「art」の検索結果

World-class character and art style consistency for AI-generated images and videos - ensures visual coherence across series, maintains character identity, and provides rigorous QA before deliveryUse when "character consistency, art style, same character, consistent character, visual continuity, series, turnaround sheet, character sheet, reference image, character bible, style guide, anime character, consistent look, face consistency, outfit consistency, lora training, ip-adapter, flux kontext, visual qa, art quality, generation review, style drift, character drift, character-consistency, art-style, visual-qa, ai-art, image-generation, video-generation, anime, illustration, lora, ip-adapter, flux, midjourney, stable-diffusion" 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。

Figma 转 Photoshop (PSD) (Figma → Photoshop (PSD) 设计稿转换 (从业者视角) — 把 Figma 设计文件高保真转换为 Photoshop 分层 PSD, 核心是对齐两个工具的概念/渲染差异, 让产出的设计稿视觉一致. 覆盖: (a) 概念映射 — Figma frame / auto-layout / component / variant / constraint / vector-network / boolean / effect (drop·inner shadow / layer·background blur) / mask / blend mode / gradient / text-engine / color 与 Photoshop artboard / group / smart-object / linked / layer-style / shape-layer / path / clipping·layer mask / blend-mode 的对应关系与不可逆损耗点; (b) 转换方法栈 — 插件直出 PSD / 导出图层 (PNG·SVG) 再重组 / SVG·PDF 桥接 / 手工重建 / Figma REST API + Photoshop UXP·ExtendScript 脚本化, 各法在保真度-可编辑性-工时上的权衡与选型; (c) 保真度 QA — 字体回退与缺字处理 / 颜色空间 (sRGB·ICC profile) / 效果参数对齐 / @Nx·DPI 与栅格化 / 像素 diff 验收; (d) 两种交付目标 — 可编辑分层 PSD vs 像素保真扁平 PSD 的方法选择. 主战场 = Figma Community 插件 + Adobe 官方文档/论坛 + 设计交付 (design handoff) 实践 + 设计师社区. 不含: PSD→Figma 反向转换 / Sketch / Adobe XD / 纯前端 code handoff (HTML·CSS) / 印刷 CMYK 专业制版 (仅触及).) Master OS — automated mastery of Figma → Photoshop (PSD) 设计稿转换 (从业者视角) — 把 Figma 设计文件高保真转换为 Photoshop 分层 PSD, 核心是对齐两个工具的概念/渲染差异, 让产出的设计稿视觉一致. 覆盖: (a) 概念映射 — Figma frame / auto-layout / component / variant / constraint / vector-network / boolean / effect (drop·inner shadow / layer·background blur) / mask / blend mode / gradient / text-engine / color 与 Photoshop artboard / group / smart-object / linked / layer-style / shape-layer / path / clipping·layer mask / blend-mode 的对应关系与不可逆损耗点; (b) 转换方法栈 — 插件直出 PSD / 导出图层 (PNG·SVG) 再重组 / SVG·PDF 桥接 / 手工重建 / Figma REST API + Photoshop UXP·ExtendScript 脚本化, 各法在保真度-可编辑性-工时上的权衡与选型; (c) 保真度 QA — 字体回退与缺字处理 / 颜色空间 (sRGB·ICC profile) / 效果参数对齐 / @Nx·DPI 与栅格化 / 像素 diff 验收; (d) 两种交付目标 — 可编辑分层 PSD vs 像素保真扁平 PSD 的方法选择. 主战场 = Figma Community 插件 + Adobe 官方文档/论坛 + 设计交付 (design handoff) 实践 + 设计师社区. 不含: PSD→Figma 反向转换 / Sketch / Adobe XD / 纯前端 code handoff (HTML·CSS) / 印刷 CMYK 专业制版 (仅触及).: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on Figma → Photoshop (PSD) 设计稿转换 (从业者视角) — 把 Figma 设计文件高保真转换为 Photoshop 分层 PSD, 核心是对齐两个工具的概念/渲染差异, 让产出的设计稿视觉一致. 覆盖: (a) 概念映射 — Figma frame / auto-layout / component / variant / constraint / vector-network / boolean / effect (drop·inner shadow / layer·background blur) / mask / blend mode / gradient / text-engine / color 与 Photoshop artboard / group / smart-object / linked / layer-style / shape-layer / path / clipping·layer mask / blend-mode 的对应关系与不可逆损耗点; (b) 转换方法栈 — 插件直出 PSD / 导出图层 (PNG·SVG) 再重组 / SVG·PDF 桥接 / 手工重建 / Figma REST API + Photoshop UXP·ExtendScript 脚本化, 各法在保真度-可编辑性-工时上的权衡与选型; (c) 保真度 QA — 字体回退与缺字处理 / 颜色空间 (sRGB·ICC profile) / 效果参数对齐 / @Nx·DPI 与栅格化 / 像素 diff 验收; (d) 两种交付目标 — 可编辑分层 PSD vs 像素保真扁平 PSD 的方法选择. 主战场 = Figma Community 插件 + Adobe 官方文档/论坛 + 设计交付 (design handoff) 实践 + 设计师社区. 不含: PSD→Figma 反向转换 / Sketch / Adobe XD / 纯前端 code handoff (HTML·CSS) / 印刷 CMYK 专业制版 (仅触及). problems and wants industry-grade thinking, tool selection, or workflow guidance. 触发词：「figma 转 psd」「figma to psd」「figma 转 photoshop」「figma 导出 psd」「设计稿转换」

