ReddRadar
Topic: claude-plugin
435 skills in this topic.
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pgvector-semantic-search
Use this skill for setting up vector similarity search with pgvector for AI/ML embeddings, RAG applications, or semantic search.
**Trigger when user asks to:**
- Store or search vector embeddings in PostgreSQL
- Set up semantic search, similarity search, or nearest neighbor search
- Create HNSW or IVFFlat indexes for vectors
- Implement RAG (Retrieval Augmented Generation) with PostgreSQL
- Optimize pgvector performance, recall, or memory usage
- Use binary quantization for large vector datasets
**Keywords:** pgvector, embeddings, semantic search, vector similarity, HNSW, IVFFlat, halfvec, cosine distance, nearest neighbor, RAG, LLM, AI search
Covers: halfvec storage, HNSW index configuration (m, ef_construction, ef_search), quantization strategies, filtered search, bulk loading, and performance tuning.
timescale/pg-aiguide 1,661
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postgres-hybrid-text-search
Use this skill to implement hybrid search combining BM25 keyword search with semantic vector search using Reciprocal Rank Fusion (RRF).
**Trigger when user asks to:**
- Combine keyword and semantic search
- Implement hybrid search or multi-modal retrieval
- Use BM25/pg_textsearch with pgvector together
- Implement RRF (Reciprocal Rank Fusion) for search
- Build search that handles both exact terms and meaning
**Keywords:** hybrid search, BM25, pg_textsearch, RRF, reciprocal rank fusion, keyword search, full-text search, reranking, cross-encoder
Covers: pg_textsearch BM25 index setup, parallel query patterns, client-side RRF fusion (Python/TypeScript), weighting strategies, and optional ML reranking.
timescale/pg-aiguide 1,661
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setup-timescaledb-hypertables
Use this skill when creating database schemas or tables for Timescale, TimescaleDB, TigerData, or Tiger Cloud, especially for time-series, IoT, metrics, events, or log data. Use this to improve the performance of any insert-heavy table.
**Trigger when user asks to:**
- Create or design SQL schemas/tables AND Timescale/TimescaleDB/TigerData/Tiger Cloud is available
- Set up hypertables, compression, retention policies, or continuous aggregates
- Configure partition columns, segment_by, order_by, or chunk intervals
- Optimize time-series database performance or storage
- Create tables for sensors, metrics, telemetry, events, or transaction logs
**Keywords:** CREATE TABLE, hypertable, Timescale, TimescaleDB, time-series, IoT, metrics, sensor data, compression policy, continuous aggregates, columnstore, retention policy, chunk interval, segment_by, order_by
Step-by-step instructions for hypertable creation, column selection, compression policies, retention, continuous aggregates, and indexes.
timescale/pg-aiguide 1,661