504 件 ・ 関連度順
概要と使いどころ
Expand workflow HDF5 demonstrations with action jitter, optionally scoped to node segments. Use for synthetic variants; do not use to collect data, alter state directly, or generate new images.
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。
Run the maintained workflow data-to-policy pipeline from recording through checkpoint validation. Use for full end-to-end requests; do not use for one individual stage.
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。
Fine-tune a manifest-backed GR00T or openpi remote Task on compatible LeRobot data. Use for training; do not use for inference-only Tasks or checkpoint rollout.
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。
Replay a workflow HDF5 episode through its original Scene. Use for visual trajectory and recording verification; do not use for policy evaluation or LeRobot 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。
Grade or filter workflow HDF5 episodes with an OpenAI-compatible vision model. Use for visual success labels; do not use for replay, policy evaluation, or recordings without frames.
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。
Help after a purchase or booking, covering the status of an order or delivery whether or not the customer names it, returns, refunds, exchanges, and cancellations, an item that arrived damaged, incomplete, or late, and questions about the store's terms or a membership. Not needed for finding, comparing, or choosing something new.
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。
Planning a coordinated set of items toward a goal, an event, a trip, or a project, where the request only comes together as several purchases with a structure between them, and later changes to a plan you have presented. Not needed when the customer wants a single item, however carefully chosen.
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。
Carefully curated, modern minimal style with elegant serif typography and understated, sophisticated palettes.
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. Triggers: "text analytics", "sentiment analysis", "entity recognition", "key phrase", "PII detection", "TextAnalyticsClient".
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 the user asks to "set up conversion values so tROAS optimizes profit not orders", "map margin onto my purchase value", "build value rules for lead / phone / signup conversions", or "stop bidding to revenue when I care about profit"; defines and QAs the conversion VALUE model — per-conversion values, margin/net-value adjustment, static-vs-dynamic value rules, proxy values for non-revenue actions, and a value-vs-count sanity check — as a value-model spec plus a pre-launch value QA sheet. Not for whether the tag fires or UTMs are clean — use conversion-signal-qa; not for cross-platform double-count de-dup — use attribution-reconciler; not for scoring R1/R2 — that is a scored veto in ad-account-auditor. 付费广告转化价值建模/利润出价/价值规则QA
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 a reversible Abridge tenant, care-setting, note-template, or EHR workflow change from authoritative release evidence. Use when migrating an Abridge implementation. Trigger with "plan the Abridge migration".
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。
Translate skills from one industry to another, identify transferable skills
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Prepare and validate research-only clinical decision-support evaluation, evidence-profile, cohort, survival, biomarker/model, privacy, and governance artifacts. Use for aggregate or synthetic research documentation and traceability—not patient care or live clinical operation.
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Guided journey from a working-but-untested vibe-coded prototype to a production-ready product with tests, clean structure, a business-rules boundary, and resilience at scale. Orchestrates nine skills phase by phase - working-with-legacy-code, clean-code, refactoring-patterns, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, system-design, ddia-systems - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, IMPROVE-CODE-QUALITY-PLAN.md) so the journey resumes across sessions. Use when the user wants to harden an AI-generated prototype, add tests before refactoring, make code safe to change, or says 'this works on my machine but I am scared to touch it'. For an aged codebase, remove-technical-debt; for greenfield structure, design-code-architecture; for a product and UX pass, improve-app; to optimize speed and structure, architecture-optimization. For one framework in isolation, invoke that skill directly.
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 medical referral letters with patient summary, reason for referral, key findings, and requested next steps; use when transferring care or communicating with another clinician or department.
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。
Clinical-grade PII/PHI detection and de-identification for healthcare text data. Scans all 18 HIPAA identifier categories with confidence scoring, generates audit logs, supports custom regex patterns, and produces de-identified output while preserving document structure.
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 drafting patient discharge summaries, creating personalized discharge instructions, simulating post-discharge outcomes, reducing hospital readmissions, or optimizing care transitions. Generates AI-enhanced discharge documentation with digital twin predictions for improved patient safety.
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。
Designs a structured real-world evidence study using EHR, claims, or registry data, with explicit handling of time zero, eligibility windows, exposure definitions, outcome windows, censoring, confounding control, and target-trial-emulation logic. Use this skill when the user needs study-type design and protocol framing for an observational clinical study based on routine-care data. Do not invent database fields, follow-up completeness, linkage, coding validity, or causal identifiability.
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Extracts concrete unmet clinical needs from guidelines, reviews, real-world studies, and clinical-practice evidence. Use this skill when a user wants to turn broad medical research value into specific clinical pain points such as weak early detection, poor risk stratification, treatment-response heterogeneity, monitoring gaps, diagnostic delay, undertreatment, overtreatment, or implementation failure. Always ground unmet-need claims in retrieved evidence and distinguish true care gaps from generic statements of importance.
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 medical AI agents for clinical decision support, medical record summarization, diagnostic assistance, and healthcare workflow automation.
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 clinical laboratory data harmonization for multi-source healthcare analytics. Convert between US conventional and SI units, standardize numeric formats, and clean data quality issues. This skill should be used when you need to harmonize lab values from different sources, convert units for clinical analysis, fix formatting inconsistencies (scientific notation, decimal separators, whitespace), or prepare lab panels for research.
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 Thinking method coaching knowledge across all nine methods including per-method techniques, deep expertise, and industry context (energy, financial services, healthcare, manufacturing, nonprofit and social impact, pharmaceuticals and life sciences, professional services, public sector, retail and CPG)
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。
Interview someone about their working life and turn the answers into a master CV inventory: every role, project and achievement with real numbers, before any CV is tailored. Use when asked to build my master CV, get my experience down properly, I don't know what to put on my CV, or as the first step before a tailored CV. Produces a structured inventory of roles, achievements in a fixed shape with evidence and numbers, skills with proof, and a list of gaps to fill. Never invents a number.
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。
Check whether a raise, more hours, or a new job could cost you more in lost benefits than you gain — the 'benefits cliff' — before you accept it. Use when asked will a raise hurt my benefits, benefits cliff, if I make more will I lose my food stamps or medicaid, or should I take more hours. Produces a plain map of which benefits phase out at what income (and which cut off suddenly vs. taper), a rough read on whether a specific income change helps or hurts net, the ones with hard cliffs to watch (childcare, Medicaid, housing), the moves that soften a cliff, and where to get a real benefits screening. Not financial/benefits advice; points to a benefits counselor.
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。