video-workbench/investigations/2026-06-23-gpt-image-2-advi.../README.md

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# GPT Image 2 Advisor Prompt Quality Investigation V2
## Why V2 Exists
The first investigation over-weighted character / MV identity scenarios. That made the result too narrow for the user's actual video-workbench usage.
This V2 uses source scenes from:
- `C:\Users\wangq\Documents\Codex\knowledge-vault\prompts\GPT\强哥的策划导演\30_CASE_典型视频分镜案例.md`
- `C:\Users\wangq\Documents\Codex\knowledge-vault\prompts\GPT\强哥的策划导演\31_CASE_典型培训AI_PPT案例.md`
The weighted priority is:
```text
典型视频分镜(科普) > 典型培训AI > 人物造型
```
## Test Scope
This is only a prompt-quality investigation. It does not generate images and does not claim final image quality.
The current environment is still treated as `gpt-image-2` Advisor / Mode C for this investigation: prompt generation and comparison only.
## Case Mix
| Group | Weight | Cases |
| --- | ---: | --- |
| Science video storyboard | 55% | S-01 AI wave, S-03 AI float vs ocean, S-05 logic sandcastle, S-07 three brakes |
| Training AI PPT | 35% | P8 prompt engineering vs cognitive engineering, P12 score vs growth-state assessment, P18 education AI logic chain |
| Character / makeup-still | 10% | lightweight directory-boundary sample only |
## Files
- `cases.md`: source-derived cases and evaluation intent.
- `outputs/direct-prompts.md`: baseline prompts from or modeled closely on the GPT case files.
- `outputs/advisor-prompts.md`: Advisor-style prompts using `gpt-image-2` structure and relevant templates.
- `提示词质量综合调研报告.md`: weighted comparison and conclusion.
## Template References Used
- `gpt-image-2/SKILL.md`
- `references/prompt-writing.md`
- `references/slides-and-visual-docs/dense-explainer-slides.md`
- `references/slides-and-visual-docs/educational-diagram-slide.md`
- `references/infographics/comparison-infographic.md`
- `references/scenes-and-illustrations/concept-scene.md`