Generate realistic synthetic data for a Neo4j property graph by asking the user the right questions, then writing a Faker script tailored to their answers. Trigger when the user wants to populate Neo4j, generate fake/synthetic/test data for a graph schema, or build a dataset to test detection logic (fraud rings, entity resolution, anomalies). Trigger when the user uploads an arrows.app schema or describes a graph model and asks for sample data. Do NOT trigger for schema design (use graph-schema-studio).
Installation
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Generate realistic synthetic data for a Neo4j property graph by asking the user the right questions, then writing a Faker script tailored to their answers. Trigger when the user wants to populate Neo4j, generate fake/synthetic/test data for a graph schema, or build a dataset to test detection logic (fraud rings, entity resolution, anomalies). Trigger when the user uploads an arrows.app schema or describes a graph model and asks for sample data. Do NOT trigger for schema design (use graph-schema-studio).
Graph Data Workflow
A six-step conversational flow: scale → use case → cardinality → preview →
patterns → script. Claude asks; the user answers; a Faker script is written
and run.
Read assets/docs/WORKFLOW.md before starting. It has the question
templates, the order, and the rules about pausing for confirmation.
Helper: scripts/build_script.py — takes a JSON config and emits a
standalone Python script using Faker.
