225 件 ・ 関連度順
概要と使いどころ
Produce a decision-ready brief of current brand, product, category, and competitor conversations across social platforms, including sentiment drivers, questions, risks, and growth opportunities.
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Find warm leads by searching LinkedIn for pain-language posts — the frustrations, complaints, and operational struggles your ICP talks about publicly. Asks clarifying questions to understand your product, ICP, and their pain points, then generates pain-language search keywords, scrapes LinkedIn for posts and engagers, enriches profiles, and ICP-filters the results. Use when someone wants to "find leads who are complaining about X" or "find people discussing problems we solve" or "LinkedIn pain-based prospecting."
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Analyze data using MATLAB. Use when the task involves tables, timetables, time-series data, numeric arrays, sensor matrices, or gridded data — including but not limited to exploring, row filtering, sorting, cleaning, transforming, aggregating, smoothing, padding, trimming, and answering questions about data. MATLAB provides extensive, easy-to-use built-in functions for these workflows with no additional products required.
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Review a business plan or product strategy through the eyes of a smart-money seed/Series-A investor. Asks the brutal questions: Is this fundable? What's the moat? What's the exit story? Outputs a verdict with one of four modes — SEED VIABLE / LATER ROUND ONLY / BOOTSTRAP-ONLY / UNFUNDABLE. Use when the user has a business plan and wants to know if it would survive an investor pitch. Triggered by: 'investor review', 'is this fundable', 'VC perspective', '投资人视角'.
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Design and run a documentation system for a team or product. Use this skill when planning what to document, choosing a documentation tool, organizing existing docs, fixing stale documentation, designing a maintenance cadence, or scoping technical writing work. Triggers on documentation, docs, tech writing, knowledge base, wiki, runbook, README, internal docs, doc audit, doc maintenance, stale docs, where do we document. Also triggers when the team is repeatedly answering the same questions or when onboarding takes too long.
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。
YC Office Hours — product idea diagnostic before writing code. Two modes: Startup (6 forcing questions with rigorous pushback) and Builder (generative brainstorming). Outputs design doc. Includes landscape research, premise challenge, alternatives generation, visual wireframe sketching, and optional cross-model second 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。
Applied statistics for business and product questions — test selection, assumption checks, power planning, effect sizes with intervals, multiplicity correction. Use when interpreting an experiment, sizing a study, or vetting a claim.
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。
World-class prompt powerhouse that generates production-ready mega-prompts for any role, industry, and task through intelligent 7-question flow, 69 comprehensive presets across 15 professional domains (technical, business, creative, legal, finance, HR, design, customer, executive, manufacturing, R&D, regulatory, specialized-technical, research, creative-media), multiple output formats (XML/Claude/ChatGPT/Gemini), quality validation gates, and contextual best practices from OpenAI/Anthropic/Google. Supports both core and advanced modes with testing scenarios and prompt variations.
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。
产出给人读的 HTML 长文——把已有的素材、经历、资料想清楚再写出来。每次触发先用 AskUserQuestion 一次性问清「给谁看 / 读完拿什么 / 多长 / 风格 + 侧重」4 个关键参数，再按 6 阶段框架输出。**产出只有 HTML 一种格式**——用户要 markdown 或要在聊天里直接说，就不该用本 skill。当用户说"做个复盘""汇总一下""总结这堆""整理成 HTML""做个教程/学习指南""把 X 讲清楚"等需要超过 500 字的结构化阅读内容时触发。不适用于：项目的计划报告/框架计划/版本路线（用 issue-pool，它自带 md2html）、PRD/需求文档/测试用例（用 prd-test-writer）、整页界面方案（用 page-solution-design）、起名（用 product-naming）、写代码/修 bug/改文件、一两句话就能答完的问题。
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。
Applies Neil Rackham's SPIN methodology (Situation/Problem/Implication/Need-payoff questions) to major B2B sales. Use for complex multi-call sales cycles, enterprise deals where the customer must justify the decision to others, when objections are mounting, when calls end in vague continuations instead of advances, when traditional closing techniques are backfiring on large deals, or when designing discovery-call structure. Triggers include 'my deal isn't closing', 'too many objections', 'B2B sales coaching', 'discovery call structure', 'stuck in the middle of the sale'. Not for transactional sub-$50 sales, pure consumer impulse, or PLG self-serve 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。
JTBD discovery techniques adapted for AI product owner context. Four Forces extraction, job dimension probing, question banks, and anti-patterns for interactive feature discovery conversations.
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Dung khi agency hoac freelancer nhan khach moi va can CHINH KHACH DIEN thong tin dau vao — form 11 phan ve san pham, muc tieu, ngan sach, kenh dang chay, doi thu, tai san san co, kem 20 ban toi uu theo tung nganh. Kich hoat khi user nhac 'brief khach hang', 'client intake', 'form khach dien', 'nhan khach moi', 'hoi khach nhung gi', 'chua biet gi ve khach', 'onboard khach hang moi', 'questionnaire cho khach'. Khong dung cho — tao file context noi bo cho san pham cua chinh minh thi dung skill product-marketing-context; dao sau insight khach hang cuoi thi dung skill 09-insight-khach-hang; brief NGUOC ra cho agency hoac vendor lam thi dung skill 67-agency-vendor-brief.
