「overview」の検索結果

Suede-affiliated AI search optimization discipline. Use when the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' The durable job: make content structurally extractable, citable, and agent-readable so AI systems surface and cite it. NOT FOR: traditional technical SEO audit (use suede-seo-audit) or launch-appeal grading (use suede-visibility-grader).

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Generate and maintain AI-readable markdown documentation for a codebase in docs/. Use this skill whenever the user asks to document their codebase, generate project docs, create architecture docs, update documentation after code changes, build a knowledge base for AI agents, create onboarding docs, map out a codebase, or explain a project structure. Also trigger when users say things like "document this repo", "create docs for my project", "update the docs", "write architecture documentation", "help AI understand my code", "generate a codebase overview", or "maintain docs". This skill is specifically about creating structured markdown files in a docs/ directory that serve as a knowledge base — NOT about writing inline code comments, README files, or API reference docs from docstrings.

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 health check of all your skills in one report. Use when the user wants to check for errors, find duplicates, detect broken skills, or get a complete overview of skill health. Pass --brief for inventory only. Trigger with '/janitor-report'.

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。

Write blogs, newsletters, Twitter threads, case studies, and marketing copy that convert. Covers copywriting frameworks (AIDA, PAS, BAB, FAB), headline formulas, SEO/GEO for 2026 (AI Overviews, SGE), newsletter deliverability, Twitter thread hooks, Cialdini psychology, and cognitive biases.

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。

SEO + Generative Engine Optimization (GEO) for 2026 — technical SEO, on-page optimization, structured data (JSON-LD, schema.org), Core Web Vitals, citability scoring (llms.txt, entity clarity), AI search engine optimization (ChatGPT, Gemini, Perplexity, Claude, Google AI Overviews), and brand authority building. Use when user asks to optimize a site for search engines, improve SEO, write SEO content, implement structured data, optimize for AI search/GEO, audit a page, or improve Google rankings. Do NOT use for content writing strategy (use content-marketing), performance optimization beyond Core Web Vitals (use performance-profiler), or paid ad strategy.

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 content for AI-generated responses and LLM citations (ChatGPT, Perplexity, Google AI Overview, Claude, Gemini). Use when the user mentions 'GEO', 'AEO', 'AI SEO', 'LLM optimization', 'citation rate', 'AI visibility', 'optimize for ChatGPT', 'roundup pages', or wants to audit pages for AI discoverability. Includes terminology alignment, FAQ schemas, and community signal strategies.

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。

SEO, AEO (Answer Engine Optimization), and GEO strategy for search engines and AI visibility. Use when working on "SEO audit," "technical SEO," "on-page SEO," "AI search optimization," "AEO," "GEO," "AI visibility," "optimize for ChatGPT," "optimize for Perplexity," "AI Overviews," "answer engine optimization," "generative engine optimization," "AI citations," "featured snippets," "meta tags," "schema markup," "search ranking," "content optimization," "E-E-A-T," "structured data," "search console," "SEO health check," "why am I not ranking," "AI search readiness," "backlink strategy," "link building," "domain authority," "programmatic SEO," "SEO at scale," "template-based SEO," "AEO monitoring," "AI search monitoring," "JSON-LD," "rich snippets," "schema.org," "SERP analysis," "search intent," "site architecture," "information architecture," "URL structure," "internal linking," or "navigation." For keyword research, see keyword-research-and-clustering.

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 improve the discoverability of the timepicker-ui documentation site (docs-app/) across the full modern discoverability stack — SEO (ranking), AEO (answer engines / featured snippets), GEO (citations inside ChatGPT/Gemini/Perplexity/Claude), and AIO (Google AI Overviews). Use when the user wants to optimize docs SEO, improve Google ranking/positioning, win featured snippets or AI-answer boxes, get the docs cited by AI engines, add or fix sitemap/robots/manifest, fill in page metadata, add Open Graph/Twitter cards, answer-first copy, or JSON-LD (FAQPage/SoftwareApplication/TechArticle/BreadcrumbList). Drives the seo-optimizer subagent with an audit → approve → apply flow.

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 optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' or 'optimize for Claude/Gemini.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.

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 and optimizes websites for search engine visibility (SEO) and AI search citation (GEO), covering technical health, E-E-A-T content scoring, domain authority, structured data, rich results, and entity signals. Use when running SEO audits, diagnosing traffic drops or ranking losses, generating Schema.org JSON-LD, checking Core Web Vitals, crawlability, robots.txt, sitemaps, hreflang, backlinks, planning content strategy or site migrations, fixing indexing issues, or optimizing for AI Overviews, ChatGPT, and Perplexity. NOT for paid ads (PPC/SEM), social media strategy, email marketing, or general web development unrelated to search.

