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Found 46 Skills
Expert database architect specializing in data layer design from scratch, technology selection, schema modeling, and scalable database architectures. Masters SQL/NoSQL/TimeSeries database selection, normalization strategies, migration planning, and performance-first design. Handles both greenfield architectures and re-architecture of existing systems. Use PROACTIVELY for database architecture, technology selection, or data modeling decisions.
MUST USE when designing ClickHouse architectures, selecting between ingestion or modeling patterns, or translating best practices into workload-specific system designs. Complements clickhouse-best-practices with decision frameworks and explicit provenance labels.
Converts legacy SQL to modular dbt models. Use when migrating SQL to dbt for: (1) Converting stored procedures, views, or raw SQL files to dbt models (2) Task mentions "migrate", "convert", "legacy SQL", "transform to dbt", or "modernize" (3) Breaking monolithic queries into modular layers (discovers project conventions first) (4) Porting existing data pipelines or ETL to dbt patterns Checks for existing models/sources, builds and validates layer by layer.
Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best practices.
Comprehensive Pydantic data validation skill for customer support tech enablement - covering BaseModel, Field validation, custom validators, FastAPI integration, BaseSettings, serialization, and Pydantic V2 features
Design systems, services, and architectures. Trigger with "design a system for", "how should we architect", "system design for", "what's the right architecture for", or when the user needs help with API design, data modeling, or service boundaries.
Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems. Use PROACTIVELY for database optimization or complex analysis.
Complete guide for dbt data transformation including models, tests, documentation, incremental builds, macros, packages, and production workflows
Qdrant vector database: collections, points, payload filtering, indexing, quantization, snapshots, and Docker/Kubernetes deployment.
AWS DynamoDB NoSQL database for scalable data storage. Use when designing table schemas, writing queries, configuring indexes, managing capacity, implementing single-table design, or troubleshooting performance issues.
Load automatically when planning, researching, or implementing ANY Medusa backend features (custom modules, API routes, workflows, data models, module links, business logic). REQUIRED for all Medusa backend work in ALL modes (planning, implementation, exploration). Contains architectural patterns, best practices, and critical rules that MCP servers don't provide.
Design database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for PostgreSQL and MySQL.