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概要と使いどころ
SEO & GEO (Generative Engine Optimization) for websites. Analyze keywords, generate schema markup, optimize for AI search engines (ChatGPT, Perplexity, Gemini, Copilot, Claude) and traditional search (Google, Bing). Use when user wants to improve search visibility, search optimization, search ranking, AI visibility, ChatGPT ranking, Google AI Overview, indexing, JSON-LD, meta tags, or keyword research.
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 this skill any time a .docx file is involved -- as input, output, or both. This includes: creating Word documents, reports, letters, memos, or proposals; reading, parsing, or extracting text from any .docx file; editing, modifying, or updating existing documents; working with templates, tracked changes, comments, headers/footers, or tables of contents. Trigger whenever the user mentions 'Word doc', 'document', 'report', 'letter', 'memo', or references a .docx filename.
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。
Process filler word annotations to generate video edit lists. Use when working with timestamp annotations for removing speech disfluencies (um, uh, like, you know) from audio/video content.
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。
Transcribe audio/video to text with word-level timestamps using OpenAI Whisper. Use when you need speech-to-text with accurate timing information for each word.
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。
WooYun business logic vulnerability methodology — 22,132 real cases across 6 domains (authentication bypass, authorization bypass, payment tampering, information disclosure, logic flaws, misconfiguration) and 33 vulnerability classes. Use for ANY security testing, auditing, or code review of web apps, APIs, or business systems — even without explicit "security" keywords. Triggers: penetration testing, security audit, vulnerability, bug bounty, payment security, IDOR, password reset, weak credentials, unauthorized access, race condition, parameter tampering, code review, 渗透测试, 安全审计, 漏洞挖掘, 支付安全, 越权, 逻辑漏洞, 业务安全, SRC, 代码审计. Also triggers on implicit intent: "test this endpoint", "find bugs", "can I bypass this", "帮我测测这个接口", "这个参数能不能改", "帮我找bug".
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。
Run a Google Alerts-style keyword coverage tracker. Uses news-search for recent keyword queries, lets the LLM dedupe and classify real features versus junk, stores decisions in SQLite, and alerts only on new real coverage.
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。
Set up a lightweight Google Alerts-style coverage tracker for any number of keywords. Creates a tracker config with each keyword and what it actually means, then hands recurrence to the user's agent harness.
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。
Self-coaching analysis of your own behavior across meetings — talk-time ratio, filler words, hedging language, monologue length, energy patterns, and (when meetings are tagged via /minutes-tag) what your behavior in winning meetings looks like vs losing ones. Use this whenever the user says "how did I do", "review my last meeting", "mirror", "self-review", "show my patterns", "coach me", "where am I weak", "talk time", "am I improving", "what do I do in meetings I win", "feedback on me", or asks for any kind of personal feedback on their own meeting behavior. This is the rare skill that gives the user a mirror to their own habits — surface it whenever they show curiosity about their own performance, even if they don't use the word "mirror".
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 or update project cspell configuration by resolving the loaded config, active dictionaries, curated words, ignore paths, and validation evidence. Use when spell-check configuration needs project words or ignores.
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。
读取 Word/WPS 审阅后的 docx，把批注（comments）与修订（track changes）提取成可逐条裁决的 markdown 对账表或 JSON。触发场景：对方批注完的合同/协议/书稿/报告回来了要读意见；「提取 docx 批注」「审阅意见对账」「读一下修订」「谁批了什么、批在哪」；WPS 云文档/Word 在线协作 导出的审阅稿；收到带修订模式改动的回稿要看对方改了什么。核心保证：修订感知——python-docx 裸读会漏掉修订插入（w:ins）的内容、认不出整段删除（w:del），本 skill 走 OpenXML SDK 引擎 不漏。只读，不改对方文件。边界：生成/排版 docx → docx-creator 或 minimax-docx；PDF 批注不在范围。
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。
Converts DOCX/PDF/PPTX and saved HTML/HTM to high-quality Markdown with automatic post-processing. Fixes pandoc grid tables, simple tables, image paths, CJK bold spacing, attribute noise, and code blocks; for PDFs also strips OCR garbage blocks, repeated headers/footers/watermarks, and absolute image paths from pymupdf4llm output. Benchmarked best-in-class (7.6/10) against Docling, MarkItDown, Pandoc raw, and Mammoth. Trigger on "convert document", "docx to markdown", "parse word", "doc to markdown", "解析word", "转换文档", "HTML to Markdown".
