timmy-config/docs/issue-605-verification.md

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

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.