Build a 4-quadrant empathy map (Says, Thinks, Does, Feels) to synthesize user research into actionable insights. Use when you need to quickly capture and share user understanding across the team.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Build a 4-quadrant empathy map (Says, Thinks, Does, Feels) to synthesize user research into actionable insights. Use when you need to quickly capture and share user understanding across the team.
日本語の概要は準備中です。原文の説明を表示しています。
Create a structured user interview script with warm-up, core exploration, and wrap-up sections. Use when preparing for user research interviews to ensure consistent, insightful conversations.
日本語の概要は準備中です。原文の説明を表示しています。
Apply the Doherty Threshold — keep system response times under 400ms to maintain user flow and perceived performance.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," "lifecycle emails," "trigger-based emails," "email funnel," "email workflow," "what emails should I send," "welcome series," or "email cadence." Use this for any multi-email automated flow. For cold outreach emails, see cold-email. For in-app onboarding, see onboarding.
日本語の概要は準備中です。原文の説明を表示しています。
Create a holistic experience map showing the full ecosystem of user touchpoints, channels, and relationships.
日本語の概要は準備中です。原文の説明を表示しています。
Create an icon system specification covering grid, sizing, naming, categories, and implementation guidance.
日本語の概要は準備中です。原文の説明を表示しています。
Map user Jobs-to-Be-Done with functional, emotional, and social dimensions plus outcome expectations. Use when reframing product decisions around user motivations rather than features.
日本語の概要は準備中です。原文の説明を表示しています。
Create developer handoff specifications with measurements, behaviors, assets, and edge cases.
日本語の概要は準備中です。原文の説明を表示しています。
Define an illustration style guide with visual language, color usage, and application rules.
日本語の概要は準備中です。原文の説明を表示しています。
Design gesture-based interactions for touch and pointer devices.
日本語の概要は準備中です。原文の説明を表示しています。
Email triage system that handles both one-time setup and recurring triage in a single skill. Auto-detects state: if no knowledge base exists at ${WORKSPACE}/Email/, runs an 8-section onboarding interview (grill-me discipline, one question at a time) to build a 7-file personalized KB, then offers to run triage immediately. If the KB already exists, skips setup and goes straight to triage — searches recent emails, classifies them via the user's taxonomy, researches new senders, generates TAKE IT/WORTH/PASS/FLAG recommendations, drafts replies (NEVER sends), delivers a report, and updates the KB. Use with 'update' argument to refresh preferences. Setup triggers: 'set up my inbox', 'configure inbox triage', 'set up my email system', 'configure email triage', 'build my email knowledge base', 'initialize email management'. Triage triggers: 'triage my inbox', 'inbox triage', 'check my email', 'run email triage', 'process my inbox', 'what's new in my email', 'handle my email', 'email triage'.
日本語の概要は準備中です。原文の説明を表示しています。
Design the structure, hierarchy, and navigation model for a product's content and features.
日本語の概要は準備中です。原文の説明を表示しています。
Craft-first interface design for dashboards, admin panels, SaaS apps, tools, settings pages, data interfaces, and interactive products. Use when designing, building, reviewing, auditing, or refining product UI where visual craft, layout hierarchy, tokens, states, visual direction, or design-system consistency matter. Not for marketing pages, landing pages, campaigns, or brand-only work.
日本語の概要は準備中です。原文の説明を表示しています。
Cluster a list of keywords into topical groups with search intent labels, validated search volume, KD, and CPC data. Use this skill whenever a user provides a list of keywords (pasted, uploaded as CSV/Excel, or via Google Sheet URL) and asks to cluster, group, map, organize, or categorize them. Also trigger when a user says "keyword cluster", "cluster my keywords", "group these keywords", "keyword map", "keyword strategy from this list", "organize keywords by topic", or pastes or uploads a list of keywords and wants structure from it. Always use this skill — do not attempt keyword clustering manually without following this workflow.
日本語の概要は準備中です。原文の説明を表示しています。
Audit and optimize content for SEO, GEO (generative engine optimization), and AEO (answer engine optimization). Use when user asks to "audit SEO", "check search visibility", "optimize for AI search", "generate schema markup", "validate metadata", "extract keywords", "optimize for Perplexity/ChatGPT/Gemini", "check Open Graph tags", "submit to IndexNow", or mentions SEO, GEO, AEO, or search optimization. Do NOT use for creating new content from scratch or image optimization.
日本語の概要は準備中です。原文の説明を表示しています。
Optimize existing blog posts and web content for GEO (Generative Engine Optimization) — AI search visibility on ChatGPT, Perplexity, Claude, and Google AI Overviews. Use whenever a user provides a blog URL or pastes existing content and asks to optimize it for AI search, rewrite for LLM visibility, improve GEO score, make content answer-first, add FAQ sections, restructure headings for AI retrieval, improve citation potential, or audit content for AI readiness. Also triggers on "GEO optimize this", "make this AI-search ready", "rewrite for Perplexity", "optimize for ChatGPT", "optimize for Google AI Overviews", "improve AI visibility", "reformat for AI search", "make this content citation-worthy", "content isn't showing up in AI search", "why isn't my blog cited by AI", "GEO audit", "answer-first rewrite", "restructure for AI", "make my blog AI-friendly", "improve LLM citability". Do NOT trigger for writing new content from scratch — use geo-content for that.
日本語の概要は準備中です。原文の説明を表示しています。
Generate STAR stories, practice questions, and talking points from resume
日本語の概要は準備中です。原文の説明を表示しています。
Audits any landing or service page across 48 checks in 10 categories for LLM/AI discoverability, GEO readiness, content clarity, schema markup, internal linking, freshness signals, and technical crawlability. Produces an overall score out of 100, a per-category score out of 100, pass/warn/fail/ manual counts, and a prioritised fix list — all rendered as a standalone HTML report saved to disk. Use when a user provides a URL and asks to audit it, score it, check its GEO readiness, test its AI discoverability, run a landing page audit, or evaluate it for LLM citation potential. Also trigger on phrases like "audit this page", "score this URL", "check GEO for", "is this page AI-ready", "run a GEO audit", "LLM page check", "how would AI read this page", or "landing page score".
日本語の概要は準備中です。原文の説明を表示しています。
Guidance for distinctive, intentional visual design when building new UI or reshaping an existing one. Helps with aesthetic direction, typography, and making choices that don't read as templated defaults.
日本語の概要は準備中です。原文の説明を表示しています。
When the user wants to plan, evaluate, or build a free tool for marketing purposes — lead generation, SEO value, or brand awareness. Also use when the user mentions "engineering as marketing," "free tool," "marketing tool," "calculator," "generator," "interactive tool," "lead gen tool," "build a tool for leads," "free resource," "ROI calculator," "grader tool," "audit tool," "should I build a free tool," or "tools for lead gen." Use this whenever someone wants to build something useful and give it away to attract leads or earn links. For downloadable content lead magnets (ebooks, checklists, templates), see lead-magnets.
日本語の概要は準備中です。原文の説明を表示しています。
Apply Fitts's Law to size and position interactive targets for fast, accurate interaction.
日本語の概要は準備中です。原文の説明を表示しています。
Create C-suite and VP level resumes emphasizing strategic leadership
日本語の概要は準備中です。原文の説明を表示しています。
Design error prevention, detection, and recovery experiences.
日本語の概要は準備中です。原文の説明を表示しています。
Design a diary study plan with prompts, duration, participant criteria, and analysis framework. Use when you need to understand user behavior over time in natural contexts.
日本語の概要は準備中です。原文の説明を表示しています。