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。
Converts Markdown to print-ready PDF with proper Chinese typography, themes and a visual self-check. Use for Markdown → PDF, including documents formatted for printing or mobile reading. Not for Word/WPS files or Word output (use docx-creator).
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 a UK Civil Service or NHS application: behaviour statements in the Success Profiles format, a personal statement mapped to the essential criteria, and a CV in the form these schemes expect. Use when asked to write my civil service application, answer Success Profiles behaviours, write a 250-word behaviour example, write my NHS supporting information, or apply on Civil Service Jobs or NHS Jobs. Produces each behaviour statement within the word limit using a situation, task, action, result structure, a criteria-mapped personal statement, and a check against the advert's essential criteria.
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。
Agent 2 of the video editing pipeline. Finds and removes spoken mistakes — stutters, repeated words, false starts, and retakes (re-recorded lines) — from a talking-head recording. Use after cut-silences, when asked to cut mistakes, remove stutters / repeats / filler restarts, clean up flubs, or keep the best take. Works review-gated: it proposes every cut with context and a reason for approval, then renders only the approved cuts via ffmpeg. Requires a word-level transcript.
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。
Help users build sustainable growth engines by transitioning from accidental word-of-mouth to structured referral programs and viral product loops.
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 this skill any time a .docx file is involved -- as input, output, or both. This includes: creating Word documents, reports, letters, memos, or proposals; reading, parsing, or extracting text from any .docx file; editing, modifying, or updating existing documents; working with templates, tracked changes, comments, headers/footers, or tables of contents. Trigger whenever the user mentions 'Word doc', 'document', 'report', 'letter', 'memo', or references a .docx filename.
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。
Reads existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.
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。
Live SEO data via DataForSEO MCP server. SERP analysis (Google, Bing, Yahoo, YouTube), keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis (Lighthouse, content parsing), competitor analysis, content analysis, business listings, AI visibility (ChatGPT scraper, LLM mention tracking), and domain analytics. Requires DataForSEO extension installed. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "competitor data", "AI visibility check", "LLM mentions", or "real search data".
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。
Codex-native multi-keyword Amazon opportunity scan using LaunchFast MCP. Use when the user wants to research 1-10 keywords, compare niches, or decide whether a product idea is a GO, INVESTIGATE, or PASS. Requires the LaunchFast MCP tool `research_products`.
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。
End-to-end Codex-native Amazon FBA research workflow using LaunchFast MCP. Use when the user wants a single report covering product research, IP risk, supplier sourcing, and PPC keyword intelligence. Requires `research_products`, `ip_check_manage`, `supplier_research`, and `amazon_keyword_research`.
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。
Codex-native batch Amazon keyword research using LaunchFast MCP. Use when the user wants a ranked comparison across many keywords and optionally wants HTML and CSV artifacts written to disk.
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。
Live SEO data via DataForSEO API credentials. SERP analysis (Google, Bing, Yahoo, YouTube, Google Images), keyword research (volume, difficulty, intent, trends), backlink profiles, on-page analysis (Lighthouse, content parsing), competitor analysis, content analysis, business listings, AI visibility (ChatGPT scraper, LLM mention tracking), and domain analytics. Uses DataForSEO credentials from the selected project `.env`; MCP tools are optional adapters when already available. Use when user says "dataforseo", "live SERP", "keyword volume", "backlink data", "competitor data", "AI visibility check", "LLM mentions", "image SERP", "google images", "image rankings", or "real search data".
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。
SERP-based semantic topic clustering for content architecture planning. Groups keywords by actual Google SERP overlap (not text similarity), designs hub-and-spoke content clusters with internal link matrices, and generates interactive visualizations. Optionally executes content creation if claude-blog is installed. Use when user says "topic cluster", "content cluster", "semantic clustering", "pillar page", "hub and spoke", "content architecture", "keyword grouping", or "cluster plan".
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 competitive SEO content briefs with per-section word counts, competitor scoring, keyword density guidance, and page-type templates. Supports both new page briefs and improve-existing-page briefs. Use when user says "content brief", "write a brief", "content outline", "blog brief", "service page brief", "brief for", "writing brief", "content plan", or "outline for".
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。