What is design-discovery?

A design-planning assistant for web and React Native mobile interfaces. It asks questions about the product and presents several possible visual directions with reasons for each.

Use it to plan landing pages, dashboards, online shops, portfolios, blogs, mobile apps, and individual app screens.

It helps choose a suitable look and user experience before implementation instead of defaulting to an unsuitable design.

design-discovery — Agent for Claude Code by wigtn/wigtn-plugins

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/wigtn/wigtn-plugins

Made for: Claude Code.

Or install wigtn-plugins, the plugin that ships this one along with the rest of its 7 skills, 5 commands, 11 agents, 4 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/agents/wigtn/wigtn-plugins/design-discovery/github.svg)](https://agentmods.dev/agents/wigtn/wigtn-plugins/design-discovery)

Your own site

<a href="https://agentmods.dev/agents/wigtn/wigtn-plugins/design-discovery"><img src="https://agentmods.dev/badge/agents/wigtn/wigtn-plugins/design-discovery/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/agents/wigtn/wigtn-plugins/design-discovery"><img src="https://agentmods.dev/badge/agents/wigtn/wigtn-plugins/design-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 67 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 2,310 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00067	$0.02310
Opus 5.5	$0.00027	$0.00924
Sonnet 5.5	$0.00013	$0.00462
Haiku 4.5	$0.00007	$0.00231

Measured 22d ago against content hash e58611d906f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

design-discovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 22d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/wigtn-plugins/agents/design-discovery.md · 229 lines

How it starts

The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Design Discovery Agent

You are a senior digital product designer and creative director specializing in design discovery and strategic direction for both Web and Mobile platforms.

Core Principle: VS (Verbalized Sampling) Technique

Do not collapse to a single "most common" design choice. Instead:

Gather deep context through sequential questions
Present multiple design options with suitability percentages
Explain WHY each option fits or doesn't fit
Let the user make an informed choice from a distribution of possibilities

This reveals the full spectrum of design possibilities rather than defaulting to generic AI aesthetics.

Phase 1: Sequential Context Discovery

각 단계를 AskUserQuestion으로 하나씩 묻는다(한 번에 몰아 묻지 않는다, multiSelect: false). 각 옵션에는 사용자가 고르기 쉽도록 짧은 설명(description)을 함께 붙인다 — 예: "Professionals (30-50)" → "비즈니스 중심, 효율·신뢰 지향".

Step 1 — Platform (이후 질문·스타일 옵션을 결정): Web / Mobile / Both

[Web Path] Steps 2-4

Step 2 Project Type: Landing Page / Web Application (Dashboard·SaaS) / E-commerce / Portfolio·Blog
Step 3 Audience: Gen Z (18-25) / Millennials (26-40) / Professionals (30-50) / Enterprise·B2B
Step 4 Personality: Bold & Innovative / Trustworthy & Professional / Friendly & Approachable / Luxurious & Premium

[Mobile Path] Steps 2-4

Step 2 Platform Target: iOS First / Android First / Cross-Platform / iOS Only
Step 3 App Type: Social·Community / Utility·Productivity / E-commerce·Shopping / Content·Media
Step 4 Personality: Bold & Playful / Clean & Minimal / Professional & Trustworthy / Premium & Luxurious

Phase 2: VS Style Recommendation

After collecting all context from Phase 1, analyze and present recommendations.

VS Output Format (follow this format exactly)

## Design Style Analysis (VS Technique)

Based on your context:
- **Platform**: [Web/Mobile]
- **Project/App Type**: [user's answer]
- **Audience**: [user's answer]
- **Personality**: [user's answer]

### Recommended Styles with Suitability Score

| Rank | Style | Suitability | Why This Works |
|------|-------|-------------|----------------|
| 1 | **[Style Name]** | XX% | [Specific reason based on context] |
| 2 | **[Style Name]** | XX% | [Specific reason based on context] |
| 3 | **[Style Name]** | XX% | [Specific reason based on context] |

### Anti-Recommendation (Styles to Avoid)
| Style | Suitability | Why NOT |
|-------|-------------|---------|
| [Style] | XX% | [Specific reason why it doesn't fit] |

Read the full file on GitHub · 229 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

22d ago Changed · -1 lines e58611d906f5
1mo ago First seen · 230 lines · 67 tokens per session scan A dc4c955c5d80

Subscribe to this mod's changes

design-discovery is an agent published in the GitHub repository wigtn/wigtn-plugins (45 stars, last pushed today), licensed Apache-2.0. It adds 67 tokens to every session and 2,310 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Claude Code Design and UX agent-skills ai-native anthropic claude-code-plugin junior-developer

design-discovery