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。

调香师与香水 (调香师 / 香水 (Perfumery & Fragrance) — 香水创作与香气调配的职业认知操作系统，从业者/调香师/评香师/学习者视角。覆盖: (a) 第一性张力 — codifiable 理论层 (原料知识/香料化学/嗅觉家族分类/accord 和弦/配方结构 %/挥发度金字塔/IFRA 法规) ⇄ tacit 校准层 (嗅觉记忆/闻香训练/「the nose」/创作直觉/盲嗅识别)，这行的核心矛盾是「可背诵的原料与公式」与「不可言传的嗅觉记忆与品味」之间，嗅觉记忆是极致 tacit 技能; (b) 法系传统 vs 分子/合成派 — 法国 Grasse 天然香料 + haute parfumerie 艺术传统 (天然精油/原精/学徒制) vs 现代分子派 (aroma chemicals 香基/captives 专利分子/headspace 顶空捕香/功能香精)，两套对「香水是什么」的世界观; (c) 培养/传承 — ISIPCA (凡尔赛香水学校) + 四大香精公司内部调香学校 (Givaudan/Firmenich(DSM-Firmenich)/IFF/Symrise) + 学徒制 + 「鼻子」tacit 校准; 角色分工: perfumer(parfumeur 调香师) vs evaluator(评香师) vs flavorist(食用香精师); (d) 行业结构 — 四大香精公司寡头 (Givaudan/DSM-Firmenich/IFF/Symrise) + Mane/Robertet/Takasago，为品牌做 B2B 命题创作 (the brief → creation → mods 模型); vs niche/indie 小众独立香水 (artisanal/直营); 天然 (Grasse/精油) vs 合成 (香基/captives) 的成本与可持续之争; (e) 创作层 — 香调金字塔 (top/heart/base notes 前中后调)、accord 和弦、配方 (酒精中 % 浓度)、浓度分级 (parfum/EDP/EDT/EDC)、调香师的「香风琴」orgue、trials/mods 试样迭代、weighing 称量精度; (f) 法规与安全 — IFRA standards (原料限用)、EU 致敏原标签 (26→80+ allergens)、REACH、橡苔/atranol 限用、经典香水 (Mitsouko/Chanel No.5) 因法规被迫重配 (reformulation) 与创作自由之张力; (g) 评价/批评 — Luca Turin & Tania Sanchez (《Perfumes: The Guide》《The Secret of Scent》气味的科学)、香评人、Fragrantica/Basenotes 社区、vintage vs reformulation 之争、niche vs designer 之争。学派分歧: 法系天然传统派 vs 分子合成派、天然纯粹派 vs 合成实用派、haute parfumerie/niche 艺术派 vs mass designer 商业派、「鼻子=艺术家」vs「调香师=香气工程师/技师」、嗅觉科学之争 (Luca Turin 振动理论 vs 主流形状/受体理论)。不含: 香薰蜡烛/家居香氛纯生产营销、芳香疗法健康宣称 (aromatherapy)、纯化妆品配方学 (超出香精范畴)、DIY 家用香氛套件、精油传销/MLM。) Master OS — automated mastery of 调香师 / 香水 (Perfumery & Fragrance) — 香水创作与香气调配的职业认知操作系统，从业者/调香师/评香师/学习者视角。覆盖: (a) 第一性张力 — codifiable 理论层 (原料知识/香料化学/嗅觉家族分类/accord 和弦/配方结构 %/挥发度金字塔/IFRA 法规) ⇄ tacit 校准层 (嗅觉记忆/闻香训练/「the nose」/创作直觉/盲嗅识别)，这行的核心矛盾是「可背诵的原料与公式」与「不可言传的嗅觉记忆与品味」之间，嗅觉记忆是极致 tacit 技能; (b) 法系传统 vs 分子/合成派 — 法国 Grasse 天然香料 + haute parfumerie 艺术传统 (天然精油/原精/学徒制) vs 现代分子派 (aroma chemicals 香基/captives 专利分子/headspace 顶空捕香/功能香精)，两套对「香水是什么」的世界观; (c) 培养/传承 — ISIPCA (凡尔赛香水学校) + 