--- title: "Tiger Data (@timescale) skills · skilld" canonical_url: "https://skilld.dev/gh/timescale" meta: description: "9 agent skills published by Tiger Data on skilld." "og:description": "9 agent skills published by Tiger Data." "og:title": "Tiger Data on skilld" --- ` ![Avatar for Tiger Data](https://skilld.dev/_img/avatar?url=https%3A%2F%2Fgithub.com%2Ftimescale.png) # **Tiger Data** [@timescale](https://github.com/timescale)org 9 skills 1.9k Synced 6 days ago [GitHub](https://github.com/timescale) [Website](https://www.tigerdata.com) ## Skills ### [timescale/pg-aiguide](https://skilld.dev/gh/timescale/pg-aiguide) 9 skills 1.9k `npx skilld add timescale/pg-aiguide` - [ **/design-postgis-tables**1.9k Comprehensive PostGIS spatial table design reference covering geometry types, coordinate systems, spatial indexing, and performance patterns for location-based applications /design-postgis-tables by timescale](https://skilld.dev/gh/timescale/pg-aiguide/design-postgis-tables) - [ **/design-postgres-tables**1.9k Use this skill for general PostgreSQL table design. \*\*Trigger when user asks to:\*\* - Design PostgreSQL tables, schemas, or data models when creating new tables and when modifying existing ones. - Choose data types, constraints, or indexes for PostgreSQL - Create user tables, order tables, reference tables, or JSONB schemas - Understand PostgreSQL best practices for normalization, constraints, or indexing - Design update-heavy, upsert-heavy, or OLTP-style tables \*\*Keywords:\*\* PostgreSQL schema, table design, data types, PRIMARY KEY, FOREIGN KEY, indexes, B-tree, GIN, JSONB, constraints, normalization, identity columns, partitioning, row-level security Comprehensive reference covering data types, indexing strategies, constraints, JSONB patterns, partitioning, and PostgreSQL-specific best practices. /design-postgres-tables by timescale](https://skilld.dev/gh/timescale/pg-aiguide/design-postgres-tables) - [ **/find-hypertable-candidates**1.9k Use this skill to analyze an existing PostgreSQL database and identify which tables should be converted to Timescale/TimescaleDB hypertables. \*\*Trigger when user asks to:\*\* - Analyze database tables for hypertable conversion potential - Identify time-series or event tables in an existing schema - Evaluate if a table would benefit from Timescale/TimescaleDB - Audit PostgreSQL tables for migration to Timescale/TimescaleDB/TigerData - Score or rank tables for hypertable candidacy \*\*Keywords:\*\* hypertable candidate, table analysis, migration assessment, Timescale, TimescaleDB, time-series detection, insert-heavy tables, event logs, audit tables Provides SQL queries to analyze table statistics, index patterns, and query patterns. Includes scoring criteria (8+ points = good candidate) and pattern recognition for IoT, events, transactions, and sequential data. /find-hypertable-candidates by timescale](https://skilld.dev/gh/timescale/pg-aiguide/find-hypertable-candidates) - [ **/migrate-postgres-tables-to-hypertables**1.9k Use this skill to migrate identified PostgreSQL tables to Timescale/TimescaleDB hypertables with optimal configuration and validation. \*\*Trigger when user asks to:\*\* - Migrate or convert PostgreSQL tables to hypertables - Execute hypertable migration with minimal downtime - Plan blue-green migration for large tables - Validate hypertable migration success - Configure compression after migration \*\*Prerequisites:\*\* Tables already identified as candidates (use find-hypertable-candidates first if needed) \*\*Keywords:\*\* migrate to hypertable, convert table, Timescale, TimescaleDB, blue-green migration, in-place conversion, create\_hypertable, migration validation, compression setup Step-by-step migration planning including: partition column selection, chunk interval calculation, PK/constraint handling, migration execution (in-place vs blue-green), and performance validation queries. /migrate-postgres-tables-to-hypertables by timescale](https://skilld.dev/gh/timescale/pg-aiguide/migrate-postgres-tables-to-hypertables) - [ **/pgvector-semantic-search**1.9k 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. /pgvector-semantic-search by timescale](https://skilld.dev/gh/timescale/pg-aiguide/pgvector-semantic-search) - [ **/postgres**1.9k Use this skill for any PostgreSQL database work — table design, indexing, data types, constraints, extensions (pgvector, PostGIS, TimescaleDB), search, and migrations. \*\*Trigger when user asks to:\*\* - Explore an existing PostgreSQL database to understand its objects and relationships - Design or modify PostgreSQL tables, schemas, or data models - Choose data types, constraints, indexes, or partitioning strategies - Work with pgvector embeddings, semantic search, or RAG - Set up full-text search, hybrid search, or BM25 ranking - Use PostGIS for spatial/geographic data - Set up TimescaleDB hypertables for time-series data - Migrate tables to hypertables or evaluate migration candidates - Plan or execute safe schema migrations with zero downtime \*\*Keywords:\*\* PostgreSQL, Postgres, SQL, schema, table design, indexes, constraints, pgvector, PostGIS, TimescaleDB, hypertable, semantic search, hybrid search, BM25, time-series, migration /postgres by timescale](https://skilld.dev/gh/timescale/pg-aiguide/postgres) - [ **/postgres-database-migration**1.9k Use this skill for planning, testing, and safely executing PostgreSQL schema migrations — especially when working with production data or shared databases. \*\*Trigger when user asks to:\*\* - Test a schema migration before applying it to production - Add, remove, or rename columns safely on a live table - Change a column's data type without downtime - Add or drop indexes, constraints, or foreign keys on large tables - Understand which ALTER TABLE operations lock the table - Roll back a failed migration - Plan a zero-downtime migration strategy - Fork a database to test a migration safely \*\*Keywords:\*\* migration, schema change, ALTER TABLE, add column, drop column, rename column, change type, zero downtime, lock, AccessExclusiveLock, concurrent index, forking, rollback, backfill, deploy Covers: lock-level reference for every common DDL operation, safe migration patterns, fork-based testing, zero-downtime column changes, index creation, constraint addition, backfill strategies, pre/post-migration validation, and rollback planning. /postgres-database-migration by timescale](https://skilld.dev/gh/timescale/pg-aiguide/postgres-database-migration) - [ **/postgres-hybrid-text-search**1.9k 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. /postgres-hybrid-text-search by timescale](https://skilld.dev/gh/timescale/pg-aiguide/postgres-hybrid-text-search) - [ **/setup-timescaledb-hypertables**1.9k 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. /setup-timescaledb-hypertables by timescale](https://skilld.dev/gh/timescale/pg-aiguide/setup-timescaledb-hypertables) Skills published by Tiger Data. 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