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From role-database
Covers data modeling patterns across paradigms: ER (Chen, Crow's Foot, UML), document (embedding/referencing, polymorphic, bucket), graph (LPG, RDF), time-series, event sourcing, dimensional (star/snowflake, SCD), Data Vault. Use for schema design and paradigm selection.
npx claudepluginhub rnavarych/alpha-engineer --plugin role-databaseHow this skill is triggered — by the user, by Claude, or both
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/role-database:data-modelingThis skill is limited to the following tools:
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Designs data models, database schemas, and modeling approaches like dimensional modeling, star schema, data vault, ER diagrams, and schema evolution for OLTP/OLAP systems.
Creates validated entity-relationship models with constraints for SQL/NoSQL/graph databases, knowledge graphs, ontologies, API data models, and taxonomies. Useful for schema design and data formalization.
Designs NoSQL data models for MongoDB, DynamoDB, Redis, and Cassandra using access patterns, embedding/referencing decisions, and denormalization trade-offs.
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Load from references/ based on what's needed:
ER notation systems (Chen, Crow's Foot, UML, IDEF1X). Relationship types (1:1, 1:N, M:N, self-referential, polymorphic) with implementation patterns. Normalization decision guide by scenario (OLTP, writes, reads, warehouse). MongoDB embedding vs referencing decision table. Document design patterns: polymorphic, bucket (time-series), outlier, subset, computed. Load when: designing relational schemas, modeling MongoDB documents, or choosing ER notation.
Labeled property graph model syntax and best practices. RDF triple model and SPARQL use cases. Time-series design principles, TimescaleDB hypertable, PostgreSQL native range partitioning. Star schema structure, SCD types comparison table, SCD Type 2 implementation. Data Vault components (hub/link/satellite) and advantages. Polyglot persistence decision table and consistency patterns (CDC, Saga, CQRS). Load when: designing graph models, time-series schemas, data warehouses, or multi-database architectures.