5,063 件 ・ 関連度順
概要と使いどころ
When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' or 'product update.' This skill covers phased launches, channel strategy, and ongoing launch momentum.
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, improve, or increase conversions on any marketing page — including homepage, landing pages, pricing pages, feature pages, or blog posts. Also use when the user says "CRO," "conversion rate optimization," "this page isn't converting," "improve conversions," or "why isn't this page working." For signup/registration flows, see signup-flow-cro. For post-signup activation, see onboarding-cro. For forms outside of signup, see form-cro. For popups/modals, see popup-cro.
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 competing products and turn the market gap into credible positioning, messaging angles, and social campaign claims. Use when comparing competitors, writing alternative pages, sharpening product positioning, or planning campaigns against a category narrative.
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。
Codified expertise for managing carrier portfolios, negotiating freight rates, tracking carrier performance, allocating freight, and maintaining strategic carrier relationships. Informed by transportation managers with 15+ years experience. Includes scorecarding frameworks, RFP processes, market intelligence, and compliance vetting. Use when managing carriers, negotiating rates, evaluating carrier performance, or building freight 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。
Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis, hedging strategies, load profiling, and sustainability reporting frameworks. Use when procuring energy, optimizing tariffs, managing demand charges, evaluating PPAs, or developing energy 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。
Write and optimize prompts for AI-generated outcomes across text and image models. Use when crafting prompts for LLMs (Claude, GPT, Gemini), image generators (Midjourney, DALL-E, Stable Diffusion, Imagen, Flux), or video generators (Veo, Runway). Covers prompt structure, style keywords, negative prompts, chain-of-thought, few-shot examples, iterative refinement, and domain-specific patterns for marketing, code, and creative writing.
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。
Branch skill for building and improving agents. Use when creating new agents, adapting marketplace agents, validating agent structure, writing system prompts, or improving existing agents. Triggers: 'create agent', 'improve agent', 'validate agent', 'fix agent', 'agent frontmatter', 'system prompt', 'adapt agent', 'customize agent', 'agent examples', 'agent tools'.
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。
Expert competitive analyst specializing in competitor intelligence, strategic analysis, and market positioning. Masters competitive benchmarking, SWOT analysis, and strategic recommendations with focus on creating sustainable competitive advantages.
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。
Options chains, option quotes, option volume, Greeks (Delta/Gamma/Theta/Vega), implied volatility, and HK warrants (callable bull/bear, call/put warrants, issuer list) for HK/US markets via Longbridge. Triggers: "期权", "期权链", "认购", "认沽", "行权价", "到期日", "IV", "隐含波动率", "Greeks", "delta", "gamma", "窝轮", "牛熊证", "认购证", "认沽证", "認購", "認沽", "行權價", "隱含波動率", "窩輪", "牛熊證", "option", "option chain", "call", "put", "strike", "expiry", "implied volatility", "warrant", "CBBC", "期權", "期權鏈"
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。
Financial statements, business segments, dividends, valuation multiples (PE/PB/PS), industry comparison, operating data, corporate actions, company and executive profiles, cross-stock comparison, and valuation ranking via Longbridge. Also: DCF models, value investing screens (low PE/PB, margin of safety), and behavioral finance analysis frameworks. Triggers: "财报", "三表", "利润表", "资产负债", "现金流", "估值", "PE", "PB", "分红", "公司信息", "高管", "行业估值", "并购", "DCF", "内在价值", "低估值", "安全边际", "行为金融", "小盘成长", "专精特新", "主营业务", "业务构成", "收入结构", "业务分析", "是做什么的", "是干嘛的", "公司画像", "行业排名", "行业龙头", "市场份额", "收入占比", "业务结构", "財報", "估值", "分紅", "內在價值", "安全邊際", "主營業務", "業務構成", "收入結構", "行業排名", "行業龍頭", "financial report", "income statement", "balance sheet", "valuation", "dividend", "company info", "industry valuation", "DCF", "value screen", "behavioral finance", "main business", "business composition", "revenue structure", "what does XX do", "industry ranking", "market share", "利潤表", "資產負債", "現金流", "行業估值", "併購", "行為金融", "小盤成長"
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。
Works out a company's go-to-market motion (product-led, sales-led or hybrid) from its website and pricing, then maps the funnel stage by stage: a definition, strategy, leading inputs the team controls, lagging outputs with targets, cadence and owner for each stage, MQL, SQL and PQL criteria, post-sale stages, closed-lost re-entry paths and backward funnel maths from a revenue target. Triggers: "funnel strategy", "funnel stages", "pipeline stages", "PLG vs SLG", "lead qualification criteria", "map our sales process", "how do leads flow". Feeds /goals. Not for setting the target itself (use /goals).
