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Found 65 Skills
Type-driven design principle: transform unstructured data into structured types at system boundaries, making illegal states unrepresentable. Use when writing or reviewing code that validates input, designs data types, defines function signatures, handles errors, or models domain logic. Use when you see validation functions that return void/undefined, redundant null checks, stringly-typed data, boolean flags controlling behavior, or functions that can receive data they shouldn't. Triggers on: "parse don't validate", "type-driven design", "make illegal states unrepresentable", "input validation", "data modeling", "refactor types", "strengthen types", "smart constructor", "newtype", "branded type".
World-class database schema design - data modeling, migrations, relationships, and the battle scars from scaling databases that store billions of rowsUse when "database schema, data model, migration, prisma schema, drizzle schema, create table, add column, foreign key, primary key, uuid, auto increment, soft delete, normalization, denormalization, one to many, many to many, junction table, polymorphic, enum type, index strategy, database, schema, migration, data-model, prisma, drizzle, typeorm, postgresql, mysql, sqlite" mentioned.
Help design database schemas, create tables, and plan data models. Activates when users ask to create tables, design schemas, or model data relationships.
Clean Architecture, Data Models, Tech Stack, Error Handling & Platform Channels
Use this skill when you need to create or modify a LookML Model file (.model.lkml). This includes defining connections, includes, and configuring model-level settings.
Design and build database schemas and data models in MotherDuck. Produces a file-based project scaffold. Use when creating tables, choosing data types, defining relationships, or restructuring data for analytics workloads.
Interactive skill for eliciting, formalizing, and persisting DynamoDB access patterns. Use when the user wants to start designing a DynamoDB table, define entities, or document how their application will read and write data. This is Step 1 of a 3-step pipeline: access patterns -> table design -> query interfaces. The output is a structured .md file that feeds into the dynamodb-table-design skill.
Guide to using LookML sets for grouping fields, controlling visibility, and managing drill paths.
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.
Documents dbt models and columns in schema.yml. Use when working with dbt documentation for: (1) Adding model descriptions or column definitions to schema.yml (2) Task mentions "document", "describe", "description", "dbt docs", or "schema.yml" (3) Explaining business context, grain, meaning of data, or business rules (4) Preparing dbt docs generate or improving model discoverability Matches existing project documentation style and conventions before writing.
Master PostgreSQL SQL fundamentals - data types, tables, constraints, schema design
Apply when deciding whether and how VTEX IO apps should use Master Data v2 for custom data. Covers entity boundaries, schema lifecycle, indexing strategy, and when Master Data is the right storage mechanism versus another data approach. Use for reviews, wishlists, forms, or other custom data modeling decisions in VTEX IO apps.