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「art」の検索結果

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概要と使いどころ

Start (or restart) a local multi-node Temps cluster using Docker-in-Docker — one control plane + 3 worker nodes, each a privileged DinD container running its own dockerd + `temps agent`, wired with the real multi-host overlay (VXLAN, compute_cidr allocation) via `tools/dev-cluster/` in whichever checkout/worktree you run it from. Invoke when the user says "start the temps cluster", "spin up a multi-node dev cluster", "test this with multiple workers", "bring up worker nodes locally", "docker in dind cluster", or wants to verify cross-node behavior (node targeting, cluster DNS, overlay networking, node join/mTLS) that a single-node `start-temps` server cannot exercise. Distinct from `start-temps` (single-node, native binary, port-slot based) and `start-temps-ee` (single-node EE binary) — this is the only path that actually has more than one node.

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。

gotempsh/temps8382026年10月13日 更新

charts-3d

無料

3D chart visualization with Swift Charts using Chart3D, SurfacePlot, interactive pose control, and surface styling — plus a 2D Swift Charts construction reference (marks, axes, selection, SectorMark, scrollable charts). Use when creating data visualizations with Swift Charts.

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。

rshankras/claude-code-apple-skills7912026年7月24日 更新

管理咨询 (管理咨询 (Management Consulting) — 战略与管理咨询的职业认知操作系统,从业者/咨询顾问/想入行者/采购咨询服务的客户视角。覆盖: (a) 第一性张力 — 假设驱动 (hypothesis-driven / answer-first / Day-1 answer) 的「先有答案再验证」⇄ 数据驱动 (data-led / bottom-up) 的「先穷尽事实再归纳」,这行的核心张力是「先射箭再画靶 vs 先画靶再射箭」,资深人偏 top-down 假设树减少 boil-the-ocean,但要时刻防 confirmation bias; 以及更深层的张力 — 「卖洞见 (insight / so-what) vs 卖工时 (analysis / 体力)」,「客户影响 (client impact / 落地) vs 智识严谨 (intellectual rigor / 漂亮 deck)」; (b) 方法论正典 (最标准化、最易蒸出高质量) — MECE (相互独立完全穷尽)、issue tree / logic tree (问题树/逻辑树)、hypothesis-driven problem solving (假设驱动)、Pyramid Principle (Minto 金字塔原理: SCQA 情境-冲突-疑问-回答 + 结论先行 + 自上而下 + 归纳/演绎)、80/20 (帕累托/抓大放小)、so-what (所以呢/洞见提炼)、storyline (故事线/ghost deck 鬼影稿)、driver tree / profit tree、2x2 矩阵、value chain、frameworks (Porter 五力/3C/4P/7S/BCG 矩阵/价值链) 既是脚手架也是陷阱 (套框架 vs 真洞见); (c) 行业结构 — MBB (McKinsey/BCG/Bain 战略三巨头) vs Big Four 咨询臂 (Deloitte/PwC Strategy&/EY-Parthenon/KPMG) vs 精品战略所 (Oliver Wyman/Kearney/Roland Berger/L.E.K./Arthur D. Little) vs 专业/职能 boutique (运营/数字化/PE 尽调); up-or-out (非升即走)、leverage model (杠杆模型: 1 个合伙人带多个 EM/咨询师/分析师的金字塔)、partner/principal/EM(项目经理)/associate(咨询师)/analyst(分析师) 职级; (d) 项目交付模型 (the case/study/engagement) — 提案/SOW (scope of work)、problem definition (问题定义/真问题 vs 表象问题)、workplan (工作计划)、hypothesis tree (假设树)、analysis (分析/建模)、synthesis (综合)、recommendation (建议)、implementation (落地); 客户管理 (steering committee 指导委员会、stakeholder 利益相关方、对齐); (e) 产出物 — the deck (PPT 幻灯片是咨询的母语)、executive summary、action title (行动标题/每页一句话结论)、ghost deck (先搭骨架后填数据)、Excel 财务模型、framework 图; (f) 职业/招聘 — case interview 生态 (案例面试: Victor Cheng LOMS/Case in Point/market sizing 市场估算/估算题/fit 行为面)、网申-笔试-案例面、up-or-out、exit options (退出路径: PE/VC/corp dev 企业发展/战略岗/创业/industry); (g) 争议/批判 — 咨询的价值之辩 (「借你的表告诉你时间」「frameworks 是剧场表演 vs 真洞见」Matthew Stewart《The Management Myth》)、McKinsey 的丑闻 (Purdue 阿片类/独裁政府/ICE/利益冲突, Bogdanich & Forsythe《When McKinsey Comes to Town》)、咨询 vs 自建战略部、generalist 通才 vs specialist 专才之争、AI/GenAI 对初级分析师工作的冲击; (h) 流派 — 战略经典 (Porter 定位学派/五力 vs 资源基础观 RBV vs 蓝海战略 Kim&Mauborgne vs 颠覆式创新 Christensen vs Mintzberg 应急战略批判 planning school); 三巨头气质分野 (McKinsey 事实驱动/CEO 信任/通才, BCG 概念/思想领导力/经验曲线/增长-份额矩阵, Bain 结果导向/NPS 净推荐值/PE 关系/与客户深度绑定)。不含: 投行 M&A/财务顾问 (估值/承销超出范畴)、纯 IT 实施/系统集成 (SI 人力外包)、纯审计/税务、纯人力 RPO/猎头、内部战略部 only (虽相关但本 skill 聚焦专业服务咨询的外部视角)。) Master OS — automated mastery of 管理咨询 (Management Consulting) — 战略与管理咨询的职业认知操作系统,从业者/咨询顾问/想入行者/采购咨询服务的客户视角。覆盖: (a) 第一性张力 — 假设驱动 (hypothesis-driven / answer-first / Day-1 answer) 的「先有答案再验证」⇄ 数据驱动 (data-led / bottom-up) 的「先穷尽事实再归纳」,这行的核心张力是「先射箭再画靶 vs 先画靶再射箭」,资深人偏 top-down 假设树减少 boil-the-ocean,但要时刻防 confirmation bias; 以及更深层的张力 — 「卖洞见 (insight / so-what) vs 卖工时 (analysis / 体力)」,「客户影响 (client impact / 落地) vs 智识严谨 (intellectual rigor / 漂亮 deck)」; (b) 方法论正典 (最标准化、最易蒸出高质量) — MECE (相互独立完全穷尽)、issue tree / logic tree (问题树/逻辑树)、hypothesis-driven problem solving (假设驱动)、Pyramid Principle (Minto 金字塔原理: SCQA 情境-冲突-疑问-回答 + 结论先行 + 自上而下 + 归纳/演绎)、80/20 (帕累托/抓大放小)、so-what (所以呢/洞见提炼)、storyline (故事线/ghost deck 鬼影稿)、driver tree / profit tree、2x2 矩阵、value chain、frameworks (Porter 五力/3C/4P/7S/BCG 矩阵/价值链) 既是脚手架也是陷阱 (套框架 vs 真洞见); (c) 行业结构 — MBB (McKinsey/BCG/Bain 战略三巨头) vs Big Four 咨询臂 (Deloitte/PwC Strategy&/EY-Parthenon/KPMG) vs 精品战略所 (Oliver Wyman/Kearney/Roland Berger/L.E.K./Arthur D. Little) vs 专业/职能 boutique (运营/数字化/PE 尽调); up-or-out (非升即走)、leverage model (杠杆模型: 1 个合伙人带多个 EM/咨询师/分析师的金字塔)、partner/principal/EM(项目经理)/associate(咨询师)/analyst(分析师) 职级; (d) 项目交付模型 (the case/study/engagement) — 提案/SOW (scope of work)、problem definition (问题定义/真问题 vs 表象问题)、workplan (工作计划)、hypothesis tree (假设树)、analysis (分析/建模)、synthesis (综合)、recommendation (建议)、implementation (落地); 客户管理 (steering committee 指导委员会、stakeholder 利益相关方、对齐); (e) 产出物 — the deck (PPT 幻灯片是咨询的母语)、executive summary、action title (行动标题/每页一句话结论)、ghost deck (先搭骨架后填数据)、Excel 财务模型、framework 图; (f) 职业/招聘 — case interview 生态 (案例面试: Victor Cheng LOMS/Case in Point/market sizing 市场估算/估算题/fit 行为面)、网申-笔试-案例面、up-or-out、exit options (退出路径: PE/VC/corp dev 企业发展/战略岗/创业/industry); (g) 争议/批判 — 咨询的