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 the user needs to understand customers deeply enough to write copy and pick targeting — consumer versus shopper, JTBD, layered persona, internal monologue, pain map, objection list, journey map, and a customer language bank pulled from real reviews and DMs. Trigger on 'customer insight', 'buyer persona', 'who is my customer', 'what do they actually want', 'jobs to be done', 'why do they hesitate before buying'. Also use when the user cannot explain who the product is for. Not for — intake questions when an agency signs a new client, see `20-client-intake-brief-global`; paid audience targeting setup, see `51-audience-research-global`; competitor study, see `08-competitor-research-global`.
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 an agency or freelancer takes on a NEW client and needs everything up front — an 11-section intake covering business overview, audience, current marketing, goals, budget, timeline, brand assets, approval process, and success criteria, written for the client to fill in and return. Trigger on 'client intake', 'agency brief', 'onboard a new client', 'discovery call template', 'what should I ask a new client', 'kickoff questionnaire'. Also use when the user just signed someone and does not know where to begin. Not for — the internal context file the skills read, see `product-marketing-context-global`; the plan built from the answers, see `00-marketing-plan-global`; briefing an outside vendor, see `67-agency-vendor-brief-global`.
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。
One-prompt autonomous product design and implementation. Use automatically for broad greenfield UI requests such as 'from scratch', '새 제품/화면을 알아서 만들어줘', or requests that delegate DESIGN.md creation. It decides whether to reuse, establish, refresh, or skip a project design system; asks at most one consequential question batch; then builds and verifies the real surface. Use omd:harness instead only when the user explicitly asks for guided checkpoints.
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。
One-prompt autonomous product design and implementation. Use automatically for broad greenfield UI requests such as 'from scratch', '새 제품/화면을 알아서 만들어줘', or requests that delegate DESIGN.md creation. It decides whether to reuse, establish, refresh, or skip a project design system; asks at most one consequential question batch; then builds and verifies the real surface. Use omd:harness instead only when the user explicitly asks for guided checkpoints.
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。
Activate this skill when BenchmarkDotNet (BDN) is involved in the task — creating, running, configuring, or reviewing BDN benchmarks. Also activate when microbenchmarking .NET code would be useful and BenchmarkDotNet is the likely tool. Consider activating when answering a .NET performance question requires measurement and BenchmarkDotNet may be needed. Covers microbenchmark design, BDN configuration and project setup, how to run BDN microbenchmarks efficiently and effectively, and using BDN for side-by-side performance comparisons. Do NOT use for profiling/tracing .NET code (dotnet-trace, PerfView), production telemetry, or load/stress testing (Crank, k6).
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 a role scorecard, interview loop, sourcing plan, reference-check guide and close plan for a hire, and grades an existing job description or loop. Use when you say 'I need to hire a PM', 'write a job description', 'interview questions', 'how do I run references', 'first sales hire', 'first marketer', 'head of product search', 'scorecard' or 'how do I close a candidate'. Draws on 210 Lenny's Podcast guests including Adam Ward, Keith Rabois and Lauren Ipsen.
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。
Turns a hard product or career decision into a one-page decision memo with the eigenquestion, options, pre-mortem with kill criteria, reversibility rating, a named decider and a review date. Use when you ask 'how should we decide', 'should we build or kill this', 'one-way door or two-way door', 'run a pre-mortem', 'we keep going in circles', 'quit or pivot', or want to grade a decision doc. Draws on 396 insights from 177 Lenny's Podcast guests, led by Annie Duke, Shreyas Doshi and Shishir Mehrotra.
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。
Align on the shape of a change through an interview, then implement it. Escalates open product decisions and settles the implementation shape in conversation. Use when the user asks to "discuss this change", "align on this change first", "ask me questions first", "interview me then implement", "agree on the approach before coding", or wants the shape of a single change settled before any code is written.
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。
Databricks CLI operations and the parent/entry-point skill for Databricks CLI use: authentication, profile selection, and bundles. Load this first for CLI, auth, profile, and bundle tasks, then load the matching product skill. For finding or exploring data, answering questions about the data, or generating SQL, load the databricks-data-discovery skill (it routes to Genie One). Contains up-to-date guidelines for Databricks-related CLI tasks.
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, audit, or implement application structured logging architecture from repository evidence. Use when a user asks whether or where to add logs, how to choose or migrate a logger, how to standardize events/fields/levels/redaction, how to add HTTP access or panic logs, or why production logs cannot answer an incident question. Do not use merely to tail platform logs or to design a full metrics, tracing, SLO, and incident-management program.
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。
Research-first content creation optimized for both human readers and AI search engines (Claude, ChatGPT, Perplexity, Gemini). Creates authentic, authoritative content that becomes the go-to citation source for AI models answering user questions. Use this skill when: - Creating content that should appear in AI search results (Perplexity, ChatGPT, Claude) - Building topical authority to become THE source AI cites for a topic - Launching a new product and need compelling, citable content - Creating blog posts, articles, social media, or press releases - Need content that references real trends, people, and recent events - Want AI-assisted content that doesn't sound AI-generated - Creating thought leadership content in any industry Triggers: "create content for", "write about", "research and write", "find experts for", "content for launch", "blog post about", "article on", "press release for", "AI search", "show up in AI", "Perplexity", "be cited by AI"
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 clear, searchable help center articles and FAQ entries based on support data, product documentation, and common customer questions. Use when the user requests knowledge base article writing or provides relevant inputs for 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。