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。
Draws out a founder's or expert's point of view: what they believe about their market that others don't, the hot takes they'd defend, the stories behind them, and their taste. Generates interview questions, works from answers, a live call or existing content, and ends with ranked One Big Idea candidates for thought leadership and positioning. Triggers: "expert POV", "founder POV", "one big idea", "OBI", "contrarian beliefs", "what makes our founder different", "thought leadership foundation", "founder interview questions". Feeds /positioning and /tov-guidelines. Not for writing posts or articles, and not for brand voice rules (use /tov-guidelines).
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。
Researches a company from its website and public sources and writes a company profile: what it sells, who buys it, traction, funding, team, hiring, tech stack, key people, red flags and the gaps you still need to fill, every claim tagged with a source and a confidence level. Use it as the first file in a marketing context folder, or to prep a discovery call or qualify a prospect. Triggers: "company research", "company background", "company context for", "qualify this prospect", "discovery call prep", "account brief", or a company URL handed over for research. Not for competitor analysis (use /competitor-research) or customer profiles (use /icp-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。
Builds an ideal customer profile from evidence: case studies, testimonials, customer logos, solutions pages, reviews and any sales notes you have. Produces market sizing layers, firmographic segments, a champion and an economic buyer persona, a negative ICP, intent signals, customer proof points and a voice-of-customer section in the buyers' own words, every claim sourced. Triggers: "ICP research", "ideal customer profile", "who are our customers", "customer segments", "buyer personas", "who should we target". Run after /company-context. Not for competitor analysis (use /competitor-research) or call transcript patterns (use /win-loss).
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。
Researches one B2B SaaS competitor across 13 dimensions (company, product, ICP, pricing, reviews, content, launches, search and AI visibility, tech stack, hiring, go-to-market, social, paid ads) and writes a sourced dossier with an executive summary, a threat level, strengths and weaknesses, and a data gaps section. Run it once per competitor, then compare. Triggers: "competitor analysis", "competitor research on", "what is [competitor] doing", "compare us to", "competitive landscape", "battlecard prep". Run after /company-context and /icp-research. Not for researching your own company (use /company-context).
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。
Score your Claude Code environment on a fun 0-10 ladder (Tourist → Swarm) calibrated to the quickstart's 4 systems — Context, Skills, Integrations, Orchestration. Two front doors - an interactive quiz (zero setup, shareable) or a silent scan of your repo. Outputs a next-level roadmap plus a branded HTML dashboard or a paste-anywhere ASCII card. The default mastery skill of this quickstart. Triggers - "level", "what's my claude code level", "claude code level quiz", "assess my setup", "how good is my setup", "claude code maturity"
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 and query a local Markdown knowledge base ("vault"). TWO functions — (1) CONVERT raw files (PDF, Word/docx, PowerPoint/pptx, Excel/xlsx, csv/tsv, images, html, md/txt, json/yaml/code, audio/video) into clean Markdown with retrieval-friendly frontmatter; local-first (pandoc / python-pptx / openpyxl / pymupdf4llm / whisper), with cloud OCR (MinerU) only as a fallback. (2) ANSWER questions over the resulting vault with retrieval discipline — self-monitor coverage, flag missing/lossy content, and propose Maps-of-Content (MOCs). Triggers: "build/sync my local knowledge base", "convert these files to markdown for AI", "整理我的资料库", "把文件转成 md 给 AI 读", "本地知识库", "读我的本地 vault 回答", "这个主题我的资料里怎么说". Not for: one-off web research, or files that are already in a single doc you can read directly.
