Ground team
Examples you can reproduce, down to the seed.
Download the data, inspect the exact rules, and verify the output yourself. Worked examples now include specifications, seeds and file checksums.
The output. The rules. The seed.
The worked-example library now includes generated CSV and JSONL files, the exact Ground specification, a seed and a manifest with SHA-256 checksums. You can inspect every file without creating an account.
Each example explains its schema, reports the counts actually generated and includes a workflow you can follow. A small Python verification script checks the downloads using only the standard library. Keep the downloaded fixture when you need exact historical output: future engine versions can change generated values.
Measured output. Inspect observed status frequencies, missing values and rare-label counts rather than relying on probability settings alone.
An inspectable recipe. Save the specification and seed with your fixture. Recreate a dataset through the API using the documented request.
Clear limits. Each example states what it models and what it leaves out, so a designed simulation is not mistaken for validated real-world behavior.