# Genesis AI Code Bench
**Developed by: Within Us AI**  
Generated: 2026-01-01

A lightweight evaluation harness for Genesis-style datasets that focuses on the signals
developers care about in practice:

- **Structure validity** (JSON parsing, required fields, schema consistency)
- **Tool-trace validity** (JSON array of tool calls with `tool` + `args`)
- **Diff validity** (`patch_diff` blocks contain recognizable unified-diff markers)
- **Self-grade validity** (score bounds, confidence bounds, presence of notes)
- **Governance presence** (audit/tests flags when expected)
- **Economics presence** (cost budgets + latency targets)

This bench is intentionally fast and offline-friendly. It does not execute repo tests; it
scores dataset quality and readiness for downstream training workflows.

## Quick start
```bash
python bench.py --jsonl path/to/train.jsonl --max_rows 5000
```

## Metrics produced
- `format_valid_rate`
- `required_fields_rate`
- `tool_trace_valid_rate`
- `patch_diff_valid_rate`
- `self_grade_valid_rate`
- `governance_present_rate`
- `economics_present_rate`
- `uniqueness_rate` (hash-based)

## Recommended use
- Run before upload to ensure Viewer-ready consistency
- Run after merges to confirm schema stability
- Compare v1.0 vs v1.1 addon impact