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Found 1,163 Skills
JOOQ type-safe SQL patterns - use for database queries, repositories, complex SQL operations, and PostgreSQL-specific features
Use when analyzing FileMaker DDR to extract calculations, custom functions, and business logic for PostgreSQL import processes or maintenance scripts - focuses on understanding and adapting FileMaker logic rather than direct schema migration
T-SQL query optimization techniques for SQL Server and Azure SQL Database. Use this skill when: (1) User needs to optimize slow queries, (2) User asks about SARGability or index seeks, (3) User needs help with query hints, (4) User has parameter sniffing issues, (5) User needs to understand execution plans, (6) User asks about statistics and cardinality estimation.
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
Implement PostgreSQL Row Level Security (RLS) for multi-tenant SaaS applications. Use when building apps where users should only see their own data, or when implementing organization-based data isolation.
Automates Apple Voice Memos (Mac Catalyst, no dictionary) via JXA using filesystem/SQLite access and System Events UI scripting. Use when asked to "automate Voice Memos", "export voice recordings", "access Voice Memos database", or "transcribe voice memos".
Patterns and best practices for using Lakebase Autoscaling (next-gen managed PostgreSQL) with autoscaling, branching, scale-to-zero, and instant restore.
MUST USE when installing chv, setting up local ClickHouse development, or running ClickHouse locally. Contains 5 guides covering chv CLI installation, local project initialization, running a local server, executing SQL from files, and migrating to cloud. Always read relevant guide files and cite them in responses.
Plan and build production-ready FastAPI endpoints with async SQLAlchemy, Pydantic v2 models, dependency injection for auth, and pytest tests. Uses interview-driven planning to clarify data models, authentication method, pagination strategy, and caching before writing any code.
Fast in-process analytical database for SQL queries on DataFrames, CSV, Parquet, JSON files, and more. Use when user wants to perform SQL analytics on data files or Python DataFrames (pandas, Polars), run complex aggregations, joins, or window functions, or query external data sources without loading into memory. Best for analytical workloads, OLAP queries, and data exploration.
Master data engineering, ETL/ELT, data warehousing, SQL optimization, and analytics. Use when building data pipelines, designing data systems, or working with large datasets.
PostgreSQL optimization including indexes, query plans, partitioning, JSONB operations, and connection pooling