1.2万 件 ・ 関連度順
概要と使いどころ
MLOps across model deployment, ML pipelines, monitoring, and feature stores. Use when deploying models to production, building training pipelines, setting up drift detection, configuring feature stores, or automating ML CI/CD workflows.
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。
Audit data quality across pipelines, warehouses, and stores. Use when designing a DQ program, defining DQ dimensions, building rule-based checks, detecting schema drift, monitoring freshness SLAs, or responding to a DQ incident.
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。
Evaluate completed mediation-competition problems consisting of general information and confidential packets for both sides. Use when asked to validate, audit, score, quality-control, or assess competition readiness; identify factual, numerical, chronological, authority, commercial-logic, or confidentiality defects; test mediation usefulness, BATNAs, settlement corridors, information asymmetry, and opportunities for firmness, cooperation, imagination, and clarification; or produce an author-only validation report. Perform a qualified partial review when packets are missing. Diagnose by default; do not generate a new problem or edit source packets unless repairs are expressly requested. Requires access to all supplied files and a host capable of reading their formats; otherwise disclose the unreviewed material and resulting limits.
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。
Méthodologie « verification-first » pour les Chambres Africaines Extraordinaires (procès Hissène Habré, Dakar). Toute citation est vérifiée (forumchambresafricaines.org, legal-tools.org). Couvre le jugement du 30 mai 2016, l'arrêt d'appel du 27 avril 2017 (réparations de 82,290 milliards FCFA pour 7 396 victimes), et la compétence universelle. Aide à la recherche, pas un conseil juridique. Fait partie de la bibliothèque open source « Skills for International Justice » — méthodologie : github.com/jeannesulzer/international-criminal-tribunals-skills
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。
Assess and operationalize implementation readiness for high-risk AI systems under the EU AI Act Annex III, including provider and deployer obligations, conformity assessment, post-market monitoring, and EU database registration. Use when users say things like “we classified this as high-risk, what now?”, “build an EU AI Act readiness plan”, “assess our Annex III compliance gaps”, “what do providers/deployers of high-risk AI need to implement?”, “prepare for conformity assessment”, or “create a high-risk AI implementation roadmap.”
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 you want to brainstorm and check available .com domains for a new project — brand naming, aftermarket pricing (HugeDomains / Afternic / Sedo / Dan), USPTO trademark screening, and social handle availability. Built on Laura Roeder's "work backwards from availability" method. Combines Vercel CLI, whois, Domainr, Namecheap, and agent-browser, each for what it reliably does. Workflow: budget → brainstorm → availability check → whois cross-check → price → aftermarket sweep (plus liveness probe and drop-watch) → bucket → negotiate → trademark + socials → buy. Triggers on "/domain," "find a domain," "check domain availability," "brainstorm a domain," "what .com is available for X," "domain hunt," "name my project," "is X.com available," "aftermarket price on X.com," "trademark check for X."
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 you want multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any "I need to actually understand X." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on "/deep-research," "research X," "investigate X," "do a deep dive on X," "look into X," "what's actually happening with X," "due diligence on X," "validate this market." Differs from a one-shot web search: this is multi-pass with verification.
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。
Measure and shrink the always-loaded context of a Claude Code harness (CLAUDE.md + rules without paths frontmatter) back under budget — migrate narrative to reference files, convert rules to path-scoped or skill-triggered loading, and verify zero governance loss with deterministic preservation checks. Use on "harness diet", "context diet", "rules diet", "CLAUDE.md too long", "always-load budget", "trim my rules", "context bloat", "하네스 다이어트", "룰 다이어트", "컨텍스트 다이어트", "always-load 줄여줘". Not for one-off prose editing or project docs cleanup.
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 patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.
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 patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.
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 one-page company profile slides (strip profiles) for A-share targets in pitch books and deal materials. Adapted from the original strip-profile skill for Chinese companies, A-share market data, and Chinese business terminology. Triggers on "A股公司简介", "公司概况", "strip profile China", "one-pager A-share", or "target profile for [company]".
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。
Track A-share sell-side M&A and deal pipeline with milestones, deadlines, and action items. Adapted from the original deal-tracker skill for Chinese market deal processes. Triggers on "A股交易跟踪", "并购进度", "deal tracker China", "M&A pipeline A-share", or "track progress on [deal]".
