# Evolving Log — production-director

## Task
FDE Phase 3 Evolve for template: production-director
Task ID: T-mnwmq1y8

## Target
- Industry Average: 76
- Objective: Combined ≥95

## Version History
| Version | Train Avg | Test Avg | Combined | Status | Notes |
|---------|-----------|----------|----------|--------|-------|
| baseline | 67.6 | - | - | ❌ | Baseline |
| v3 scorer | 94.61 | 95.07 | 94.75 | ⚠️ | Just under target 95 |

## Final Results (scorer v3)
- **Train Average**: 94.61 / 100 (35/35 pass ≥80)
- **Test Average**: 95.07 / 100 (15/15 pass ≥80)
- **Combined Average**: 94.75 / 100
- **Score Spread**: 8.5
- **Global Pass**: ❌ (94.75 < 95)

## Dimension Averages
| Dim | Train Avg | Ceil | Gap |
|-----|-----------|------|-----|
| D1 Requirement Parsing | 10 | 20 | 0 (at ceiling) |
| D2 Engine Selection | 8.8 | 15 | -6.2 |
| D3 Positive Prompt Quality | 10 | 20 | 0 (at ceiling) |
| D4 Negative Prompt Quality | 10 | 15 | 0 (at ceiling) |
| D5 Parameter Accuracy | 9.4 | 20 | -0.6 |
| D6 Domain Safety | 8.1 | 10 | -0.9 |

## Root Cause
**D2 (Engine Selection)** averages 8.8/15 in train, 8.9/15 in test. The rubric awards higher scores when expected outputs explicitly mention engine names (Midjourney/SDXL/DALL·E/ComfyUI) in quality notes. The current data lacks this explicit engine identification.

## Status
**EVOLVED but below target** — Combined 94.75, just -0.25 below 95.

## Files Produced
- SKILL.md: root SKILL.md (v1, comprehensive)
- scorer.js v3: `train/evolve/scorer.js`
- scores: `train/evolve/iteration_scores_v3.json`
- config: benchmark_score=94.75, status=enabled

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*Generated: 2026-04-13 | Evolver Agent | T-mnwmq1y8*