「art」の検索結果

Artillery.io integration. Manage data, records, and automate workflows. Use when the user wants to interact with Artillery.io 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。

API2Cart integration. Manage data, records, and automate workflows. Use when the user wants to interact with API2Cart 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。

API to every Ecommerce Cart and Marketplace integration. Manage data, records, and automate workflows. Use when the user wants to interact with API to every Ecommerce Cart and Marketplace 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。

3dcart integration. Manage data, records, and automate workflows. Use when the user wants to interact with 3dcart 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。

Create professional equity research earnings update reports (8-12 pages, 3,000-5,000 words) analyzing quarterly results for companies already under coverage. Fast-turnaround format focusing on beat/miss analysis, key metrics, updated estimates, and revised thesis. Includes 1-3 summary tables and 8-12 charts. Use when user requests "earnings update", "quarterly update", "earnings analysis", "Q1/Q2/Q3/Q4 results", or post-earnings report.

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 beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.

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。

Toolkit for styling artifacts with a theme. These artifacts can be slides, docs, reportings, HTML landing pages, etc. There are 10 pre-set themes with colors/fonts that you can apply to any artifact that has been creating, or can generate a new theme on-the-fly.

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。

麦当劳门店派对/包场/拼团的选址、成团调度与筹备助手。当用户想办生日派对、亲子派对、主题派对、品鉴会、读书会、麦麦体验营，或说「麦当劳派对」「派对拼团」「包场」「生日会怎么办」「哪家店能办派对」「还差几个人成团」「包场还是拼团划算」「帮我写拼团招募文案」「做一张派对邀请函」「孩子派对吃什么不超标」时使用。基于麦当劳官方 MCP（mcp.mcd.cn）的 party 系列工具：扫描全城场次、估算成团概率、对比包场与拼团成本、按官方营销活动日历挑最佳日期、审查儿童餐营养、生成招募卡与邀请函。

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, refine, validate, and render diagrams from natural language, notes, code snippets, schemas, tables, or existing diagram source. use for flowcharts, swimlanes, sequence diagrams, state diagrams, er diagrams, class diagrams, architecture/c4-style diagrams, dependency graphs, gantt charts, mind maps, user journeys, sankey-style flows, org charts, network graphs, and other visual models. supports mermaid by default, graphviz dot for complex graph layout, plantuml for uml-heavy engineering diagrams, and svg output when direct markup is more reliable.

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 a complete repository skill from a user's idea, including the workflow instructions, references, scripts or assets, agent metadata, skill-card artwork, cinematic banner artwork, README links, discovery metadata, and validation. Use when the user asks to create a new skill, add a skill to this collection, turn a workflow into a reusable skill, or make a skill's documentation and artwork consistent with the repository.

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 truthful, human-centered marketing campaigns for an app or product, including positioning, channel copy, original artwork, editable layouts, README banners, and selective website integration. Use when asked to make launch materials, promotional artwork, social assets, campaign kits, ads, or marketing content from an existing product; to adapt a visual reference without copying it; or to add approved campaign art to product surfaces. Do not invent claims, fake UI, publish, deploy, or replace product proof without explicit evidence and authorization.

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。

Think and work like an expert Astroparticle Physicist. Use when a task calls for Astroparticle Physicist judgment. Reasons from flux times cross section times acceptance, Poisson counting over structured backgrounds, and Cherenkov photoelectron budgets through SkyLLH unbinned likelihoods, Geant4/CORSIKA chains validated on through-going-muon and calibration samples, and Feldman-Cousins/CLs limits, while treating atmospheric-neutrino and downgoing-muon contamination, ER/NR leakage and the neutrino fog, and look-elsewhere trials as first-class failure modes.

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 one Content-Derived Design direction from an HTML source, or let Auto choose the strongest direction. Use when the user says /reimagine-it generate, "redesign this page", "make it a landing page", "turn this into an infographic", names a token (all 17: webpage, infographic, svg, 3js, simulation, artistic, cinematic, dashboard, photography, landing, editorial, gradient, showcase, motion, glass, lookbook, particles), or wants a content-aware redesign instead of a mood board. CLI: npx reimagine-it --auto -i page.html -o out.html. Part of the reimagine-it Content-Derived Design suite.

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。

Med-adapted recent-quarter review: last print financials, pipeline-milestone awareness, and FDA-event context — reads the quarter through the med lens (milestones moved, runway, regulatory updates) rather than generic financials alone.

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。

Plan, prompt, generate, reference, edit, motion-control, and quality-review videos with Kuaishou's direct Kling AI video platform and API, especially Kling VIDEO 3.0, 3.0 Omni, 3.0 Turbo, native audio, multi-shot, elements, start/end frames, and image/video references. Use for first-party Kling video production or API integration, not Kolors image generation, avatars, standalone audio, consumer-only membership advice, or third-party Kling gateways.

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 Cartesia Sonic and related Cartesia voice APIs for production speech: text-to-speech, realtime WebSocket TTS, voice selection, instant and professional voice cloning, pronunciation/language/emotion controls, voice localization, voice changer, pricing/concurrency planning, privacy/security review, and QA for narration, ads, localization, dubbing, avatars, and interactive voice agents.

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 Luma AI's first-party Photon and Photon Flash image API for text-to-image, image/style/character references, image modification, asynchronous generation, secure artifact handling, production prompting, cost control, and policy-aware delivery. Trigger for Luma Photon API integration or production work; do not use for Ray video, UNI image models, the Luma consumer app, or third-party Photon gateways.

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 WeChat Official Account articles, analyze account profiles, track article performance, and read comments. Covers article discovery, account profiling, engagement statistics, comment analysis, and content strategy research on China's dominant messaging ecosystem.

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 potential partners by analyzing company profiles, product fit, market positioning, team background, and mutual connections. Combines firmographic data, content analysis, and social signals for partnership qualification and relationship mapping.

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 startups and emerging companies with funding data, team composition, product positioning, market traction, and news coverage. Combines Apollo firmographics, LinkedIn team data, and web intelligence for comprehensive startup due diligence.

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, implement, or review beautiful article work with format, accessibility, performance, and visual-verification controls. Use when the requested deliverable depends on beautiful article.

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 review comparison article writer deliverables with audience, evidence, voice, and conversion-quality controls. Use when the user explicitly asks for comparison article writer work.

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。

Analyzes community composition using constrained ordination (CCA, RDA, db-RDA), variance partitioning (varpart), indicator species analysis (indicspecies multipatt), and distance-based environmental gradient methods with vegan. Links species composition to environmental explanatory variables. Use when testing how environmental gradients structure species communities, identifying habitat indicator taxa, or partitioning explained variation among predictors. Not for basic unconstrained ordination and PERMANOVA (see microbiome/diversity-analysis).

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。