資料庫

Create and manage database schema migrations following best practices for versioning, reversibility, and zero-downtime deployments. Use this skill when creating or modifying database migration files, Alembic migrations, Django migrations, Rails migrations, or any schema change scripts. Use this skill when working with database schema evolution, implementing rollback strategies, managing indexes on large tables, or separating schema changes from data migrations. Use this skill when working with files in migrations/, db/migrate/, alembic/versions/, or similar migration directories. Use this skill when creating new tables, modifying columns, adding indexes, establishing foreign key relationships, or managing database versioning in development and production environments.

TanStack Query + Zustand patterns.

PostgreSQL, MySQL, SQLite, 및 SQL Server를 지원하는 전문가 수준의 SQL 쿼리 작성, 최적화 및 데이터베이스 스키마 설계입니다. 데이터베이스 작업 시 다음을 위해 사용하세요: (1) JOIN, 서브쿼리, 윈도우 함수를 포함한 복잡한 SQL 쿼리 작성, (2) 느린 쿼리 최적화 및 실행 계획 분석, (3) 올바른 정규화를 적용한 데이터베이스 스키마 설계, (4) 인덱스 생성 및 쿼리 성능 개선, (5) 마이그레이션 작성 및 스키마 변경 처리, (6) SQL 에러 및 쿼리 문제 디버깅

Systematic debugging including root-cause tracing (trace backward through call stack), reproduction strategies, pdb/debugpy usage, logging analysis, binary search debugging, and error pattern recognition. Use when debugging errors, tracing bugs through call stacks, investigating production issues, or reproducing intermittent bugs.

Configure bubble charts in drizzle-cube dashboards for three-variable analysis with size and color dimensions. Use when creating bubble charts, multi-variable visualizations, or comparing three metrics simultaneously.

Redis-based rate limiting implementations with token bucket, leaky bucket, and sliding window algorithms. Use when implementing API rate limiting, throttling, or request quota management.

Perform SQL joins and multi-table analysis on DST data in DuckDB. Use whenresearch requires combining multiple tables on common dimensions (time, region).Provides patterns for common DST dimension joins and multi-table comparisons.

Search RAG database for relevant content. Use for semantic queries over processed documents, code, or papers.

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

Standardize Next.js App Router API route implementations under src/app/api/** (auth/session, input validation, Drizzle queries, rate limiting, response shape). Use when creating or refactoring API routes in this repo.

Enforce proper error handling patterns. Use when writing async code, API calls, or user-facing features. Covers try-catch, error boundaries, graceful degradation, and user feedback.

Complete pull request workflow combining git-hex (local craft) with remote collaboration (GitHub plugin or CLI). This skill should be used when the user wants to prepare, submit, and iterate on a PR with clean commit history. Trigger phrases include: "prepare a PR", "open a pull request", "address review feedback", "update my PR", "clean up commits for PR".

Execute SQL queries, migrations, and RLS policies on Supabase database using MCP tools

Gather design feedback from AI consultants (Gemini and Codex). Use for architecture decisions, design review, or when you want multiple expert perspectives on SENTINEL development.

Use when search queries need better recall through query expansion - generates multiple query variants, retrieves with each, and fuses results using RRF for improved retrieval quality especially with ambiguous or under-specified queries

World-class data engineering skill for building scalable data pipelines, ETL/ELT systems, and data infrastructure. Expertise in Python, SQL, Spark, Airflow, dbt, Kafka, and modern data stack. Includes data modeling, pipeline orchestration, data quality, and DataOps. Use when designing data architectures, building data pipelines, optimizing data workflows, or implementing data governance.

Enterprise-grade cloud architecture expertise with production-ready patterns for AWS (Lambda 3.13, ECS/Fargate 1.4.0, RDS, CDK 2.223.0), GCP (Cloud Run Gen2, Cloud Functions 2nd gen, Cloud SQL), Azure (Functions v4, Container Apps, AKS), and multi-cloud orchestration (Terraform 1.9.8, Pulumi 3.x, Kubernetes 1.34). Covers serverless architectures, container orchestration, multi-cloud deployments, cloud-native databases, infrastructure automation, cost optimization, security patterns, and disaster recovery for 2025 stable versions.

Comprehensive database management workflow that orchestrates database architecture, schema design, performance optimization, and data governance. Handles everything from database design and implementation to performance tuning, backup strategies, and data migration.

dbt best practices for models, tests, documentation, and project organization.

Database query optimization strategies. Use when improving query performance.