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Build high-quality image generation and edit prompts from user intent using prompt structures proven across prompts.chat examples and OpenAI image prompting guidance.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Make interfaces production-ready: error handling, empty states, onboarding flows, i18n, text overflow, and edge case management. Use when the user asks to harden, make production-ready, handle edge cases, add error states, design empty states, improve onboarding, or fix overflow and i18n issues.
Adapt designs to work across different screen sizes, devices, contexts, or platforms. Implements breakpoints, fluid layouts, and touch targets. Use when the user mentions responsive design, mobile layouts, breakpoints, viewport adaptation, or cross-device compatibility.
Review a feature and enhance it with purposeful animations, micro-interactions, and motion effects that improve usability and delight. Use when the user mentions adding animation, transitions, micro-interactions, motion design, hover effects, or making the UI feel more alive.
Run technical quality checks across accessibility, performance, theming, responsive design, and anti-patterns. Generates a scored report with P0-P3 severity ratings and actionable plan. Use when the user wants an accessibility check, performance audit, or technical quality review.
Amplify safe or boring designs to make them more visually interesting and stimulating. Increases impact while maintaining usability. Use when the user says the design looks bland, generic, too safe, lacks personality, or wants more visual impact and character.
Improve unclear UX copy, error messages, microcopy, labels, and instructions to make interfaces easier to understand. Use when the user mentions confusing text, unclear labels, bad error messages, hard-to-follow instructions, or wanting better UX writing.
| name | image-prompting |
| description | Build high-quality image generation and edit prompts from user intent using prompt structures proven across prompts.chat examples and OpenAI image prompting guidance. |
Use this skill before calling image-generation tools. Turn vague requests into a strong, production-ready JSON prompt object without relying on downstream tool rewriting.
openai-image-gen-mcp, OpenAI image APIs, or another image modelBuild the final prompt before the MCP/tool call.
For openai-image-gen-mcp, output a single JSON object and pass it as prompt_json. Do not hand the MCP a loose prose prompt when this skill is available.
Call the Skill tool directly with name image-prompting for this workflow. Do not rely on skill_find for this path.
Common winning ingredients from the prompts.chat IMAGE dataset and OpenAI image prompting docs:
Always return a JSON object with this shape:
{
"goal": "",
"subject": "",
"scene": "",
"composition": "",
"camera": "",
"lighting": "",
"style": "",
"details": [],
"constraints": [],
"negative_prompt": []
}
Optional fields when needed:
{
"text_in_image": "",
"preserve": [],
"change": [],
"output_rules": []
}
Rules:
Fill the JSON in this order:
goalsubjectscenecompositioncameralightingstyledetailsconstraintsnegative_promptoutput_rules if neededFor edits, you MUST separate what changes from what stays locked.
Use these JSON fields:
{
"change": ["what to transform"],
"preserve": ["what must remain exact"],
"constraints": ["change only X", "keep everything else the same"]
}
When the prompt uses reference people or products:
EXACT, verbatim, or appears onceUse negative constraints whenever realism or polish matters. Typical items:
When the target tool is openai-image-gen-mcp:
prompt_json object for the handoff.change vs preserve?