Loading...
Loading...
Found 58 Skills
Generate complete solutions for specific Dataverse SDK use cases with architecture recommendations
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.
Generate technical plan, data model, and interface contracts from spec.md
Safely refactors dbt models with downstream impact analysis. Use when restructuring dbt models for: (1) Task mentions "refactor", "restructure", "extract", "split", "break into", or "reorganize" (2) Extracting CTEs to intermediate models or creating macros (3) Modifying model logic that has downstream consumers (4) Renaming columns, changing types, or reorganizing model dependencies Analyzes all downstream dependencies BEFORE making changes.
Use this skill when optimizing Jazz applications for speed, responsiveness, and scalability. Covers crypto setup, efficient data modeling, and UI patterns to prevent lag.
SQL database queries, joins, aggregations, subqueries, and optimization. Use for .sql files and database operations.
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.
Expert-level Power BI, DAX, M language, data modeling, Power Query, report design, and paginated reports
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".
Expert-level Looker BI, LookML, explores, dimensions, measures, dashboards, and data modeling
Orchestrates the full journey from zero to a running Neo4j application. Executes 8 named stages in order: prerequisites → context → provision → model → load → explore → query → build. Each stage has its own reference file in references/ that the agent reads and follows when entering that stage. Supports both HITL and fully autonomous operation. Time budget: ≤15 min after DB is running (autonomous), ≤90 min total (HITL).
Design, review, and refactor Neo4j graph data models. Use when choosing node labels vs relationship types vs properties, migrating relational/document schemas to graph, detecting anti-patterns (generic labels, supernodes, missing constraints), designing intermediate nodes for n-ary relationships, enforcing schema with constraints and indexes, or assessing an existing model against graph modeling best practices. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle Spring Data Neo4j entity mapping — use neo4j-spring-data-skill. Does NOT handle GraphQL type definitions — use neo4j-graphql-skill. Does NOT handle data import — use neo4j-import-skill.