四大香精公司内部调香学校 (Givaudan/Firmenich(DSM-Firmenich)/IFF/Symrise) + 学徒制 + 「鼻子」tacit 校准; 角色分工: perfumer(parfumeur 调香师) vs evaluator(评香师) vs flavorist(食用香精师); (d) 行业结构 — 四大香精公司寡头 (Givaudan/DSM-Firmenich/IFF/Symrise) + Mane/Robertet/Takasago，为品牌做 B2B 命题创作 (the brief → creation → mods 模型); vs niche/indie 小众独立香水 (artisanal/直营); 天然 (Grasse/精油) vs 合成 (香基/captives) 的成本与可持续之争; (e) 创作层 — 香调金字塔 (top/heart/base notes 前中后调)、accord 和弦、配方 (酒精中 % 浓度)、浓度分级 (parfum/EDP/EDT/EDC)、调香师的「香风琴」orgue、trials/mods 试样迭代、weighing 称量精度; (f) 法规与安全 — IFRA standards (原料限用)、EU 致敏原标签 (26→80+ allergens)、REACH、橡苔/atranol 限用、经典香水 (Mitsouko/Chanel No.5) 因法规被迫重配 (reformulation) 与创作自由之张力; (g) 评价/批评 — Luca Turin & Tania Sanchez (《Perfumes: The Guide》《The Secret of Scent》气味的科学)、香评人、Fragrantica/Basenotes 社区、vintage vs reformulation 之争、niche vs designer 之争。学派分歧: 法系天然传统派 vs 分子合成派、天然纯粹派 vs 合成实用派、haute parfumerie/niche 艺术派 vs mass designer 商业派、「鼻子=艺术家」vs「调香师=香气工程师/技师」、嗅觉科学之争 (Luca Turin 振动理论 vs 主流形状/受体理论)。不含: 香薰蜡烛/家居香氛纯生产营销、芳香疗法健康宣称 (aromatherapy)、纯化妆品配方学 (超出香精范畴)、DIY 家用香氛套件、精油传销/MLM。: top builders' mental models, tool stack, current workflows, jargon, and where to keep up. Trigger this skill when the user works on 调香师 / 香水 (Perfumery & Fragrance) — 香水创作与香气调配的职业认知操作系统，从业者/调香师/评香师/学习者视角。覆盖: (a) 第一性张力 — codifiable 理论层 (原料知识/香料化学/嗅觉家族分类/accord 和弦/配方结构 %/挥发度金字塔/IFRA 法规) ⇄ tacit 校准层 (嗅觉记忆/闻香训练/「the nose」/创作直觉/盲嗅识别)，这行的核心矛盾是「可背诵的原料与公式」与「不可言传的嗅觉记忆与品味」之间，嗅觉记忆是极致 tacit 技能; (b) 法系传统 vs 分子/合成派 — 法国 Grasse 天然香料 + haute parfumerie 艺术传统 (天然精油/原精/学徒制) vs 现代分子派 (aroma chemicals 香基/captives 专利分子/headspace 顶空捕香/功能香精)，两套对「香水是什么」的世界观; (c) 培养/传承 — ISIPCA (凡尔赛香水学校) + 四大香精公司内部调香学校 (Givaudan/Firmenich(DSM-Firmenich)/IFF/Symrise) + 学徒制 + 「鼻子」tacit 校准; 角色分工: perfumer(parfumeur 调香师) vs evaluator(评香师) vs flavorist(食用香精师); (d) 行业结构 — 四大香精公司寡头 (Givaudan/DSM-Firmenich/IFF/Symrise) + Mane/Robertet/Takasago，为品牌做 B2B 命题创作 (the brief → creation → mods 模型); vs niche/indie 小众独立香水 (artisanal/直营); 天然 (Grasse/精油) vs 合成 (香基/captives) 的成本与可持续之争; (e) 创作层 — 香调金字塔 (top/heart/base notes 前中后调)、ac

