Comprehensive Microsoft 365 tenant administration skill for setup, configuration, user management, security policies, and organizational structure optimization for Global Administrators
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。
6,876 件 ・ 関連度順
概要と使いどころ
Comprehensive Microsoft 365 tenant administration skill for setup, configuration, user management, security policies, and organizational structure optimization for Global Administrators
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 create, generate, edit, or optimize images for marketing — blog heroes, social graphics, product mockups, profile banners, listing visuals, or brand assets. Also use when the user mentions 'AI image generation,' 'generate an image,' 'create a graphic,' 'product mockup,' 'hero image,' 'social media graphic,' 'banner image,' 'cover photo,' 'profile banner,' 'listing screenshot,' 'Flux,' 'Flux Kontext,' 'Midjourney,' 'DALL-E,' 'GPT Image,' 'ChatGPT Images,' 'Ideogram,' 'Gemini image,' 'Nano Banana,' 'Recraft,' 'Stable Diffusion,' 'Canva,' 'Figma,' 'image optimization,' 'compress images,' 'WebP,' or 'OG image.' Use this for general-purpose marketing image creation and optimization. For paid ad image creative and platform-specific ad specs, see ad-creative. For video production, see video.
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 help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'can AI read my pricing.' Use this whenever someone is figuring out what to charge, how to structure their plans, or wants to audit a pricing page (for humans and for the AI agents that shortlist tools). For in-app upgrade screens, see paywalls. For offer construction (bonuses, guarantees, value framing, naming) on services/courses/coaching/high-ticket B2B, see offers.
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 SOC 2 compliance assistant covering all five Trust Services Criteria (Security/CC, Availability/A, Confidentiality/C, Processing Integrity/PI, Privacy/P). Use this skill whenever a user mentions SOC 2, Trust Services Criteria, SOC 2 Type 1 or Type 2, audit readiness, compliance gaps, control documentation, evidence collection, vendor risk questionnaires, or anything related to AICPA service organization controls. Trigger even for adjacent topics like "we need to get audited", "a customer asked for our security report", "writing an information security policy", or "preparing for an audit". Covers gap analysis, policy writing, control documentation, audit evidence preparation, and vendor risk reviews for organizations at any maturity level — from first-time startups to seasoned compliance teams.
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 NIST Cybersecurity Framework (CSF) advisor covering CSF 2.0 and CSF 1.1. Use this skill whenever a user asks about NIST CSF, cybersecurity risk management, the six CSF functions (Govern, Identify, Protect, Detect, Respond, Recover), CSF profiles, implementation tiers, gap assessments, organizational profiles, community profiles, CSF core subcategories, informative references, or mapping to other frameworks (NIST SP 800-53, ISO 27001, CIS Controls, COBIT). Also trigger for questions like "how do I implement NIST CSF?", "what does CSF 2.0 change?", "help me build a CSF profile", "how do I assess my cybersecurity posture?", or any request involving organizational cybersecurity risk strategy or framework alignment.
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。
Analyze any OFAC or OFSI enforcement action — by URL, pasted text, or uploaded document — and produce a structured root cause analysis as a formatted Excel (.xlsx) spreadsheet. Use this skill whenever a user names, links to, pastes, or uploads an OFAC or OFSI enforcement action and asks for any of the following: root cause analysis, compliance gaps, what went wrong, lessons learned, organizational self-assessment, or remediation planning. Also trigger when a user asks "analyze this enforcement action", "what were the root causes", "turn this into a checklist", or "how do I make sure this doesn't happen to us". Outputs a single-sheet .xlsx table with six columns: Root Cause | What Went Wrong | How It Went Wrong | What Could Have Stopped It | Is my organization immune to this? (Yes/No/Partial) | Notes.
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 FedRAMP certification and compliance under CR26 (FedRAMP Consolidated Rules for 2026). Use this skill whenever a user asks about FedRAMP authorization, ATO (Authority to Operate), cloud security for federal government, NIST SP 800-53 controls, CSP compliance, or any of the core FedRAMP document types: SSP, SAP, SAR, POA&M, CIS/CRM workbooks. Also trigger for questions about FedRAMP Certification Classes (A, B, C, D — new baseline labels: A = pilot/transitional, B = LI-SaaS/Low, C = Moderate, D = High, per NTC-0004), FedRAMP 20x (now the primary authorization pathway), OSCAL mandate (September 2026), 3PAO assessments, continuous monitoring (ConMon), gap assessments, system boundary definition, or architecture reviews for federal cloud. FedRAMP Ready retires July 28, 2026. When in doubt, use this skill — it covers the full FedRAMP lifecycle from readiness through continuous monitoring.
