87 lines
3.6 KiB
Markdown
87 lines
3.6 KiB
Markdown
# Comparison
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## Rubric
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Scores are subjective prompt-text scores from 0 to 5. They judge whether the prompt is likely to be controllable and reusable in video-workbench. They do not judge generated image quality.
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| Dimension | Meaning |
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| --- | --- |
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| D1 Intent Decomposition | Separates goal, subject, scene, and output use. |
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| D2 Reference Role Control | Clarifies which reference preserves identity, wardrobe, pose, or style. |
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| D3 Composition Specificity | Defines camera, framing, aspect ratio, environment ratio, and motion. |
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| D4 Failure Prevention | Names predictable failure modes and avoids them. |
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| D5 Workflow Fit | Fits `projects/<project-id>/...` style production records and later review. |
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| D6 Model Usability | Gives image models concrete visual instructions without overloading readable text. |
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## Scores
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| Case | Direct Total / 30 | Advisor Total / 30 | Main Difference |
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| --- | ---: | ---: | --- |
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| T01 Identity makeup still | 20 | 27 | Advisor treats the result as `identity_ref`, not a final cinematic scene. |
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| T02 Wardrobe fullbody anchor | 18 | 27 | Advisor explicitly downgrades face likeness and prioritizes outfit geometry. |
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| T03 MV side-walking shot | 19 | 29 | Advisor separates identity, wardrobe, pose, and style references and guards against portrait drift. |
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| T04 Muddy boots detail | 22 | 28 | Advisor correctly avoids using identity as the primary reference. |
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| T05 Dense explainer slide | 18 | 27 | Advisor prevents the common error of asking the image model to render final readable text. |
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Average:
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| Prompt Type | Average / 30 |
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| --- | ---: |
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| Direct | 19.4 |
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| Advisor | 27.6 |
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## Findings
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At the prompt-text level, the Advisor workflow is materially stronger than direct prompting for this use case.
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The main improvement is not prettier language. It is production control:
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- It states whether an output is an identity anchor, wardrobe anchor, final shot, detail shot, or slide background.
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- It splits references into roles instead of treating all references as the same kind of input.
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- It encodes known failures from the prior run, especially portrait drift and overusing face identity.
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- It creates prompts that can be versioned, reviewed, and revised per shot.
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This supports the restructuring premise:
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```text
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GPT should output director cards and acceptance standards.
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Codex / video-workbench should render final image prompts using gpt-image-2 Advisor logic.
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```
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## Limits
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This does not prove final image quality. It proves only that the Advisor prompt artifacts are higher-quality production inputs under a text rubric.
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The next validation level should be:
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1. Pick 2-3 prompts from this investigation.
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2. Generate images on the same image platform.
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3. Judge image outcomes with the same acceptance criteria.
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4. Record whether the Advisor prompts actually reduce failure rates.
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## Path Implications
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The investigation supports adding a project-local character package folder for human-character projects:
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```text
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projects/<project-id>/makeup-still/
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identity-prompt-v1.md
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identity-ref-v1.png
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wardrobe-prompt-v1.md
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wardrobe-ref-v1.png
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pose-ref-notes.md
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acceptance-notes.md
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```
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This folder should exist only when a project needs a recurring human / character identity system. Non-character projects should not carry the folder.
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Stable Codex-side knowledge should not be buried in a single project. After owner acceptance, summarize this into `docs/` as video-workbench operating knowledge, likely:
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```text
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docs/image-prompt-advisor-workflow.md
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docs/makeup-still-directory-policy.md
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docs/reference-strategy-and-review-rubric.md
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```
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Do not write those stable docs before the owner accepts this investigation result.
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