design-an-interface/SKILL.md
Generates multiple radically different interface designs for a module using parallel sub-agents. Use when user wants to design an API, explore interface options, compare module shapes, or mentions "design it twice".
npx skillsauth add kayaman/skills design-an-interfaceInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Based on "Design It Twice" from "A Philosophy of Software Design": your first idea is unlikely to be the best. Generate multiple radically different designs, then compare.
Before designing, understand:
Ask: "What does this module need to do? Who will use it?"
Spawn 3+ sub-agents simultaneously using Task tool. Each must produce a radically different approach.
Prompt template for each sub-agent:
Design an interface for: [module description]
Requirements: [gathered requirements]
Constraints for this design: [assign a different constraint to each agent]
- Agent 1: "Minimize method count - aim for 1-3 methods max"
- Agent 2: "Maximize flexibility - support many use cases"
- Agent 3: "Optimize for the most common case"
- Agent 4: "Take inspiration from [specific paradigm/library]"
Output format:
1. Interface signature (types/methods)
2. Usage example (how caller uses it)
3. What this design hides internally
4. Trade-offs of this approach
Show each design with:
Present designs sequentially so user can absorb each approach before comparison.
After showing all designs, compare them on:
Discuss trade-offs in prose, not tables. Highlight where designs diverge most.
Often the best design combines insights from multiple options. Ask:
From "A Philosophy of Software Design":
Interface simplicity: Fewer methods, simpler params = easier to learn and use correctly.
General-purpose: Can handle future use cases without changes. But beware over-generalization.
Implementation efficiency: Does interface shape allow efficient implementation? Or force awkward internals?
Depth: Small interface hiding significant complexity = deep module (good). Large interface with thin implementation = shallow module (avoid).
tools
Guidance for designing charts, graphs, plots, dashboards, and data visualizations that communicate clearly and persuade. Use when creating or reviewing a visualization, choosing a chart type, picking a color palette, decluttering a busy graphic, fixing misleading axes or proportions, building a dashboard, annotating a figure, or turning data into a presentation, report, or data-driven story. Grounded in the standard data-visualization literature (Knaflic, Tufte, Cleveland & McGill, Cairo, Wilke, Munzner, Few, Berinato). Covers chart selection, graphical perception and encoding, color and accessibility, decluttering, graphical integrity, dashboards, and narrative. Does NOT cover building data pipelines or ETL, statistical modeling or analysis methods, BI tool/vendor selection, or general UI/UX layout (see ux-design-principles). Tool-agnostic, with optional Python recipes.
development
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development
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