Use when you need to generate, validate, or deploy stored procedures for PostgreSQL, MySQL, or SQL Server. Creates database functions, triggers, and procedures with proper error handling and transaction management. Trigger with phrases like "generate stored procedure", "create database function", "write SQL procedure", "add trigger to table", or "create CRUD procedures".
Build use when you need to work with NoSQL data modeling. This skill provides NoSQL database design with comprehensive guidance and automation. Trigger with phrases like "model NoSQL data", "design document structure", or "optimize NoSQL schema".
Detect and analyze SQL injection vulnerabilities in application code and database queries. Use when you need to scan code for SQL injection risks, review query construction, validate input sanitization, or implement secure query patterns. Trigger with phrases like "detect SQL injection", "scan for SQLi vulnerabilities", "review database queries", or "check SQL security".
Comprehensive database administration, schema management, data operations, and optimization. Use when Codex needs to: (1) Create or modify database tables with proper indexing, (2) Perform bulk data insertions with type safety and constraint handling, (3) Execute complex queries with JOINs, aggregations, and subqueries, (4) Optimize query performance through indexing and execution plan analysis, (5) Manage database backups, restores, and migrations, (6) Handle special data types (BIGINT, UUID, JSONB, enums), (7) Implement transactional safety with ACID compliance, or (8) Debug and resolve database errors including constraint violations, type mismatches, and foreign key issues
Query database safely with parameterized statements
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.
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.
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.
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.
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:** - 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 **Keywords:** PostgreSQL, Postgres, SQL, schema, table design, indexes, constraints, pgvector, PostGIS, TimescaleDB, hypertable, semantic search, hybrid search, BM25, time-series
Database design principles and decision-making. Schema design, indexing strategy, ORM selection, serverless databases.
Design a PostgreSQL-specific schema. Covers best-practices, data types, indexing, constraints, performance patterns, and advanced features
HashQL J-Expr syntax for writing queries. Use when writing J-Expr code, using #literal/#struct/#list constructs, understanding function call syntax, or working with HashQL query files (.jsonc).
Design robust, scalable database schemas for SQL and NoSQL databases. Provides normalization guidelines, indexing strategies, migration patterns, constraint design, and performance optimization. Ensures data integrity, query performance, and maintainable data models.
Designs database schemas, indexing strategies, query optimization, and migration patterns for SQL and NoSQL databases. Use when designing tables, optimizing queries, fixing N+1 problems, planning migrations, or when asked about database performance, normalization, ORMs, or data modeling.
Create and query Databricks Genie Spaces for natural language SQL exploration. Use when building Genie Spaces, exporting and importing Genie Spaces, migrating Genie Spaces between workspaces or environments, or asking questions via the Genie Conversation API.
Query optimization, indexing strategies, and database performance tuning for PostgreSQL and MySQL
PostgreSQL optimization including indexes, query plans, partitioning, JSONB operations, and connection pooling
SQL query optimization techniques and best practices
Comprehensive guide for Go database access. Covers parameterized queries, struct scanning, NULLable column handling, error patterns, transactions, isolation levels, SELECT FOR UPDATE, connection pool, batch processing, context propagation, and migration tooling. Use this skill whenever writing, reviewing, or debugging Golang code that interacts with PostgreSQL, MariaDB, MySQL, or SQLite. Also triggers for database testing or any question about database/sql, sqlx, pgx, or SQL queries in Golang. This skill explicitly does NOT generate database schemas or migration SQL.
数据库服务攻击方法论。当发现 Redis(6379)、MSSQL(1433)、PostgreSQL(5432)、MySQL(3306)、MongoDB(27017) 等数据库端口时使用。覆盖未授权访问、弱口令爆破、命令执行、文件读写、提权。任何涉及数据库攻击、数据库提权、数据库利用的场景都应使用此技能
This skill analyzes and optimizes SQL queries for improved performance. It identifies potential bottlenecks, suggests optimal indexes, and proposes query rewrites. Use this when the user mentions "optimize SQL query", "improve SQL performance", "SQL query optimization", "slow SQL query", or asks for help with "SQL indexing". The skill helps enhance database efficiency by analyzing query structure, recommending indexes, and reviewing execution plans.
Complex Join Helper - Auto-activating skill for Data Analytics. Triggers on: complex join helper, complex join helper Part of the Data Analytics skill category.
