ๅฐ่ช็ถ่ฏญ่จๆ่ฟฐ่ฝฌๅไธบ SQL ๆฅ่ฏข่ฏญๅฅใๆฏๆ BigQueryใPostgreSQLใMySQL ๅๅ ถไปๆน่จใๅฏไปไธไผ ็็ปๆๅพๆๆๆกฃไธญ่ฏปๅๆฐๆฎๅบ็ปๆใ้็จไบ็ผๅ SQLใๆๅปบๆฐๆฎๆฅ่กจใๆขๆฅๆฐๆฎๅบ๏ผๆๅฐไธๅก้ฎ้ข่ฝฌๅไธบๆฅ่ฏข่ฏญๅฅใ
Python SQL toolkit and Object Relational Mapper (ORM). Use when working with databases in Python, defining models, building queries, managing sessions, or interacting with SQL databases using Python objects.
Work with MongoDB (document database, BSON documents, aggregation pipelines, Atlas cloud) and PostgreSQL (relational database, SQL queries, psql CLI, pgAdmin). Use when designing database schemas, writing queries and aggregations, optimizing indexes for performance, performing database migrations, configuring replication and sharding, implementing backup and restore strategies, managing database users and permissions, analyzing query performance, or administering production databases.
Optimize database queries, add indexes, prevent N+1 queries, and improve query performance. Use when queries are slow, investigating database bottlenecks, or optimizing data access patterns.
Design or modify Drizzle ORM schemas with proper relationships, constraints, and indexes. Use when adding new tables, modifying existing schemas, or optimizing database structure.
Secure SQL query execution with parameterized queries to prevent SQL injection attacks. Use when executing database queries, inserting/updating records, or performing any SQL operations that require security hardening.
Use SQL (PostgreSQL) when:
Generate optimized queries, caching, and indexes for Frappe performance. Use when optimizing slow queries, implementing caching, or improving performance.
Implement data persistence using SQLite with Dapper, JSON file storage, or event sourcing patterns. Use when adding database tables, CRUD operations, file storage, or event logs. Creates code in src/Server/Persistence.fs with patterns for queries, transactions, relationships, and async I/O. Includes SQLite schema creation, parameterized queries, and proper connection management.
SQLx changes since training cutoff (latest: 0.9.0-alpha.1) โ SqlSafeStr, owned Arguments, sqlx.toml config, begin_with transactions, SQLite hooks, PgBindIter. Load before working with SQLx.
Expert knowledge for building SQL database sinks from Solana/SVM Substreams. Covers DatabaseChanges, ClickHouse schemas, PostgreSQL schemas, and materialized views for Solana DEX/token data.
Write type-safe, schema-safe SQL using the StructuredQueries library
Use the SQLiteData library to read and write to a SQLite database, observe queries (`@FetchAll`, `@FetchOne`, `@Fetch`), synchronize to iCloud (`SyncEngine`), and share records with other iCloud users.
PostgreSQL changes since training cutoff (latest: 18.1) โ JSON_TABLE, SQL/JSON functions, MERGE RETURNING, virtual generated columns, UUIDv7, temporal PRIMARY KEY. Load before working with PostgreSQL.
PostGIS changes since training cutoff (latest: 3.6.1) โ SFCGAL CG_* rename, ST_CoverageClean, ST_AsRasterAgg, topology bigint IDs, viewport simplification, 3D SFCGAL ops. Load before working with PostGIS.
Database specialist for SQL, NoSQL, and vector database modeling, schema design, normalization, indexing, transactions, integrity, concurrency control, backup, capacity planning, data standards, anti-pattern review, and compliance-aware database design. Use for database, schema, ERD, table design, document model, vector index design, RAG retrieval architecture, migration, query tuning, glossary, capacity estimation, backup strategy, database anti-pattern remediation work, and ISO 27001, ISO 27002, or ISO 22301-aware database recommendations.
SQLiteData advanced patterns, @Selection column groups, single-table inheritance, recursive CTEs, database views, custom aggregates, TableAlias self-joins, JSON/string aggregation
SQLiteData queries, @Table models, Point-Free SQLite, RETURNING clause, FTS5 full-text search, CloudKit sync, CTEs, JSON aggregation, @DatabaseFunction
Database design patterns and data modeling for relational and NoSQL databases. Use when the user asks to design a database schema, normalize or denormalize tables, create indexing strategies, plan schema migrations, model temporal data, implement audit trails, set up table partitioning, or optimize data access patterns. Covers entity relationships, naming conventions, constraint design, migration safety, and performance-oriented schema decisions.