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。
Draft, adapt, and review contracts and clauses aligned with The Chancery Lane Project's methodology for reducing carbon emissions through legal agreements. Use when Claude needs to: (1) Draft new climate-aligned clauses (e.g., net zero commitments, carbon accounting, supply chain decarbonization), (2) Adapt or modify existing contracts to incorporate climate objectives, (3) Review and analyze clauses for alignment with climate goals and decarbonization strategies, (4) Provide guidance on The Chancery Lane Project's house style and drafting methodology for climate-conscious legal 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。
Expert blueprint for data-oriented design using Resource/RefCounted classes (item databases, character stats, reusable data structures). Covers typed arrays, serialization, nested resources, and resource caching. Use when implementing data systems OR inventory/stats/dialogue databases. Keywords Resource, RefCounted, ItemData, CharacterStats, database, serialization, @export, typed arrays.
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 blueprint for performance profiling and optimization (frame drops, memory leaks, draw calls) using Godot Profiler, object pooling, visibility culling, and bottleneck identification. Use when diagnosing lag, optimizing for target FPS, or reducing memory usage. Keywords profiling, Godot Profiler, bottleneck, object pooling, VisibleOnScreenNotifier, draw calls, MultiMesh.
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 blueprint for Godot 4 project organization (feature-based folders, naming conventions, version control). Enforces snake_case files, PascalCase nodes, %SceneUniqueNames, and .gitignore best practices. Use when starting new projects or refactoring structure. Keywords project organization, naming conventions, snake_case, PascalCase, feature-based, .gitignore, .gdignore.
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 blueprint for save/load systems using JSON/binary serialization, PERSIST group pattern, versioning, and migration. Covers player progress, settings, game state persistence, and error recovery. Use when implementing save systems OR data persistence. Keywords save, load, JSON, FileAccess, user://, serialization, version migration, PERSIST group.
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 branching dialogue systems including dialogue graphs (Resource-based), character portraits, player choices, conditional dialogue (flags/quests), typewriter effects, localization support, and voice acting integration. Use for narrative games, RPGs, or visual novels. Trigger keywords: DialogueLine, DialogueChoice, DialogueGraph, dialogue_manager, typewriter_effect, branching_dialogue, dialogue_flags, localization, voice_acting.
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 porting desktop games to mobile including touch control schemes (virtual joystick, gesture detection), UI scaling for small screens, performance optimization for mobile GPUs, battery life management, and platform-specific features. Use when creating mobile ports or cross-platform mobile builds. Trigger keywords: TouchScreenButton, virtual_joystick, gesture_detector, InputEventScreenTouch, InputEventScreenDrag, mobile_optimization, battery_saving, adaptive_performance, MOBILE_ENABLED.
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 blueprint for performance profiling and optimization (frame drops, memory leaks, draw calls) using Godot Profiler, object pooling, visibility culling, and bottleneck identification. Use when diagnosing lag, optimizing for target FPS, or reducing memory usage. Keywords profiling, Godot Profiler, bottleneck, object pooling, VisibleOnScreenNotifier, draw calls, MultiMesh.
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 blueprint for save/load systems using JSON/binary serialization, PERSIST group pattern, versioning, and migration. Covers player progress, settings, game state persistence, and error recovery. Use when implementing save systems OR data persistence. Keywords save, load, JSON, FileAccess, user://, serialization, version migration, PERSIST group.
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 blueprint for Godot 4 project organization (feature-based folders, naming conventions, version control). Enforces snake_case files, PascalCase nodes, %SceneUniqueNames, and .gitignore best practices. Use when starting new projects or refactoring structure. Keywords project organization, naming conventions, snake_case, PascalCase, feature-based, .gitignore, .gdignore.
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 blueprint for data-oriented design using Resource/RefCounted classes (item databases, character stats, reusable data structures). Covers typed arrays, serialization, nested resources, and resource caching. Use when implementing data systems OR inventory/stats/dialogue databases. Keywords Resource, RefCounted, ItemData, CharacterStats, database, serialization, @export, typed arrays.
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 branching dialogue systems including dialogue graphs (Resource-based), character portraits, player choices, conditional dialogue (flags/quests), typewriter effects, localization support, and voice acting integration. Use for narrative games, RPGs, or visual novels. Trigger keywords: DialogueLine, DialogueChoice, DialogueGraph, dialogue_manager, typewriter_effect, branching_dialogue, dialogue_flags, localization, voice_acting.
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 porting desktop games to mobile including touch control schemes (virtual joystick, gesture detection), UI scaling for small screens, performance optimization for mobile GPUs, battery life management, and platform-specific features. Use when creating mobile ports or cross-platform mobile builds. Trigger keywords: TouchScreenButton, virtual_joystick, gesture_detector, InputEventScreenTouch, InputEventScreenDrag, mobile_optimization, battery_saving, adaptive_performance, MOBILE_ENABLED.
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。
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
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。
Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
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。
Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization 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。
Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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。