skills/sketch/SKILL.md
拋棄式 HTML mockup 比稿:產出 2 到 3 個設計立場不同的變體(密度 / 版式 / 強調軸,不是換色),各附取捨說明,最後給有立場的對比結論。適用:「畫個草圖」「比較 A 版 B 版」「先看方向再做」「給我看幾種做法」。要 production 元件或設計已定案時不適用。
npx skillsauth add seikaikyo/dash-skills sketchInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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在投入實作前,用 2 到 3 個可互動的拋棄式 HTML mockup 比較設計方向。每個變體是一個自足的 HTML 檔:inline CSS、擬真內容、基本互動。目的是視覺比較,不是可出貨的程式碼。
只做一版是原型不是比稿,比稿的價值在正面對決。兩個變體多一倍工,消掉八成重做風險。
不適用:要 production 元件(走 frontend-design / interface-design 正規做)、要單一精緻 HTML 成品、要圖表或架構圖、設計已定案(直接做)。
intake → 變體 → 正面對決 → 選出勝者(或再一輪)
產變體前先拿到三件事,一次一題:
每個變體要有不同的設計立場,不是不同的像素值。可用的立場軸:
挑一條軸拉開距離。只差主色的兩個變體是浪費,使用者無法區辨。
每個變體是單一自足 HTML 檔:
<style>,不需建構步驟寫完用 agent-browser 開 file:// 截圖實看,抓純看原始碼看不出的版面問題(字型載入失敗、flex 容器塌掉),修到每個變體看起來是對的。
## 變體:<立場名>
### 設計立場
一句話講驅動這個變體的原則。
### 關鍵選擇
版式 / 字型 / 色彩 / 互動各一行。
### 取捨
強在哪、弱在哪。
### 適合誰
這個變體實際服務的使用者或情境。
全部做完後給對比,不能只列清單,要有立場:
| 維度 | 安靜編輯感 | 工具感高密度 | 玩心分割版 |
|------|-----------|-------------|-----------|
| 密度 | 低 | 高 | 中 |
| 主動作可見度 | 低 | 高 | 中 |
| 掃讀性 | 高 | 中 | 低 |
我的判斷:重度使用者選工具感高密度,內容導向選安靜編輯感。
玩心分割版最弱,兩頭想抓、兩頭不沾。
讓使用者選勝者、合併兩案成混血、或再來一輪。
open <路徑>/index.html草圖夠互動的標準:主動作點下去有可見反應(狀態變化、modal、toast)、至少一個有意義的狀態轉換、可辨識的元件有 hover。超過這些是過度打磨拋棄品,低於這些是截圖。
tools
Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.
tools
Parse Windows forensic artifacts—$MFT/$J (MFTECmd), Prefetch (PECmd), registry hives (RECmd), shellbags, and Amcache—into normalized CSV/JSON with Eric Zimmerman's EZ Tools, then load results into Timeline Explorer for analysis. Use during DFIR/incident-response investigations, after triage collection (e.g. with KAPE), to establish program execution, file/folder access, and persistence evidence from acquired forensic images.
development
Build automated multi-turn adversarial attacks against conversational LLM targets using Microsoft PyRIT's RedTeamingOrchestrator, CrescendoOrchestrator (gradual escalation), and TreeOfAttacksWithPruningOrchestrator (adaptive branching), with scorer feedback loops and persisted conversation memory. Use when single-shot LLM scanning is insufficient and you need multi-turn, scorer-driven AI red-team campaigns against a chatbot or agent.
testing
Stand up MISP, enable and cache curated threat feeds (CIRCL, abuse.ch, Feodo Tracker), apply warninglists to suppress false positives, query indicators with PyMISP, and export attributes as auto-generated Suricata/Sigma/Wazuh detection rules. Use when maturing a MISP instance to actively drive detection, curating threat feeds with quality controls, or automating IOC-to-detection pipelines for the SIEM/IDS.