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 research workflow skill for investment analysts and policy researchers. Three scope modes the user picks at trigger time — light (4-5 page decision memo, ~15 min, 0 charts), medium (12-15 page topic brief, ~1 h, 6-10 charts), heavy (flagship report 30-40 pages / 15k+ words, ~2-3 h, 25-35+ charts, multi-stage workflow, multi-LLM, PDF + Word + WeChat + HTML derivations). Reports default to English; the AI replies in the user's chat language. Battle-tested on real macro/policy/equity reports (e.g. Saudi Vision 2030 deep-dive). Triggers when user types /analyst-research, /flagship-research, or describes needs like "research report", "topic analysis", "investment research", "做研报", "投研报告", "主题分析", "深度分析", "policy assessment", "industry deep-dive". Not for: pure news commentary (use topic-brief), slide decks (use deckster-slide-generator), one-shot Q&A.
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 information (fact, number, quote, event, statement) against authoritative primary sources, or cross-checking a number via one-level metric decomposition (Z = P × Q). Triggers: "verify X", "is this true", "find the original source", "where is this number from", "two sources disagree", "is it true X never did Y". Covers five scenarios: (1) basic truthfulness check, (2) completeness / out-of-context quoting, (3) one-level reasoning verification, (4) negative-statement handling, (5) multi-source conflict side-by-side output. Dig into whitelisted primary sources only (user-supplied files, official websites & databases, authoritative industry sources); cited reports / charts / datasets must be downloaded and read locally to count as verified — if download is blocked, hand the link to the user. If nothing can be found, plainly state "cannot verify" rather than guessing, patching, or citing secondary paraphrases. Always reply in the user's question language.
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 a topic-focused briefing in HTML from public news sources. Use when user asks for a briefing / observation / digest / 简报 / 观察 on any subject — region (Middle East, ASEAN, India), industry (semiconductors, EV supply chain, AI), policy issue (AI regulation, critical minerals, cross-border payments), institution (Fed, ECB, IMF), or theme. Output is a single self-contained HTML file with blue-color "TOPIC BRIEF" branding, optimized for both browser viewing and direct copy-paste into 微信公众号 / WeChat Official Account editor. Walks through 5 steps with one user confirmation midway. Do NOT use this skill for short summaries (<1000 字), single-piece news commentary, or already-defined report templates.
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-coverage formatted Excel report generation with Dutch market compatibility
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。
Multi-provider deliberation panel for COMPLEX, multi-view questions — architecture, strategy, market research, and codebase sweeps. Runs a 4-stage deliberation across the provider fleet (diverge → contrarian red-team → adversarial verify → cited synthesis), the same multi-perspective rigour the plan-gate already applies to plan reviews, generalised to arbitrary questions. Use when one model's answer isn't enough and you want convergence THROUGH disagreement + verification, not a single opinion.
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 whenever the user wants to find, shortlist, vet, enrich, or research US professional-services firms — law, marketing, consulting, accounting, IT services, architecture, engineering, HR, PR, design, and similar B2B service providers. Triggers on requests like "find me a PPC agency in California", "shortlist three boutique IP law firms", "build a longlist of 50 mid-size IT consultancies", or "here are 12 agency domains — pull contact info and confirm which are US-based", even when the need is described indirectly without naming a category. Drives the ServiceGraph API (api.servicegraph.co) — a 100k+ US firm catalog with filters for industry, services, location, size, ratings, and third-party listings. Skip when the user is asking for personal/consumer services for themselves (an individual's own legal, tax, or medical needs), non-US firms, individual freelancers, retail/ecommerce/SaaS-product companies, recruiting-an-employee tasks, or general web research that doesn't need a structured firm directory.
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。
The branded entry point to ServiceGraph — use whenever the user explicitly names **ServiceGraph** — "use ServiceGraph to…", "what datasets does ServiceGraph have", "search ServiceGraph for…", "look this up in ServiceGraph", "pull contacts from ServiceGraph for these domains", "how many credits do I have on ServiceGraph". ServiceGraph is a multi-dataset platform of metrics-enriched business data for founders — where to launch, who to email, who to hire. This skill explains how to drive the API (api.servicegraph.co / mcp.servicegraph.co) against ANY dataset — discover what datasets exist, discover a dataset's schema and filters, search free brief rows, and unlock contact + metric detail with credits. Dataset-agnostic by design — it discovers everything through the API and never assumes which datasets or fields exist. When the user describes an intent WITHOUT naming ServiceGraph (e.g. "find a PR agency in NY"), defer to the matching specific skill (find-pr-agency, find-marketing-agency, find-law-firm, …); this skill is for explicit ServiceGraph requests and for datasets no specific skill covers yet. Skip non-US firms, consumer/personal services, and individual freelancers.
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。