Generate realistic test data conforming to Vague schemas with constraints and cross-references.
npx skills add https://github.com/mcclowes/omg --skill vague
Please help me install this Agent Skill. Skill: vague Source: https://github.com/mcclowes/omg/tree/main/.claude/skills/vague Command: npx skills add https://github.com/mcclowes/omg --skill vague
This Skill automates the creation of realistic, structured test data with constraints, references, and superposition logic built-in.
Generate 50 realistic user profiles with unique emails, realistic names, and age ranges between 18 and 65.
High-intent search queries and answers about installing and using this skill.
Generate test data using Vague schemas that enforce constraints, unique values, and relationships between fields. The Skill creates realistic datasets like user profiles, invoices, and orders with deterministic seeding for reproducibility in testing environments.
Yes. Vague supports superposition for multiple valid values, ranges for numeric fields, computed fields for derived data, and plugin integrations with Faker and Regex. This enables complex, multi-variant test datasets from a single schema definition.
Define your API spec or data schema once, then generate realistic mock datasets automatically. The Skill handles realistic names, emails, age ranges, and cross-references, reducing manual mock authoring and ensuring test data consistency.
Use Vague's deterministic seeding to generate the same test data across runs, enabling reproducible testing. CLI tooling supports inference from schemas, validation, and multiple output formats for dataset generation.
Yes. Generate datasets at scale—like 50+ user profiles—while maintaining referential integrity, unique constraints, and field relationships. Vague handles private fields, refinements, and Issuer plugins for specialized value generation.
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