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Found 78 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".
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 this skill when optimizing Jazz applications for speed, responsiveness, and scalability. Covers crypto setup, efficient data modeling, and UI patterns to prevent lag.
Create or update system design documents. Supports initial design and incremental design modes. Use when users need technical architecture, API design, data models, design changes, or impact analysis. Triggers on keywords like "system design", "architecture", "technical design", "API design", "design change", "impact analysis", "design change", "impact analysis".
Design database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for PostgreSQL and MySQL.
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.
Reference skill for CDF Data Modeling API best practices. Covers concurrency limits (avoiding 429s), pagination patterns for instances.list and instances.query, batching write operations, search vs filter guidance, and the QueuedTaskRunner (Semaphore) utility for controlling concurrent requests. Triggers: DMS limits, 429 error, rate limit, pagination, cursor, nextCursor, batching, semaphore, QueuedTaskRunner, cdfTaskRunner, instances.search, instances.list, instances.query, instances.upsert, concurrency, deadlock.
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.
Complete guide for dbt data transformation including models, tests, documentation, incremental builds, macros, packages, and production workflows
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.
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.
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.