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概要と使いどころ
Route HugeGraph MCP graph data extraction and controlled import/delete tasks to stable public tools. Use when the user asks to extract graph data from text, import structured vertices or edges, verify an import, or asks whether table, SQL, update, or delete graph writes are available.
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。
Use when code needs a judgment about natural language that rules or regex cannot make (classify, route, triage, moderate, score, rank, match, dedupe, filter, extract, verify, or gate an action), when brainstorming where AI could fit in an app, when an LLM call exists only to pick a label, score, or yes/no, or when code uses TypeSafe AI, Jev, System One, typesafe-sdk, or @typesafe-ai/sdk.
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。
Inspect or invoke locally registered ArkCLI actions when product commands cannot cover a task. Use for registry errors or exact raw payloads. Not for public API catalogs or OpenAPI schemas.
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 the end-to-end service delivery system including frontstage actions, backstage processes, and supporting infrastructure.
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 refined user personas from research data with demographics, goals, frustrations, and behavioral patterns. Use when synthesizing user research into actionable persona profiles for design decisions.
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。
Summarize a user interview transcript into structured insights with key themes, quotes, and action items. Use after conducting user interviews to extract and share findings efficiently.
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 adaptive layouts and interactions that work across all screen sizes and input methods.
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。
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。
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。
Design system feedback for user actions including confirmations, status updates, and notifications.
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 an emotional resonance lens to any UI. Use when a design is technically correct but flat — to identify what's missing and prescribe specific changes at the copy, motion, and interaction layer.
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。
Extract, suggest, and sync tags and categories for blog posts across all major CMS platforms. Supports WordPress REST API, Shopify GraphQL, Ghost Content API, Strapi REST/GraphQL, and Sanity GROQ. Generates tag suggestions from content analysis (keyword frequency, heading extraction, semantic grouping), enforces minimum post-count thresholds to prevent thin tag archives, and syncs taxonomy via authenticated API calls. Use when user says "tags", "categories", "taxonomy", "tag suggestions", "sync tags", "WordPress tags", "Shopify tags".
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。
Facilitate structured design critiques with clear feedback frameworks and actionable outcomes.
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。
Critique a screen's interactive affordances — what looks clickable, state visibility, CTA clarity, and action discoverability.
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 a set of actionable design principles that guide decision-making and resolve trade-offs.
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 domain's AI-readiness by using curl to directly probe robots.txt, llms.txt, and llms-full.txt, then scores each file against a structured checklist and delivers a formatted report with pass/warn/fail findings and actionable fixes. Use this skill whenever a user provides a domain or URL and wants to know if llms.txt or llms-full.txt is available, discoverable, or properly structured. Trigger on phrases like "check llms.txt for", "does this site have llms.txt", "find llms.txt", "check llms for this url", "audit llms.txt", "is llms-full.txt available", or any time a user shares a domain/docs URL and wants AI-readiness checked. Also trigger when the user wants to verify GEO/AEO readiness of a documentation site.
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。
Full-site blog health assessment scanning all blog files for quality scores, orphan pages, topic cannibalization, stale content, and AI citation readiness. Spawns parallel subagents for comprehensive analysis. Produces per-post scores and a prioritized action queue. Use when user says "audit blog", "blog audit", "site audit", "blog health", "audit all posts", "check all blogs".
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 and manage writing personas with NNGroup 4-dimension tone framework (Funny-Serious, Formal-Casual, Respectful-Irreverent, Enthusiastic-Matter-of-fact). Personas define readability targets, sentence length distribution, vocabulary tier, contraction frequency, and summary box label. Used by blog-write and blog-rewrite to enforce consistent voice. Use when user says "persona", "voice", "tone", "writing style", "brand voice", "create persona", "use persona".
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 animation principles to UI motion for purposeful, polished interactions.
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。
AI image generation and editing for blog content powered by Gemini via MCP. Claude acts as Creative Director - interpreting intent, selecting domain expertise, constructing optimized 6-component prompts (Subject + Action + Context + Composition + Lighting + Style), and orchestrating Gemini for blog-quality results. Generates hero images, inline illustrations, social preview cards, and OG images. Edits existing blog images. Supports 6 blog-optimized domain modes (Editorial, Product, Landscape, UI/Web, Infographic, Abstract). Works standalone via /blog image or internally from blog-write and blog-rewrite workflows. Falls back gracefully when MCP is not configured. Use when user says "blog image", "generate hero image", "blog illustration", "social card", "generate blog image", "edit blog image", "image generate", "blog cover image", "inline image", "OG image".
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。
Your For You page for content creators. Scrapes tracked competitors across social media platforms, scores what's performing, and turns it into actionable, differentiated content ideas backed by real engagement data. Use this whenever the user wants competitor/creator research, a content feed or "for you" page, trending-topic ideas in their niche, to see what's working on social, to track what creators are posting, or to generate video/post briefs from what's performing — even if they don't say "find ideas." First run walks through setup.
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。
Use when verifying that requirements/specs/PRDs and their implementation plans match — before starting work, after a spec or plan update, or when suspecting coverage gaps, scope creep, or design drift between intent and action documents. Needs both documents; not for checking code against a spec.
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。
定义与用户之间的交互策略：何时反问、何时直接执行、何时交付结果。在任何需要判断"是否该停下来和用户沟通"的场景中参考本 skill。
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。