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 variance commentary for A-share financial results. Adapts the original variance-commentary skill for Chinese financial statements, CAS conventions, and Chinese business terminology. Triggers on "A股业绩点评", "财报点评", "variance commentary China", "业绩分析", "variances [company]", or "commentary on [company] results".
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。
Populate A-share investment banking pitch deck templates with data from source files. Adapted from the original pitch-deck skill for Chinese companies, A-share market data, and Chinese business context. Triggers on "A股Pitch Deck", "路演PPT", "pitch deck China", "pitch deck A-share", or "fill pitch template for [company]".
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。
Three-statement financial model for A-share stocks. Adapts the standard 3-statement-model methodology for Chinese accounting standards (CAS), Chinese GAAP differences, and AkShare-sourced financials. Use instead of the original 3-statement-model skill when building integrated IS/BS/CF models for Chinese listed companies.
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。
Systematic stock screening and investment idea sourcing for A-share markets. Combines quantitative screens, thematic research, and pattern recognition to surface new long and short ideas. Adapted from the original idea-generation skill for Chinese market conventions and data sources. Triggers on "A股选股", "股票筛选", "寻找机会", "stock screen China", "A-share ideas", "find ideas for Chinese stocks", or "screen for A-share opportunities".
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。
Local SEO analysis covering Google Business Profile optimization, NAP consistency, citation health, review signals, local schema markup, location page quality, multi-location SEO, and industry-specific recommendations. Detects business type (brick-and-mortar, SAB, hybrid) and industry vertical (restaurant, healthcare, legal, home services, real estate, automotive). Use when user says "local SEO", "Google Business Profile", "GBP", "map pack", "local pack", "citations", "NAP consistency", "local rankings", "service area", "multi-location", or "local search".
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 generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' or 'ad performance optimization.' This skill covers generating ad creative at scale, iterating based on performance data, and enforcing platform character limits. For campaign strategy and targeting, see paid-ads. For landing page copy, see copywriting.
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 knowledge for Azure Lab Services development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when configuring lab plans, VM templates/schedules, VNet-integrated labs, GPU/nested virtualization, or Canvas/Teams integration, and other Azure Lab Services related development tasks. Not for Azure DevTest Labs (use azure-devtest-labs), Azure Virtual Machines (use azure-virtual-machines), Azure Virtual Desktop (use azure-virtual-desktop).
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 knowledge for Azure DevOps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing org/projects, repos, pipelines, work items, dashboards/analytics, or Azure DevOps Server deployments, and other Azure DevOps related development tasks. Not for Azure Boards (use azure-boards), Azure Pipelines (use azure-pipelines), Azure Repos (use azure-repos), Azure Test Plans (use azure-test-plans).
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 knowledge for Azure Extended Zones development including limits & quotas, security, and configuration. Use when registering subs, authoring Azure Policy, deploying Azure Firewall, CMK disk encryption, or quota requests, and other Azure Extended Zones related development tasks. Not for Azure Virtual Network (use azure-virtual-network), Azure Virtual WAN (use azure-virtual-wan), Azure Traffic Manager (use azure-traffic-manager).
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 guidance for planning and executing cloud adoption using Azure Cloud Adoption Framework. Covers strategy, planning, readiness & landing zones, adoption patterns, governance, security, operations & management, organization & teams, and adoption scenarios. Use when planning AVD, SAP, Oracle, VMware, AI/ML workloads, or designing Azure landing zones and governance, and other Azure Cloud Adoption Framework related development 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。
Conversational intake for cold email campaigns. Interviews the user about their business, ICP (Ideal Customer Profile), offer, lead magnets, and hard vs soft filters. Outputs a structured `client-profile.yaml` that every other skill in the repo reads from. Use at the very start of a new campaign or when onboarding a new business. Triggers on "onboard me", "set up my ICP", "new client", "new business intake", "help me define my ICP".
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 you need to determine audience awareness level and the correct messaging approach. Trigger on "awareness stage", "cold vs warm audience", "Schwartz", "message to market match".
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。