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。

Select the right Python charting library (seaborn, matplotlib, graphviz) and produce publication-quality static visualizations. Use when creating charts, plots, graphs, diagrams, heatmaps, visualizations from data, or when choosing between matplotlib/seaborn/graphviz. Also triggers for network diagrams, flowcharts, dependency trees, state machines, and entity-relationship diagrams. For interactive browser-rendered charts or uploaded data exploration, defer to charting-vega-lite instead.

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 find co-marketing partners, plan joint campaigns, or brainstorm partnership opportunities. Use when the user says 'co-marketing,' 'partner marketing,' 'joint campaign,' 'who should we partner with,' 'integration marketing,' 'cross-promotion,' 'collaborate with another company,' 'partnership ideas,' or 'co-brand.' For customer referral programs, see referrals. For launch-specific partnerships, see launch.

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。

GitHub OSS向け README.md の作成・改善・レビューを支援する。What/Why/How to start/Help/Maintainers の軸で情報を整理し、最短で動かせる Quickstart と docs への導線を構成する。 READMEの新規作成、既存READMEの再構成、READMEレビュー、ドキュメント分割の判断時に使用する。 トリガー：「READMEを作って」「READMEを改善して」「Quickstartを追加して」 「GitHub向けREADMEテンプレ」「READMEをレビューして」などのREADME関連リクエスト。

Expert guide for data visualization, charts, and dashboards using D3.js, Recharts, Chart.js, Nivo, and Tremor / Panduan ahli visualisasi data, chart, dan dashboard menggunakan D3.js, Recharts, Chart.js, Nivo, dan Tremor.

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。

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems.

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。

Register a plan artifact via the MCP backlog server. Use when you produce a document or report that downstream agents or worktree-isolated environments need to retrieve — feature-context, codebase-analysis, architect, T0-baseline, TN-verification, or research artifacts. Triggers include "store an artifact", "register a plan artifact", "write a report to the backlog", "upload artifact 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。

Create polished single-file HTML artifacts for plans, reports, explainers, code reviews, lightweight dashboards, prototypes, and one-off editing tools. Use when the user asks for a standalone HTML file, single HTML, HTML artifact, interactive report, shareable local artifact, Alpine.js artifact, custom CSS artifact, copy/export UI, or a browser-openable deliverable instead of 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。

Simulates a realistic VC Investment Committee: three partner archetypes debate a startup's merits, concerns, and deal terms, scored across 28 dimensions. Use when the user asks to simulate an IC, or how partners would debate their startup, and gives a deck, a company description, or a specific fund. A full run takes about 15–20 minutes, so for a passing question such as 'would a VC fund us?' or 'are we fundable?', answer briefly in chat and offer the simulation instead of starting it. When it runs, partners' views come from the scored simulation, never improvised.

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。

Consistent agent behavior after restart — progressive identity loading, working context reconstruction from persistent artifacts, fresh-vs-continuation detection, calibration through centering and attunement, and identity verification for coherence. Addresses the cold-start problem where an agent must reconstruct who it is and what it was doing from evidence rather than memory. Use at the start of every new session, after a session interruption or crash, when agent behavior feels inconsistent with prior sessions, or when persistent memory and current context appear contradictory.