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Builds a talk as a beatdeck - a fixed 1920x1080 React stage where one click is one beat, with authored motion, presenter view, overview, and an offline self-contained build. Covers turning source material (PPTX, Keynote/PDF export, Markdown, notes) into a content audit and a scene/beat map, choosing or applying a theme, writing scene layers, automatic beats, and verifying every beat with npm run verify. Use whenever the task is creating, porting, restyling, rehearsing or fixing a presentation, talk, keynote, slide deck or conference session that should feel like a live system rather than slides, or whenever the repo contains src/beatdeck/.

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。

保险市场概览工具。获取中国保险行业整体数据，包括保费收入、赔付支出、行业资产规模、增速等。使用金融监管总局数据、AkShare保险行业数据。适用于保险行业研究、市场趋势分析。

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。

This skill should be used when the user asks for an "insurance briefing", "sigorta brifing", "insurance digest", "sigorta haberleri", "insurance news summary", or wants to understand the editorial philosophy behind the insurance briefing system. Also triggers when the user mentions "insurance briefing plugin" or wants a curated daily overview of the Turkish insurance sector.

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。

Guide creation of new industry use cases for the Adobe Experience Platform blueprints repository. Use this skill when adding a new use case to an industry vertical (retail, automotive, healthcare, financial services, insurance, media & entertainment, telecommunications, travel & hospitality, B2B), when the user wants to add business scenarios to industry pages, or when updating the use case catalog. Handles the full workflow: gathering use case details, assessing maturity level, generating content, updating the industry overview page and use case catalog, and invoking the use-case-icon-generator skill for icon creation.

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。

Guide a researcher step by step into an unfamiliar research field, or decode a paper, abstract, figure caption, or referee comment they cannot parse. Builds understanding in rungs (motivation, vocabulary, core framework, methods, frontier), anchored to what the user already knows, with a checkpoint before each advance. Use when the user says they are new to a field, asks what a research area or method is, says an explanation was too technical, asks to be walked through something step by step, asks for a reading path, or supplies dense research text. Trigger even when the user only names an unfamiliar field or pastes an abstract without asking to be taught. Do not trigger for a one-line summary, a short overview request, or a direct factual answer; do not use it for translation, editing, search, debugging, or specialist questions inside the user's own field. Also trigger in other languages, including Chinese such as 入门, 一步一步讲, 看不懂, 这篇论文讲什么, 帮我理解这个领域.

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Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions. Use when asked to "map the architecture", "system diagram", "how does this work", or "architecture overview".

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。

Generates publication-quality academic figures (framework diagrams, pipeline illustrations, system architectures, method overviews) from a paper's method text and a target caption, using a local PaperBanana multi-agent pipeline (Retriever → Planner → Stylist → Visualizer → Critic).

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。

Performs initial binary triage by surveying memory layout, strings, imports/exports, and functions to quickly understand what a binary does and identify suspicious behavior. Use when first examining a binary, when user asks to triage/survey/analyze a program, or wants an overview before deeper reverse engineering.

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 files or a requested directory scope from actual contents. Extract code, config, data and document evidence, preserve exact counts and source locations, and disclose incomplete or unsupported acquisition. Use for file summaries, code explanations and configuration overviews.

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。

Claude Code runtime skills router. Use when configuring SKILL.md frontmatter, discovery, invocation, hooks, context forks, substitutions, loading behavior, or headless skill dispatch.

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。

Semantic code understanding with IDE-like symbol operations. Use when: (1) Large codebase analysis (>50 files), (2) Symbol-level operations (find, rename, refactor), (3) Cross-file reference tracking, (4) Project memory and session persistence, (5) Multi-language semantic navigation. Triggers: "find symbol", "rename function", "find references", "symbol overview", "project memory". IMPORTANT: Prioritize Serena's symbolic tools over file-based grep/read for code exploration.

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。

Market intelligence: strategy screener, popularity rankings, top movers with news correlation, quote anomalies, index/ETF constituent stocks, morning briefings, catalyst monitoring for watchlist, event-driven strategies, ETF fund flows, sector rotation, market microstructure, supply chain analysis, industry overviews, and ARK-style disruptive innovation analysis. Triggers: "筛选", "策略筛选", "排行", "热度", "异动", "成分股", "晨报", "早报", "催化剂", "事件驱动", "ETF资金流", "板块轮动", "产业链", "行业概览", "颠覆式创新", "ARK", "篩選", "排行", "異動", "成分股", "晨報", "ETF資金流", "板塊輪動", "產業鏈", "screener", "rank", "anomaly", "constituent", "morning brief", "catalyst", "event strategy", "ETF flow", "ETF资金流", "ETF申赎", "ETF資金流", "etf flow", "资金申赎", "etf 资金", "sector rotation", "supply chain", "ARK", "disruptive innovation", "板块筛选", "行业筛选", "板塊篩選", "強勢板塊", "弱勢板塊", "top sectors", "催化劑", "事件驅動", "行業概覽", "顛覆式創新", "策略篩選", "熱度"

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。

Analyze the codebase to create a concise, LLM-optimized structured overview in .agent/map.md.

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。

Transform implementation plans into concise stakeholder-friendly summaries with file change overviews, component listings, and optional flow diagrams.

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。