gpt-taste
gpt taste
Full skill instructions
Generate a catalog of 5-8 design proposals before implementing anything.
All proposal generation MUST be delegated to Kimi K2.5 via MCP.
Kimi excels at frontend/visual work. Claude orchestrates, Kimi implements:
// Generate proposals in parallel (4.5x faster than sequential)
mcp__kimi__spawn_agents_parallel({
agents: [
{ prompt: "Generate proposal 1: [DNA code]. Output: .design-catalog/proposals/01-[name]/", thinking: true },
{ prompt: "Generate proposal 2: [DNA code]. Output: .design-catalog/proposals/02-[name]/", thinking: true },
// ... 5-8 total proposals
]
})
Workflow:
Design is visual and iterative. Showing options before implementing:
Skill("frontend-design") # Philosophy
Skill("aesthetic-system") # Strategic direction
Skill("ui-skills") # Implementation constraints
If $1 provided (route or URL):
If no argument:
gemini "Analyze this [product type] for distinctive design directions.
Research 2025 trends. Anti-convergence: avoid Inter, Space Grotesk,
purple gradients, Tailwind default blue-500."
For EACH proposal:
/rams — Must score ≥70/100DNA variety rule: No two proposals share >2 axes.
mkdir -p .design-catalog && cd .design-catalog
python -m http.server 8888 &
Open in browser, screenshot, present:
Design Catalog Ready
[N] proposals passed validation. Live: http://localhost:8888
1. [Name] - [soul] - DNA: [code] - RAMS: [score]/100
2. [Name] - [soul] - DNA: [code] - RAMS: [score]/100
...
Browse, compare, tell me which 2-3 resonate.
User selects favorites → generate hybrids → re-validate.
Verify NO proposal uses:
Catalog ready for user selection. Next: User picks direction → /design-theme.
gpt taste
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