About this skill
A visual-prompt skill for turning an idea into detailed prompts for Midjourney and similar image models, including subject, composition, style, lighting and scene details.
Use this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A visual-prompt skill for turning an idea into detailed prompts for Midjourney and similar image models, including subject, composition, style, lighting and scene details.
Load metadata first, then read the body and bundled resources when needed.
Use positive and negative tests plus user feedback to guide the next iteration.
Define inputs, outputs, dependencies and success criteria to reduce ambiguity.
Skill files
Ultra-detailed restoration and sharpness enhancement of a vintage photo. Recover fine details and improve clarity, especially on faces. Remove all scratches, dust, stains, tears. Preserve natural film grain. Correct geometry and tonal range.
Then, colorize it to look like a historical color photograph: natural, muted, historically accurate colors. Avoid plastic skin, oversaturation, digital painting look, and oversharpening artifacts. Museum-quality realism.nameUltra-Detailed Vintage Photo Restoration and ColorizationdescriptionUse this skill when the user needs the workflow described above, especially when they want a structured result rather than a one-off answer. A visual-prompt skill for turning an idea into detailed prompts for Midjourney and similar image models, including subject, composition, style, lighting and scene details.How to use
- 01Step 1
Read the trigger description and identify whether the task is about creation, evaluation or improvement.
- 02Step 2
Open SKILL.md and confirm the input, output and bundled resource requirements.
- 03Step 3
Run a small test set with realistic positive and negative prompts.
- 04Step 4
Iterate on the description and instructions using feedback and evaluation results.
Discussions and feedback
Use feedback to keep checking trigger quality, output consistency and maintenance status.