240 件 ・ 関連度順
概要と使いどころ
GPU-optimized OCR using Surya. Use when extracting text from images/screenshots, recovering image-only content in PDFs or slides, or inspecting multilingual document layouts. Preserve source locations and report recognition gaps separately from verified text.
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。
"Design conversational AI chatbots including intent recognition, slot filling, dialogue flow, and response generation. Use this skill when the user needs to build a chatbot, design conversation flows, implement intent classification, or improve chatbot accuracy — even if they say 'build a chatbot', 'our bot doesn't understand users', 'design a FAQ bot', or 'improve our chatbot's responses'.".
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。
"Implement Named Entity Recognition to identify and classify entities in text. Use this skill when the user needs to extract people, organizations, locations, dates, or custom entities from documents — even if they say 'extract names from text', 'find companies mentioned', or 'entity extraction'.".
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 a task needs the judgment of an accountant/financial controller — closing the books on a fixed calendar, resolving a bank or account reconciliation variance, evaluating a revenue-recognition or substance-over-form question, designing or testing an internal control, or triaging a discrepancy in financial records before it reaches the auditors.
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。
Rewrite raw meeting audio transcriptions into clean, accurate meeting minutes in Traditional Chinese. Use when the user has an unprocessed audio transcription file with recognition errors and needs it cleaned up into proper meeting minutes.
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 an ASC 606 / IFRS 15 revenue recognition engine for SaaS — the five-step model (identify contract, identify performance obligations, determine transaction price, allocate to performance obligations, recognize as POs are satisfied) applied to subscription contracts.
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。
Spot patterns appearing in 3+ domains to find universal principles
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。
Creative problem-solving techniques for breaking through stuck points - includes collision-zone thinking, inversion, pattern recognition, and simplification
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。
Design the engagement model for an Experience Cloud community: reputation levels, ideation, and content contribution strategy. Triggers: 'community engagement strategy', 'gamification Experience Cloud', 'reputation levels setup', 'ideation community portal', 'member recognition program'. NOT for blocking, flagging or approving what members post — use admin/experience-cloud-moderation. NOT for measuring logins, page views or engagement after launch — use data/community-analytics-data. Also covers: the Network reputation elements that carry the ladder (enableReputation, reputationLevels/level/label/lowerThreshold, reputationPointsRules/pointsRule/eventType/points), the 16 documented reputation eventType values and their default points, ManagedTopics / ManagedTopic (Navigational vs Featured, position 0-24), NetworkMember.ReputationPoints seeding, and why FeedItem cannot carry the engagement dashboard.
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。
Consumer Goods Cloud setup: visit execution, retail execution, route planning, in-store task management, compliance checks, off-shelf detection, image recognition. NOT for territory planning and route optimization for sales reps - use integration/salesforce-maps-setup. NOT for B2B Commerce storefronts - use admin/b2b-commerce-store-setup.
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。
Configure Salesforce Billing (blng__ managed package) billing schedules, invoice plans, billing policies, and billing treatments on activated Orders. Triggers: 'billing schedule not generating invoices', 'blng__BillingSchedule__c missing after order activation', 'in-advance vs in-arrears billing', 'milestone billing', 'invoice run not picking up order products', 'evergreen billing setup', 'billing treatment configuration'. NOT for revenue schedules, GL transactions and ASC 606 - use admin/revenue-recognition-requirements. NOT for native Revenue Cloud (RLM) BillingSchedule objects - use data/revenue-cloud-data-model.
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。
Drafts filing-ready Articles of Incorporation for U.S. non-profit corporations satisfying state corporate law and the IRS organizational test under IRC § 501(c)(3). Enforces mandatory exempt-purpose language, private inurement prohibition, dissolution clause, and political activity limitations. Use when forming a new non-profit, charitable corporation, or tax-exempt entity seeking 501(c)(3) recognition.
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 stuck on approach (not debugging). Strategic unsticking via 7 non-default techniques: simplification cascades, collision-zone thinking, meta-pattern recognition, inversion, scale game, first principles, via negativa. Triggers on complexity spiraling, innovation block, recurring patterns across domains, forced-assumption solutions, scale uncertainty, told-it's-impossible, or bloated systems needing subtraction. For evidence-based root-cause debugging, use mk:sequential-thinking 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。
Apply recognition-primed decision making to agents operating under time pressure, uncertainty, and ambiguous cues. Use for situation assessment, RPD-style action selection, and decision-support design in operational settings. NOT for batch optimization, static planning with full information, or tasks where exhaustive search is cheap and harmless.
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。
Long-running design anthropologist that builds comprehensive visual databases from 500-1000 real-world examples, extracting color palettes, typography patterns, layout systems, and interaction design across any domain (portfolios, e-commerce, SaaS, adult content, technical showcases). This skill should be used when users need exhaustive design research, pattern recognition across large example sets, or systematic visual analysis for competitive positioning.
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。
Identify and counteract cognitive biases in medical decision-making through systematic error analysis and contextual algorithm application. For diagnostic reasoning, treatment decisions, and clinical judgment improvement. NOT for basic medical knowledge, technical procedures, or non-clinical healthcare domains.
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。
Build production computer vision pipelines for object detection, tracking, and video analysis. Handles drone footage, wildlife monitoring, and real-time detection. Supports YOLO, Detectron2, TensorFlow, PyTorch. Use for archaeological surveys, conservation, security. Activate on "object detection", "video analysis", "YOLO", "tracking", "drone footage". NOT for simple image filters, photo editing, or face recognition APIs.
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 methodology for eliciting, representing, and operationalizing expert cognitive skills—pattern recognition, situation assessment, mental simulation—from practitioners without requiring research training. Bridges academic rigor and practical usability.
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。
Recognize which awakening stage consciousness is navigating through. Use when diagnosing seeker development, identifying stage transitions, or recognizing readiness levels. Covers 7 stages from initial dissatisfaction through natural flow mastery.
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。
Deploy universal wisdom voices from all traditions simultaneously - Hindu, Buddhist, Taoist, Abrahamic, Indigenous, Scientific - revealing their unified recognition of consciousness navigation.
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。
Assesses patient’s knowledge of diabetic ketoacidosis prevention, recognition, and treatment. Triggered by clinician prompts such as 'Review sick-day rules and DKA signs' or 'Ensure patient knows when to seek help for hyperglycemia'.
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。
Assesses the patient’s ability to prevent, detect, and treat hypoglycemia, including recognition of symptoms, appropriate carbohydrate treatment, and use of emergency glucagon. Triggered when clinicians review the hypoglycemia action plan or check whether the patient recognizes low symptoms and treatment steps.
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。
Educates patients with primary adrenal insufficiency on increasing glucocorticoid dosage during intercurrent illness, fever (≥38°C), or physiological stress, including recognition of precipitating symptoms (e.g., fever, vomiting, trauma) and actions to prevent impending adrenal crisis. Trigger phrases: fever, intercurrent illness, stress, vomiting, inability to tolerate oral meds, need for parenteral glucocorticoid.
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。
Azure AI Text Analytics SDK for sentiment analysis, entity recognition, key phrases, language detection, PII, and healthcare NLP. Use for natural language processing on text.
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。