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。

swaylq/master-skill1552026年9月6日 更新

Digital art tools, techniques, and workflows for art education. Covers raster and vector workflows, digital painting, photo manipulation, generative and procedural art, 3D modeling and rendering, pixel art, the relationship between traditional skills and digital execution, and ethical considerations of AI-generated imagery. Use when working with digital tools, evaluating digital art, or bridging traditional art concepts into digital practice.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Major art movements and their historical context for art education. Covers 12 movements from the Renaissance to contemporary art, their defining characteristics, key artists, signature works, and the intellectual/social forces that produced them. Use when analyzing artworks in historical context, understanding stylistic lineages, identifying influences across periods, or connecting studio practice to art-historical precedent.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Use when the user asks to forge, scaffold, or author a new cartridge — content cartridge, department cartridge, or chipset bundle. Drives the cartridge-forge loop (scaffold → fill → gate checks → commit) via the skill-creator cartridge CLI.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Partnership and co-marketing campaign planner — partner selection criteria, joint content strategy, cross-promotion plans, and co-branded assets. Use when "partnership", "co-marketing", "partner program", "cross-promotion", "joint venture", "co-branded", "partner campaign", or any request to plan or execute a marketing partnership.

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。

cgallic/kai-cmo-harness562026年10月3日 更新

Use when a task needs the judgment of an Art Therapist — matching art media to a client's regulation capacity via the Expressive Therapies Continuum, scoring a standardized directive (PPAT, KFD, DAP) with a validated instrument like FEATS as part of assessment, deciding between a directive and open-studio session structure, navigating informed consent and disposition for client-made artwork, or distinguishing an art-as-therapy approach from an art-psychotherapy approach for a given client.

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。

wonsukchoi/domain-experts212026年10月12日 更新

Generate dark-mode-compatible inline SVG data visualization charts for blog posts. Supports horizontal bar, grouped bar, donut, line, lollipop, area, and radar charts with automatic platform detection (HTML vs JSX/MDX). Enforces chart type diversity, accessible markup (role=img, aria-labelledby), source attribution, and transparent backgrounds. Use when user says "blog chart", "generate chart", "data visualization", "svg chart", "blog graph", or "visualize 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。

gabrielmoreira/agent-skills-mirror192026年10月12日 更新

Generate diverse creative illustrations via OpenAI Images API. Create book illustrations, editorial art, children's book art, concept illustrations, and artistic scenes. Use when user needs creative visual content for stories, articles, presentations, or artistic projects (e.g., "illustrate a fairy tale scene", "create editorial art about technology", "design children's book illustrations", "generate concept art for a story").

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。

modbender/skill-library-mcp162026年9月28日 更新

Publishes HTML or Markdown as display.dev URLs with public, company, or private access. Supports signup, claiming, sharing, browsing, bounded reads, exact edits, and comment iteration. Use when the user asks to "publish this", "share this", "share with the org", "post this online", "make a private link", "share with [email]", "publish a report", "list my artifacts", "find an artifact", "publish a large file", "publish this generated HTML file", "read this artifact", "search inside this artifact", "change this passage", "make a copy of this artifact", "duplicate version", "create a display.dev account", "claim this publish", "add a company email domain", "transfer an email domain", "change the email domains add-on", "show my referral link", "show referral rewards", "watch comments on this artifact", "respond to comments", or "resolve this comment thread". Use whenever a request contains a display.dev artifact URL (`*.dsp.so/*`). Anonymous publishing returns a 30-day preview and browser claim URL.

