when touching prod or debugging live systems. Use when asked to "guard mode", "full safety", "lock it down", or "maximum safety".
Build GraphRAG retrieval pipelines on Neo4j using the neo4j-graphrag Python package (formerly neo4j-genai). Covers retriever selection (VectorRetriever, HybridRetriever, VectorCypherRetriever, HybridCypherRetriever, Text2CypherRetriever), retrieval_query Cypher fragments, query_params, pipeline wiring (GraphRAG + LLM), embedder setup, index creation, and LangChain/LlamaIndex integration. Does NOT handle KG construction from documents — use neo4j-document-import-skill. Does NOT handle plain vector search — use neo4j-vector-index-skill. Does NOT handle GDS analytics — use neo4j-gds-skill. Does NOT handle agent memory — use neo4j-agent-memory-skill.