Scored across 12 tools
The two generation tools (generate_from_schema vs generate_dataset) and the three validation tools (check_realism, audit_dataset, validate_domain) have adjacent purposes, but descriptions explicitly delineate boundaries (schema-driven vs story-driven; statistical tells vs internal contradictions vs external plausibility). preview_story vs inspect_schema is the closest pair, but the 'heavier than preview_story' note and differing return shapes clarify them. Most tools remain clearly distinct.
All names are lowercase snake_case with a verb_noun shape (list_domains, preview_story, create_sandbox, query_sandbox, audit_dataset). Minor deviation: validation is expressed across three verbs (check_realism, audit_dataset, validate_*) and generation mixes generate_dataset with generate_from_schema, but the pattern stays predictable and readable.
12 tools is well-scoped for a synthetic data engine spanning authoring, generation, validation, DB seeding, and sandboxing. Each tool maps to a distinct stage of the workflow with no obvious redundancy or padding.
The lifecycle is broadly covered: discover domains, preview/inspect, generate from story or schema, validate schema, seed live DBs, spin up and query a sandbox, and audit output for realism, contradictions, and domain plausibility. Minor gaps exist (no tool to list/inspect already-generated artifacts or to fetch the extended declaration reference noted in the docs), but core workflows have no dead ends.