調査、論文、教育、資格学習（4,178 件）
概要と使いどころ
Investigate a question against high-trust primary sources and capture the findings as a Markdown file in the repo. Use when the user wants a topic researched, docs or API facts gathered, or reading legwork delegated to a background agent.
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。
Learn the target framework from enabled knowledge tools and implement a baseline GPU kernel. Use this skill to understand compute semantics, determine the target platform and framework, search reference implementations, and produce a correct V0 baseline with performance records for later profile-driven optimization.
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 the evidence loop of one long-horizon GPU kernel optimization episode. Use this skill to reconstruct the incumbent, profile and localize a bottleneck, research progressively, plan one coherent direction, implement and repair, validate development correctness and performance, and record every decisive experiment in the episode journal.
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。
Conducts deep technical research for Aha Loop stories. Use before implementing stories involving unfamiliar libraries or architectural decisions. Triggers on: research this, investigate, explore options, compare alternatives.
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。
台灣正式文件撰寫助手 — 涵蓋政府公文、政府機關其他文件、法律文件、人民對政府文書四類中文正式文件的撰寫（不含學術論文、商業文書、私人書信等，見下方排除清單）。 根據使用者意圖自動判斷文件類別，載入對應的撰寫規範與格式指引。 觸發此 skill 的情境： - 政府公文：簽、函、書函、公告、令、呈、咨、箋函、便簽、行文、發文、簽辦、擬稿、陳核、簽稿併陳、以稿代簽、先簽後稿、上行文、下行文、平行文 - 政府機關其他文件：會議紀錄、開會通知單、新聞稿、聲明稿、施政報告、出國報告、施政計畫書、業務計畫書、裁處書、訴願決定書、聘函、獎狀、證書 - 法律文件：存證信函、律師函、合約書、備忘錄(MOU)、保密協議(NDA)、聲明書、切結書、委託書、授權書 - 人民對政府文書：陳情書、申請書、訴願書、異議書、申覆書 - 描述需要撰寫正式文件的情境（如「幫我寫一封給教育部的公文」「我要寄存證信函」「幫我寫陳情書」） - 詢問任何正式文件的格式或用語規範 - 公務員考試或受訓的公文練習題 - 公文案件後續：催辦、展期、補正、否准、陳述意見通知、陳情答復、原函更正、會辦、會勘、會議異動、公務電話紀錄 不應觸發的情境： - 商業 email、求職信、履歷 - 學術論文、研究計畫書 - 商業計畫書、簡報 - 私人書信、感謝卡 - 翻譯任務 - 純粹的文章潤飾或改寫
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 customer case studies as marketing and chasm-crossing reference assets during PRD v1.0 Market Adoption. Triggers on requests to build case studies, produce customer stories, create reference content, or when user asks "build a case study", "customer story", "reference account", "case study interview", "before/after story", "social proof page", "logo wall". Outputs CFD-CASE-* evidence entries, GTM-CASE-* marketing assets, and updates ADO-REF-* with story status.
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 competitive landscape before positioning your product for PRD v0.2 Market Definition. Triggers on completing v0.1 Spark, analyzing competitors, researching market, or requests like "competitive analysis", "who else solves this", "market landscape", "what alternatives exist", "competitor research", "feature comparison". Outputs CFD- entries for competitive intelligence and BR- entries for positioning rules.
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。
Establish channels and processes for capturing and processing post-launch feedback during PRD v0.9 Go-to-Market. Triggers on requests to set up feedback systems, capture user input, or when user asks "how do we collect feedback?", "feedback loop", "user research", "post-launch feedback", "customer feedback", "NPS", "voice of customer". Outputs CFD- entries specialized for post-launch feedback capture.
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 Tier 1/2/3 cold outreach sequences differentiated by personalization depth and research signal strength during PRD v0.9 Go-to-Market. Triggers on requests to plan cold outreach, founder-led sales, or when user asks "cold email sequence", "outbound campaign", "founder outreach", "LinkedIn outreach", "Tier 1 personalization", "predictable revenue", "sales cadence", "BDR sequence". Outputs GTM-OUT-* sequence entries and lead-list references.
