# Issue #605 Verification

Status: already implemented on `main`.

Issue: Prompt Enhancement: Video Scenes — 500 Terse→Rich Pairs

What is already present on `main`
- `training/data/prompt-enhancement/video-scenes-500.jsonl`
- 500 JSONL records
- every record includes `terse`, `rich`, and `domain`
- every `domain` value is `video scenes`
- 500/500 full records are unique
- every `rich` prompt includes video-scene structure markers for `lighting`, `composition`, and `transition`

Evidence gathered from a fresh clone
- validation against `training/data/prompt-enhancement/video-scenes-500.jsonl` returned:
  - `count = 500`
  - `unique_records = 500`
  - `unique_terse = 120`
  - `domains = ['video scenes']`
  - `missing_keys = 0`
  - all 500 `rich` prompts contain `lighting`, `composition`, and `transition`
- closed PRs `#755` (`fix/605`) and `#648` (`feat/605-video-scenes-prompts`) show prior attempts on this lane
- SHA-256 of `training/data/prompt-enhancement/video-scenes-500.jsonl` on `origin/main` matches the same file on remote branch `fix/605`, which shows the requested dataset is already present on `main`

Verification commands
```bash
python3 - <<'PY'
import json
from pathlib import Path
path = Path('training/data/prompt-enhancement/video-scenes-500.jsonl')
records = [json.loads(line) for line in path.read_text().splitlines() if line.strip()]
print('count', len(records))
print('unique_records', len({json.dumps(r, sort_keys=True) for r in records}))
print('unique_terse', len({r['terse'] for r in records}))
print('domains', sorted({r.get('domain') for r in records}))
print('missing_keys', sum(any(k not in r or not str(r[k]).strip() for k in ('terse', 'rich', 'domain')) for r in records))
print('lighting_count', sum('lighting' in r['rich'].lower() for r in records))
print('composition_count', sum('composition' in r['rich'].lower() for r in records))
print('transition_count', sum('transition' in r['rich'].lower() for r in records))
PY
```

Recommendation
- Close issue #605 as already implemented on `main`.
- This branch only adds a durable verification note and regression test so the open issue can be closed cleanly without regenerating duplicate training data.