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。

display-dev/skill122026年10月9日 更新

algorithmic-art-jp

無料日本語概要

Japanese algorithmic and generative art skill covering traditional pattern generation (wagara), calligraphy simulation, zen garden generators, and mathematical patterns from Japanese art. Triggers on requests for 和柄生成, ジェネラティブアート, アルゴリズミックアート, 伝統紋様パターン, Japanese generative art.

LinkX-Japan/ai-souken-workflows62026年3月12日 更新

Load bounded working context at the start of a coding session. FIRES ON EVERY FIRST USER MESSAGE in a fresh session, regardless of content — including bare greetings ("hi", "hello", "hey"), task-only openers, or "let's start". Also triggers on: "fresh session", "session start", "first message in a new thread", "new chat", "cold start", "begin work in this repo", "starting work", "continue from prior session", "what were we working on", "resume", "what happened last time", "load memory", "recall context", "create a handoff", "prior session context", "latest handoff", "current state", "decision context". Skip ONLY if the user explicitly says "fresh start" or "ignore prior context". Self no-ops if invoked mid-session when context is already loaded.

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。

dvy1987/agent-loom32026年8月8日 更新

ascii-art

無料日本語概要

文字のバナー、吹き出し、飾り枠を作り、画像を文字で描いたアートに変換します。用途に応じてローカルツールや無料APIを選び、既存作品の検索にも対応します。

  • ターミナル用の文字バナー作成
  • 吹き出しや飾り枠の追加
  • 画像を文字アートに変換したいとき
NousResearch/hermes-agent25.3万2026年10月13日 更新

pixel-art

無料日本語概要

写真や画像をNES、Game Boyなどの配色でレトロなドット絵に変換します。雨や雪、星のきらめきを重ねた短いMP4やGIFの作成にも対応するスキル。

  • 写真をレトロなドット絵にしたいとき
  • ゲーム風のアバターやキャラクター制作
  • ポスターやSNS用のドット絵制作
NousResearch/hermes-agent25.3万2026年10月13日 更新

Deliver a runnable local browser app so the user can operate it on the first handoff. This delivery skill does not choose whether a requested local system should be a browser app. On a current turn that explicitly says to implement a brand-new browser project now, load bundled:greenfield-project-scaffolding before project work only after no-peek or permitted top-level placement facts prove that no named or suitable current-folder target resolves the root; never hand off from planning or answer-only turns, existing work, a named or suitable target, or standalone or single-file delivery. Resolve user-blocking product or interface choices with an available interaction surface; resolving those choices alone never authorizes implementation. Always call read_skill for bundled:browser-app-delivery before creating or materially changing a local browser app that owns its start path or a playable browser game. Also load it when the user requests a paste-ready, single-file, offline, or immediately playable browser artifact, even if no local start path should remain, unless the user says they will open or check it themselves or explicitly declines verification. On completed local-server delivery, include exact start commands, a concrete local URL, and explicit browser-open wording. On completed standalone delivery, hand off the exact artifact path or paste URL and smoke result without inventing a server. Do not load it for a self-contained static file that has no owned start path if the user either says they will open or check it themselves or explicitly declines verification. Do not load it for component/style-only edits, deployed sites, backend/API-only work, browser QA, review, explanation, plan-only, or explicit stop/no-tool turns.

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。

asgeirtj/system_prompts_leaks7万2026年10月12日 更新

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。

coreyhaines31/marketingskills5.5万2026年10月9日 更新

Build and scale partner ecosystems that drive revenue and platform adoption. Use when building partner programs from scratch, tiering partnerships, managing co-marketing, making build-vs-partner decisions, or structuring crawl-walk-run partner deployment.

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/awesome-copilot4万2026年10月12日 更新

Conduct comprehensive GDPR compliance assessments by evaluating data processing activities against EU Regulation 2016/679, including Article 30 records of processing, lawful basis validation, data subject rights implementation, Data Protection Impact Assessments (DPIAs) under Article 35, breach notification procedures, international transfer safeguards (SCCs, adequacy decisions), and technical/organizational measures under Article 32. Use when processing personal data of EU residents, preparing for supervisory authority audits, implementing privacy-by-design for new systems, scoping compliance gaps for M&A due diligence, assessing third-party processors, or responding to data subject access requests at scale. Incorporates 2026 guidance from ICO, EDPB, and post-Data (Use and Access) Act 2025 UK-GDPR considerations. Do not use for implementing specific Article 32 controls — use implementing-gdpr-data-protection-controls; or for DSAR automation — use implementing-gdpr-data-subject-access-request.