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 about "technical decision", "what to use", "A vs B", "comparison analysis", "library selection", "architecture decision", "which one to use", "tradeoffs", "tech selection", "implementation approach", or needs deep analysis for technical decisions. Provides systematic multi-source research and synthesized recommendations.
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。
Deep web research skill using parallel subagents + chromux browser-explorer + Gemini. Spawns multiple WebSearch research agents AND browser-explorer agents (via chromux for JS-heavy/dynamic sites), plus a Gemini CLI deep research source, then synthesizes everything into a cited report. Uses WebSearch, WebFetch, chromux browser-explorer, and Gemini CLI. Invoke with /deep-research <topic>.
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 says "/compound", "compound this", "document learnings", "save what we learned", or after completing a PR. Extracts knowledge from PR context and saves to docs/learnings/.
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。
Hoyeon deep research workflow for Codex. Use when the user invokes "$hoyeon-deep-research" or wants a multi-channel cited research report using web search, browser extraction, and optional Gemini. This adapter loads the canonical deep-research skill and follows its Codex runtime surface.
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。
Independently review a CUMCM computation package before its claims enter validation or paper writing. Use only inside a generated independent-review package.
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 has positioning and wants a reusable Xiaohongshu topic/title bank instead of asking AI to freely brainstorm, especially to map topics to user needs such as emotional resonance, growth proof, new insight, learning value, or identity expression. Trigger phrases: "选题库", "标题公式", "每天发什么", "批量选题", "爆款需求", "XHS topic bank", "title formulas". Do not use before account positioning and target audience are known.
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 structured research briefs from RSS feeds and web sources on any topic. Synthesizes multiple sources into actionable analysis with key findings, data points, expert perspectives, and content angles.
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 detailed ideal customer profiles with pain points, objections, buying triggers, and messaging angles. Includes community research to find where ICPs gather online and extract their exact language. Use when researching audiences, creating buyer personas, or developing targeted messaging.
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 content creation workflow that orchestrates research, editorial review, and social distribution agents in sequence. Use when the user wants to create, review, and distribute content through a multi-stage pipeline, or says "/content-pipeline".
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 comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Professional LaTeX formatting, strategic analysis frameworks (Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, BCG Matrix), and deep research integration.
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 has positioning and wants a reusable Xiaohongshu topic/title bank instead of asking AI to freely brainstorm, especially to map topics to user needs such as emotional resonance, growth proof, new insight, learning value, or identity expression. Trigger phrases: "选题库", "标题公式", "每天发什么", "批量选题", "爆款需求", "XHS topic bank", "title formulas". Do not use before account positioning and target audience are known.
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。
当用户需要把内容（文章、笔记、截图、数据、产品说明）做成中文图文卡片组图时使用——小红书 / Rednote 3:4 竖图、公众号封面、社交卡。提供三套独家视觉语言（静纸 Still Paper本手记 / Signal Proof 证据层 / Bridge Canvas 跨平台桥），由 Claude 读懂内容、自己撰写 brief.json，交给确定性引擎渲染出第一眼惊艳、一眼可辨、国内开箱即用的图文组图。
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 in designing engaging learning experiences - completion optimization, multimedia learning, interactivity, gamification, and retention strategies. Covers the science of how people learn and practical techniques to make courses that students actually finish. Use when "learning experience, course engagement, completion rate, make learning fun, gamification, interactive course, learning design, " mentioned.
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。
Production incident response - from detection through resolution to post-mortem. Effective communication, systematic investigation, and blameless learning from failuresUse when "incident, outage, production issue, site down, on-call, post-mortem, war room, severity, pages, alerts, rollback, incident, outage, on-call, post-mortem, production, reliability, SRE, communication" mentioned.
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 in running effective incident postmortems. Covers blameless analysis, root cause investigation, action item prioritization, and building a learning culture. Understands that incidents are opportunities to improve systems, not punish people. Use when "postmortem, incident review, what went wrong, root cause, blameless, outage, post-incident, " mentioned.
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。