From design-style-picker
Batch-generates and compares visual design directions so developers can choose a style without describing abstract visuals. Preserves existing assets and generates structured style matrices.
How this skill is triggered — by the user, by Claude, or both
Slash command
/design-style-picker:design-style-pickerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use this skill to turn vague taste into concrete visual choices. The goal is not to guess one final design; it is to generate a structured set of options that exposes the user's taste boundary quickly.
Use this skill to turn vague taste into concrete visual choices. The goal is not to guess one final design; it is to generate a structured set of options that exposes the user's taste boundary quickly.
Do not ask the user to describe an abstract style if they already said they cannot. Generate comparable visual evidence, let them pick, then implement from the selected references.
Restate The Real Target
Collect Existing Assets First
Generate A Matrix, Not Minor Variants
Use Color As A System
Review Before Presenting
Implement From Selected Images
When generating images, include:
This is an evolution of the existing UI/design system, not a replacement.
Preserve these assets: <tokens, imagery, sections, components, brand cues>.
Axis: <vertical ladder or horizontal direction>.
Variant name: <clear label>.
Color/visual rule: <specific budget or organization method>.
Primary focal point: <one thing>.
Avoid: <known rejected styles from the user>.
references/selection-playbook.md when running a full style-selection session or when the user gives taste corrections during image exploration.npx claudepluginhub daymade/claude-code-skills --plugin design-style-pickerGuides reception of code review feedback: verify before implementing, avoid performative agreement, push back with technical reasoning when needed.
Design banners for social media, ads, website heroes, and print with multiple art direction options and AI-generated visuals.