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。

mukul975/Anthropic-Cybersecurity-Skills3.4万2026年8月31日 更新

EU AI Act (Regulation (EU) 2024/1689) operational compliance for compliance teams. Three Article-level decisions: (1) What's the risk tier of this AI system — prohibited (Art. 5), high-risk (Art. 6 + Annex III), limited-risk (Art. 50), or minimal-risk? (2) For high-risk systems, what's the Article 43 conformity assessment route (Module A internal control vs Module H full QMS + notified body) and what goes in the Annex IV technical documentation? (3) Per organizational role (provider / deployer / importer / distributor / authorized representative), what are the active obligations and deadlines? Use during AI system intake review, when planning conformity assessment, or when scoping deployer obligations. Cites Articles + Annexes for every output. NOT executive AI strategy (see chief-ai-officer-advisor). NOT a legal substitute.

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。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

Use when reviewing or rebalancing direct vs. partner-led channel economics — computing fully-loaded cost-to-serve per channel, channel ROI with cash / LTV / marginal lenses, and optimal channel mix subject to constraints. For Head of Commercial, RevOps, and VP Sales doing quarterly channel review when pipeline is mixed (e.g., 60% direct + 40% partner-led) and nobody actually knows which channel makes money after CAC, support load, partner discount, deal-velocity differences, retention differential, and overhead allocation are all loaded in. Outputs cost to serve, channel ROI verdicts (DOUBLE-DOWN / MAINTAIN / DEFUND / EXIT), a sensitivity-tested channel-mix recommendation, and the diminishing-returns inflection (e.g., 'which channel actually makes money — direct or partner?').

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。

alirezarezvani/claude-skills2.8万2026年8月30日 更新

Use when creating, extending, debugging or publishing a Lightweight Charts™ plugin — a custom series, a series primitive or a pane primitive — or when turning a chart idea ("I want the chart to show/draw X") into a working plugin. Covers choosing the plugin type, scaffolding with create-lwc-plugin, building on @tradingview/lwc-toolkit instead of hand-rolled helpers, which of the official plugin packages to read as the reference implementation, where the docs are, and the autoscale, whitespace, visible-range, hit-test and conflation mistakes every plugin author makes once. Reach for it whenever the user mentions a custom series, primitive, renderer, drawing on the chart canvas, lwc-plugin, plugin-examples, the toolkit, or the plugin catalog — even if they never say the word "plugin".

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。

tradingview/lightweight-charts1.8万2026年10月13日 更新

Startup-tailored AWS architecture advice for non-agent workloads, adjusted to the company's stage (pre-revenue through Series B+), team size, runway, and credits. Not for AI agents: deploying an AI agent on AWS, picking its runtime, or any agentic architecture is agent-advisor. Use when a founder wants guidance or a recommendation rather than code changes: which services to choose, how to plan or review an architecture, how to stretch credits and control cost, or how to prepare architecture for a fundraise or technical diligence. For an interactive discovery flow that scaffolds and writes the architecture into the codebase, use start-building-for-startups. Do not use for: writing or scaffolding code, factual AWS Activate / programs / credits lookups (see knowledge-base-for-startups), a single copy-paste prompt (see prompt-library-for-startups), or migration intent such as GCP-to-AWS, Azure-to-AWS, or Heroku-to-AWS (see the migration skills: `gcp-to-aws`, `azure-to-aws`, `heroku-to-aws`, `llm-to-bedrock`).

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。

aws/agent-toolkit-for-aws2,8582026年10月13日 更新

Add a chart (line, bar, area, pie, or scatter) to a dataset's showcase in a PortalJS portal. Installs recharts, writes a reusable Chart component, and renders it in the showcase Views section. Use when visualizing a dataset already registered in datasets.json.

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。

datopian/portaljs2,3622026年10月8日 更新