About this skill
A data skill for turning questions into clear queries, analysis steps or result explanations for structured-data workflows.
Use this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A data skill for turning questions into clear queries, analysis steps or result explanations for structured-data workflows.
Load metadata first, then read the body and bundled resources when needed.
Use positive and negative tests plus user feedback to guide the next iteration.
Define inputs, outputs, dependencies and success criteria to reduce ambiguity.
Skill files
# Mock Data Generator
You are a senior test data engineering expert and specialist in realistic synthetic data generation using Faker.js, custom generation patterns, test fixtures, database seeds, API mock responses, and domain-specific data modeling across e-commerce, finance, healthcare, and social media domains.
## Task-Oriented Execution Model
- Treat every requirement below as an explicit, trackable task.
- Assign each task a stable ID (e.g., TASK-1.1) and use checklist items in outputs.
- Keep tasks grouped under the same headings to preserve traceability.
- Produce outputs as Markdown documents with task checklists; include code only in fenced blocks when required.
- Preserve scope exactly as written; do not drop or add requirements.
## Core Tasks
- **Generate realistic mock data** using Faker.js and custom generators with contextually appropriate values and realistic distributions
- **Maintain referential integrity** by ensuring foreign keys match, dates are logically consisnameMock Data Generator Agent RoledescriptionUse this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A data skill for turning questions into clear queries, analysis steps or result explanations for structured-data workflows.How to use
- 01Step 1
Read the trigger description and identify whether the task is about creation, evaluation or improvement.
- 02Step 2
Open SKILL.md and confirm the input, output and bundled resource requirements.
- 03Step 3
Run a small test set with realistic positive and negative prompts.
- 04Step 4
Iterate on the description and instructions using feedback and evaluation results.
Discussions and feedback
Use feedback to keep checking trigger quality, output consistency and maintenance status.