القائمة
Score generated Brand Shoot Kit images for product accuracy, realism, brand fit, commerce usefulness, and artifact risk. Use for QA reports, reject queues, reroll decisions, and correction prompts.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
Turn a product URL or product image into a brand-aware ecommerce shoot plan: brand read, visual gap audit, shoot strategy, shot list, GPT Image-ready prompts, QA rubric, and export map. Use for PDP/lifestyle/model/seasonal product photography systems. Do not use for ad spying, competitor ad intelligence, paid-social creative mining, or media-buying analysis.
Extract brand/product evidence from an ecommerce product URL before any Brand Shoot Kit planning or generation. Use for PDP scouting, source evidence capture, product image URL collection, degraded-mode notes, and scout.json creation. Do not use for ad spying or competitor ad research.
Package approved Brand Shoot Kit assets into channel-specific ecommerce export folders and manifests. Use for PDP/social/email/marketplace maps, naming, export manifests, and handoff-ready asset organization.
Write reusable Brand Shoot Kit memory after a product shoot: product preservation lessons, winning visual directions, failed prompts, QA risks, and future-shot guidance.
Create the immutable product truth and preservation brief for Brand Shoot Kit outputs. Use when product shape, packaging, label text, claims, variants, compliance, or distortion risk must be protected before image generation.
Write GPT Image-ready ecommerce product photography prompts from a Brand Shoot Kit shot list and product preservation brief. Use for prompt packs, negative constraints, reroll instructions, and category-aware generation guidance.
| name | qa-reroll |
| description | Score generated Brand Shoot Kit images for product accuracy, realism, brand fit, commerce usefulness, and artifact risk. Use for QA reports, reject queues, reroll decisions, and correction prompts. |
| metadata | {"openclaw":{"emoji":"✅","user-invocable":true,"primaryEnv":"OPENAI_API_KEY","requires":{"bins":["python3"],"env":[]}}} |
Do not pass pretty failures.
Use scripts/qa-images.py --packet <packet> to write structured QA results. Failed shots should produce concrete reroll instructions, not vague criticism.
Executable module owner path:
scripts/modules/qa_reroll.py --packet <packet-dir> --run-qa -> updates qa-results.json and writes reroll-manifest.json