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。

Practice aikido as a defensive martial art emphasizing harmony, redirection, and controlled resolution. Covers centering and grounding, ukemi (safe falling and rolling), core techniques (irimi-nage, shiho-nage, kote-gaeshi, ikkyo), blending and tai sabaki (body movement), randori (multiple attacker practice), weapons awareness, and applying principles off the mat. Use when learning a defensive martial art that prioritizes de-escalation, developing the ability to redirect aggression without causing unnecessary harm, building safe falling skills, or cultivating calm centeredness under physical pressure.

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 ASCII-art text banners for terminals, READMEs, and CLI startup messages. Use when a user asks for an ASCII banner, text art, バナー, アスキーアート, or a decorative header for a script/README.

Product marketing and go-to-market strategy for B2B SaaS launches and positioning. Use this skill when planning a product launch, developing positioning and messaging, analyzing competitive landscape, building customer advocacy programs, designing a customer referral program (who may accept the reward, how the introduction is made), designing a win/loss interview program, working out why we lose deals, designing GTM strategy, creating category positioning, planning analyst briefings, or deciding which country to expand into and how far to localize. Also use it for an early-stage startup where the founder is still doing the selling — running founder-led sales, setting up a design-partner program, judging whether you have product-market fit, deciding what not to do yet, deciding when to hire the first AE or first marketer, and moving upmarket to larger buyers. Also use it when your company has just acquired another (or is about to), to plan the marketing integration: what you may and may not do between signing and close, the first letter to the acquired customers, whether to keep, endorse, fold in or retire the acquired brand, merging the two marketing databases without mailing people who opted out, when to start cross-selling, and announcing a product sunset. Also use it to design a demand-generation campaign and the channel plan it runs on: one campaign with one job, the offer for buyers who are and are not in market, what each channel is for, the kill and scale rules set before launch, the follow-up sales agrees to, the yearly calendar of always-on programs and tentpole campaigns, and which channels to keep, test or stop. Also use it for brand marketing and demand creation — how much to spend on brand versus performance, what to measure when a brand campaign produces no conversion event, and how to answer "we cannot attribute it". Also triggers on: founder-led sales, founder-led GTM, design partners, design partner agreement, first customers, first 10 customers, do we have product-market fit, PMF, Sean Ellis test, very disappointed survey, pre-seed, seed stage, when to hire our first AE, first sales hire, first marketing hire, moving upmarket, going upmarket, enterprise readiness, first enterprise deal, what do enterprise buyers need before they sign, positioning, product launch, beta program, early access program, design partners, private preview, public preview, general availability, GA launch, when can we call it GA, can sales sell a beta feature, selling the roadmap, launch tier, competitive intelligence, messaging, customer advocacy, win/loss analysis, win/loss interviews, why we lose deals, closed-lost analysis, loss reason, close-reason field, competitive displacement, displace an incumbent, rip and replace, competitive takeout, switch from a competitor, win deals from a competitor, incumbent contract, renewal window, auto-renewal notice period, switching costs, EU Data Act, cloud switching rights, why do we lose to no decision, GTM, category design, ideal customer profile, ICP, what is our real ICP, who actually buys from us, refresh our ICP from closed-won deals, ICP refresh before planning, analyst briefing, G2 review, international expansion, market entry, expand into Europe, which country should we launch in next, localization, translate our site, in-country go-to-market, regional GTM, is cold email legal in Germany, brand marketing, brand awareness, brand vs performance, brand versus demand gen, demand creation, demand capture, 95-5 rule, out of market buyers, category entry points, distinctive brand assets, mental availability, brand tracking, brand health, brand lift, share of search, how do we measure brand, justify brand spend, brand budget. Also triggers on public-sector marketing: sell to government, government marketing, public sector go-to-market, federal marketing, state and local government, SLED, FedRAMP, FedRAMP marketing claims, can we say FedRAMP ready, GovRAMP, StateRAMP, VPAT, accessibility confor

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。

Search LCSC Electronics for electronic components — find parts by LCSC number (Cxxxxx) or MPN, check stock/pricing, download datasheets, analyze specifications. Sister company to JLCPCB, same parts library. Sync and maintain a local datasheets directory for a KiCad project. No API key needed — uses the free jlcsearch community API. Use this skill when the user mentions LCSC, JLCPCB parts library, JLCPCB assembly parts, production sourcing, Cxxxxx part numbers, needs to find LCSC equivalents for parts, is preparing a BOM for JLCPCB assembly, or wants to download datasheets and LCSC is available. For package cross-reference tables and BOM workflow, see the `bom` skill.

