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Found 60 Skills
Data modeling with Entity-Relationship Diagrams (ERDs), data dictionaries, and conceptual/logical/physical models. Documents data structures, relationships, and attributes.
Create and manage NocoBase data models via MCP. Use when users want to inspect or change collections, fields, relations, or view-backed schemas in a NocoBase app.
Design database schemas for Grey Haven multi-tenant SaaS - SQLModel models, Drizzle schema, multi-tenant isolation with tenant_id and RLS, timestamp fields, foreign keys, indexes, migrations, and relationships. Use when creating database tables.
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.
Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file
Best practices for building with Gadget. Use when developers need guidance on models, actions, routes, access control, Shopify/BigCommerce integrations, frontend patterns, API usage, permissions, or framework decisions. Triggers "model", "action", "route", "permission", "access control", "multi-tenancy", "Shopify", "BigCommerce", "frontend", "API client", "filter", "pagination", "webhook", "background job"
Analytics engineering for reliable metrics and BI readiness. Build transformation layers, dimensional models, semantic metrics, data quality tests, and documentation. Use when you need dbt or SQL transformation strategy, metrics definition, or analytics data modeling.
Use when designing database schemas, need to model domain entities and relationships clearly, building knowledge graphs or ontologies, creating API data models, defining system boundaries and invariants, migrating between data models, establishing taxonomies or hierarchies, user mentions "schema", "data model", "entities", "relationships", "ontology", "knowledge graph", or when scattered/inconsistent data structures need formalization.
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.
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.
Comprehensive Pydantic data validation skill for customer support tech enablement - covering BaseModel, Field validation, custom validators, FastAPI integration, BaseSettings, serialization, and Pydantic V2 features