daymade/claude-code-skills

design-style-picker

Batch-generate and compare visual design directions so a user can choose the style they actually want.

소스 보기

사용 방법

  1. 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
  2. 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
  3. 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/daymade/claude-code-skills --skill design-style-picker

시작 전 확인

  • 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
  • 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서

원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.

Design Style Picker

Purpose

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.

Core Rule

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.

Workflow

  1. Restate The Real Target
  • Say what the user is actually choosing: design-system style, business app surface, landing page, deck, component library, etc.
  • Separate the primary artifact from validation samples. If the task is a design system, business screens are optional validation samples, not the main deliverable.
  • Preserve any existing UI, assets, tokens, layout, brand cues, and domain context unless the user explicitly asks to discard them.
  1. Collect Existing Assets First
  • Inspect the current rendered UI or screenshots.
  • Read design tokens, CSS variables, component names, key images, brand/domain references, and existing screenshots.
  • Treat current assets as the starting vocabulary. Do not generate unrelated "fresh" concepts over them.
  1. Generate A Matrix, Not Minor Variants
  • Use at least two axes when taste is unclear:
  • Vertical ladder: one dimension changes by large steps, such as color intensity 20/35/50/65/80.
  • Horizontal directions: different organization strategies, such as data-driven color, brand spine, warm product imagery, scenario modules, or governance-led layout.
  • Make options visibly different. If two images look like siblings, regenerate one with a clearer contrast.
  • Prefer batch generation. The user is waiting for selection, not watching one slow image at a time.
  1. Use Color As A System
  • "Less colorful" does not mean black-and-white. It usually means fewer competing focal points.
  • Keep the product palette alive, but assign color roles:
  • Broad zones and section bands for architecture.
  • Data visualization and evidence systems for multi-color semantics.
  • Brand/risk colors for rare, high-signal emphasis.
  • Neutral components for routine UI.
  • Include explicit upper-bound samples when the user is tuning color: safe, middle, high, and overload boundary.
  1. Review Before Presenting
  • Open generated images yourself.
  • Mark which are likely too dead, too colorful, too generic, too business-system-like, or closest to the target.
  • Present file paths and a short decision note for each useful candidate.
  1. Implement From Selected Images
  • Extract principles, not pixels: color roles, layout density, focal hierarchy, component treatment, image use, governance/data placement.
  • Fuse selected references explicitly. Example: "Use H02 for color placement and V04 for palette intensity."
  • Keep implementation scoped to the existing UI unless the user asks for a new artifact.
  • Run rendered visual QA after implementation.

Prompt Pattern

When generating images, include:

text
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>.

Lessons To Preserve

  • A user saying "not colorful" may mean "no dozens of equal-weight small color chips", not "remove all color".
  • A user saying "more weight" may mean visual authority and hierarchy, not dark-mode control room.
  • For design-system work, do not replace the system with a business dashboard. Business screens can validate style, but should not become the answer.
  • Always create deliberate boundary samples. They make "too much" visible and speed up selection.
  • After selection, fuse the chosen references and name what each contributes.

References

  • Read references/selection-playbook.md when running a full style-selection session or when the user gives taste corrections during image exploration.

관련 작업

같은 저장소의 Skills

더 많은 Skills

모든 Skills
daymade
커뮤니티

github-ops

Operates GitHub via gh CLI and REST/GraphQL — PRs, issues, Actions, repos, collaborators, org permissions, 2FA — with explicit target, authorization, and independent readback. Use when a write reports success but state didn't change, or choosing gh/REST/GraphQL/UI-only. Not for local Git recovery (use git-safety-net), maintainer PR review (use github-review-pr), or upstream contribution (use github-contributor).

설치 수
2
GitHub Stars
1.5천
업데이트
10월 20일
daymade
커뮤니티

audio-router

Routes audio: StepFun ASR/语音识别, StepFun TTS/配音, transcript/妙记→会议纪要, merge/review minutes. Reads one bundled specialist; generic ASR and correction stay direct.

설치 수
2
GitHub Stars
1.5천
업데이트
10월 20일
daymade
커뮤니티

product-analysis

Multi-path parallel product analysis with cross-model test-time compute scaling. Spawns parallel agents (Claude Code agent teams + Codex CLI) to explore product from multiple perspectives, then synthesizes findings into actionable optimization plans. Can invoke competitors-analysis for competitive benchmarking. Use when "product audit", "self-review", "发布前审查", "产品分析", "analyze our product", "UX audit", or "信息架构审计".

설치 수
2
GitHub Stars
1.5천
업데이트
10월 15일
daymade
커뮤니티

fact-checker

Verifies factual claims in documents using web search and official sources, then proposes corrections with user confirmation. Use when the user asks to fact-check, verify information, validate claims, check accuracy, or update outdated information in documents. Supports AI model specs, technical documentation, statistics, and general factual statements.

설치 수
1
GitHub Stars
1.4천
업데이트
10월 4일