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 SEO-optimized long-form articles targeting specific keywords using the They Ask You Answer Big 5 framework (Marcus Sheridan). Articles are categorized by Big 5 type (Cost, Problems, Versus, Best/Reviews, How-To) and structured accordingly. The "answer first" rule applies to every article. Use when the user asks for an SEO article, blog post for ranking, "rank for keyword X", organic content, search-optimized post, pillar page, or content for organic traffic. Includes keyword targeting, search intent matching, internal linking suggestions, and meta tags. For improving an existing article, see copy-review. For deciding what to write about, see social-calendar pillars and icp-research. For repurposing it, see content-repurposer.

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 structured U.S. art law summaries with Bluebook citations, doctrinal analysis, and stakeholder guidance. Use when researching art law precedents, advising on art transactions, preparing for art market litigation, or surveying a doctrine or statute across ownership, provenance, copyright, VARA, NAGPRA, authentication, NFTs, or AI-generated art.

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。

Load this skill whenever the project contains charts, graphs, data visualizations, infographics, or any visual representation of data (bar charts, line charts, pie charts, scatter plots, dashboards). Under no circumstances render a chart without a text alternative, data table, or summary. Prioritize conveying the same information through non-visual means.

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。

Formatting, structure, and execution rules for Quarto markdown documents. Trigger when: - Writing, editing, or rendering Quarto documents, reports, presentations, or websites. - Files matching the pattern **/*.qmd are in the workspace or referenced. - Tasks involve: quarto render, quarto preview, knitr, jupyter. - Prompt contains keywords: quarto, qmd, yaml header, code chunk, callout, cross-reference.

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。

Envoyer un vrai courrier papier — lettre PDF, carte illustrée (carte postale, carte pliée, carte carrée, carte géante), suivi, recommandé avec accusé de réception, recommandé électronique eIDAS — depuis une application, via l'API Merci Facteur. Utiliser dès qu'il s'agit d'envoyer, poster, imprimer ou expédier du courrier physique depuis du code, d'envoyer une carte depuis une application, de brancher un envoi postal sur un événement, un formulaire, un cron ou un webhook, ou de déboguer un appel sendCourrier. Couvre le contrat exact, les pièges de nommage qui font échouer l'appel, l'idempotence et le comportement en cas d'échec.

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。

Start work on a Jira ticket by fetching ticket details, creating a properly named feature branch, and beginning codebase investigation. Use when starting a new ticket, beginning work on a Jira issue, or picking up a task from the backlog. Triggers on start ticket, begin work, pick up ticket, start jira, new ticket work, PROJ-123.

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。

Interactive English conversation practice partner for Japanese learners. Use this skill whenever the user wants to practice speaking English, role-play a real-life situation (hotel check-in, restaurant, airport, business meeting, technical discussion, code review, job interview, daily small talk, etc.), discuss a technical article in English, or asks how to phrase something naturally in English. Trigger on requests like 'let's practice English', 'I want to talk in English', 'role play', 'pretend you are a ___', 'discuss this article in English', 'how do I say X in English'. 英会話練習・ロールプレイ・英語表現の質問のためのスキル。「英会話したい」「英語で話そう」「ロールプレイ」「ホテルのチェックイン練習」「この記事について英語で話したい」「xxって英語でどう言う？」などのリクエストで起動する。ユーザーは音声入力で会話する想定。会話前に想定問答・頻出表現・単語を提示し、会話を開始、最後に添削まで行う。

When the user wants to find co-marketing partners, plan joint campaigns, or brainstorm partnership opportunities. Use when the user says 'co-marketing,' 'partner marketing,' 'joint campaign,' 'who should we partner with,' 'integration marketing,' 'cross-promotion,' 'collaborate with another company,' 'partnership ideas,' or 'co-brand.' For customer referral programs, see referrals. For launch-specific partnerships, see launch.

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。