Create, extend, validate, and improve Qlerify workflow diagrams and domain models, including domain events, roles, read models, commands, policies, aggregates, entities, value objects, attributes, given-when-then scenarios, bounded contexts, and invariants. Use when the task involves event storming, event modeling, domain-driven design (DDD), specification-driven development (SDD), model-driven development (MDD), software modeling, domain modeling, process modeling, legacy modernization, reverse-engineering code into a model, generating code from a model, or any direct use of the Qlerify modeling tools.
Generate production-ready code from a Qlerify domain model. Use when the user asks to "generate code from the model", "implement the workflow", "scaffold from Qlerify", "build the aggregate", "code up the domain model", "create the app from the model", or after a workflow has been modeled or extracted and the next step is producing runnable code on a target tech stack. Pairs with the workflow-creation skill (which produces the model) and the sync skill (which keeps model and code aligned over time).
Keep a codebase and its Qlerify domain model in agreement, in both directions. Use when the user asks to "sync domain model", "update Qlerify", "push changes to Qlerify", "sync schemas/entities/domain events", or after implementing features that add or change entities, API endpoints, commands, domain events, database schemas, migrations, or Prisma/GraphQL types — sync applies that code drift into the Qlerify model. Also use when the Qlerify model has been edited (new entities, changed commands, new acceptance criteria) and the code needs to catch up — sync detects the model-side drift and hands off to the code-generation skill. For brownfield/legacy codebases with unclear boundaries, isolate one aggregate at a time first (the workflow-creation skill's Phase 0 covers aggregate extraction).
This skill should be used when the user asks to "save to file", "download", "export", "store in file", or any request that involves getting data from Qlerify and saving it locally. Bypasses AI processing and is ~100x faster than MCP tools for large data exports.