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design_theme

Generate a production-ready design system (colors, typography, spacing, shadows, transitions) as CSS custom properties, tailored to your industry and design tone.

Instructions

Phase 3 — Generate a complete, production-ready design system based on business context.

Returns: color palette (primary, secondary, accent, neutrals, semantic), typography (with Google Fonts link), spacing (8px grid), shadows, border radius, transitions — all as CSS custom properties.

The theme is NEVER randomly dark or light — it's chosen based on industry (fintech → light + navy, gaming → dark + neon, etc.). Colors avoid the AI-telltale purple-blue gradient.

Call this AFTER analyze_project and plan_architecture, BEFORE select_components.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toneYesDesign tone/personality. Examples: "modern", "corporate", "playful", "minimal", "luxury", "technical", "warm", "bold", "elegant"
industryYesBusiness industry or type. Examples: "fintech", "healthcare", "saas", "ecommerce", "restaurant", "law firm", "gaming studio", "luxury fashion", "startup", "nonprofit"
brandColorNoOptional brand hex color to use as primary (e.g., "#2563EB"). If omitted, the engine picks the best color for your industry.
themePreferenceNoForce light/dark theme, or let the engine decide based on industry (recommended: "auto")
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses that theme selection is never random and is based on industry, and that colors avoid typical AI gradients. This adds meaningful behavioral context beyond the schema, though it could mention permissions or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: first sentence states action, then lists return values, then explains behavioral nuance, then provides ordering. Every sentence is informative with no redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (generating a design system) and no output schema, the description adequately covers return values, selection logic, and ordering. It omits potential error cases or prerequisites (like requiring prior phases), but overall it is sufficiently complete for an AI agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with all parameters described. The description adds value by explaining that brandColor is optional and that themePreference allows forcing light/dark, with 'auto' recommended. It also gives examples for industry and tone, enriching meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a complete design system from business context. It lists what is returned (color palette, typography, etc.) and distinguishes from siblings by specifying its phase order (after analyze_project and plan_architecture, before select_components).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states the call order relative to sibling tools (AFTER analyze_project and plan_architecture, BEFORE select_components), providing clear context. However, it does not include exclusions or when not to use the tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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