rulesgen

rulesgen is a secure rule-processing service for synthetic data workflows.

It accepts rule input as either natural_language or DSL, translates natural_language requests into an untrusted semantic_frame plus DSL candidate, validates the DSL into a compiled_rule, supports local execution_preview, and can execute full dataset generation as a tracked job.

diagnostics are part of the contract at every stage. The service does not treat LLM output as trusted input, and a rule only becomes executable after validation and compilation succeed.

Who this documentation is for

• Teams authoring rules for synthetic data workflows
• Contributors extending the service, compiler, or execution adapters
• Operators evaluating local preview and full dataset-generation paths

Core flow

1. Parse rule input into a semantic_frame plus diagnostics.
2. Treat natural_language output and any DSL candidate as untrusted until validation succeeds.
3. Compile validated DSL into a compiled_rule.
4. Run an execution_preview against a sample row and seed.
5. Execute full dataset generation as a job and inspect diagnostics and generated artifacts.

Start here

• Quick Start
• Domain Vocabulary
• Repository Docs