102 件 ・ 関連度順
概要と使いどころ
Orchestrate an end-to-end data analysis or machine learning project from decision framing through reproducible handoff. Use when a request spans multiple lifecycle stages or an ambiguous modeling request must become a decision-ready result; use narrower audit or experiment-design skills for isolated reviews.
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 datasets, joins, labels, and ground truth before analysis or modeling. Use when data meaning, row grain, time semantics, source-of-truth reliability, or label construction may invalidate conclusions; not for general model evaluation after the evidence base is already trusted.
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。
Validate trained models and analytical claims against their intended decision, independent evidence, and human-reviewed ground truth. Use when reviewing model performance, analysis conclusions, launch claims, or evaluation reports; use failure diagnosis instead when the main task is locating a known defect.
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Package completed data analysis and ML work so an independent recipient can reproduce the claimed results, verify artifact lineage, and operate the handoff within its stated scope. Use when finalizing a project, study, model package, or review bundle; not for deploying to a live system.
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Quantiza LLMs para 8-bit ou 4-bit com redução de memória de 50-75% e perda mínima de acurácia. Use quando a memória GPU é limitada, precisa ajustar modelos maiores ou quer inferência mais rápida. Suporta formatos INT8, NF4, FP4, treinamento QLoRA e otimizadores 8-bit. Funciona com HuggingFace Transformers.
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。
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
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Add, change, or debug external API integrations, vendor SDK adapters, and bridges to legacy business workflows. Use when an Action or domain service needs an outer technical dependency.
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Create or refactor business calculations and rules spanning multiple domain objects when no single entity or value object naturally owns the behavior. Use when assessing a growing service class.
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。
Test or debug application use cases through their public Action API, including persistence, authorization failures, atomic rollback, and post-commit reactions. Use when adding regression tests for business operations.
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。
Test or fix domain rules, state transitions, value objects, and domain services directly. Use for business-rule regression tests, rejected transitions, and model behavior without HTTP.
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, modify, or refactor application use cases into Laravel-native DDD Actions. Use for business operations such as placing or cancelling orders, extracting controller orchestration, and fixing use-case behavior.
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Create or change structured input for application use cases, including extracting HTTP request data for Actions invoked from controllers, jobs, or commands. Avoid DTOs for trivial scalar input.
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Implement or refactor Laravel controllers, commands, jobs, listeners, and scheduled tasks. Use for endpoints, authentication, request validation, simple reads, or extracting business orchestration into Actions.
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, introduce, or refactor persistence abstractions when direct Eloquent is insufficient. Use for repository requests, complex aggregate reconstruction, or multiple persistence implementations; reject CRUD wrappers without a concrete benefit.
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, modify, or debug business events and their follow-up reactions, including order cancellation events, queued listeners, transaction timing, and rollback behavior.
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, extend, or fix Eloquent business models and their state transitions. Use when moving business rules out of controllers or Actions, or explicitly migrating a model into a DDD capability.
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Create or change immutable business values with meaningful invariants, equality, or behavior, such as order numbers and money. Use when primitive values obscure domain rules; avoid wrapping every scalar.
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Resolve complex or high-impact problems when the cause, solution path, requirements, or proof boundary is genuinely uncertain. Use when work needs evidence-led diagnosis, consequential design or implementation, or a completion audit; do not trigger merely because work has multiple steps, or for simple facts, fully specified routine changes, or pure creative generation.
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 Resource Manager SDK for Arize AI Observability and Evaluation (.NET).
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 working with Bigpanda — bigPanda AIOps platform management covering event correlation, root cause analysis, incident management, alert enrichment, topology-based correlation, environment management, and analytics. Use when configuring BigPanda correlation patterns, investigating correlated incidents, tuning noise reduction, or analyzing alert topology and root cause indicators.
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This skill should be used when the user asks how to "use VibeTags", "add VibeTags annotations", "set up AI guardrails", "protect code from AI", "configure AI platforms", asks about @AILocked, @AIContext, @AIDraft, @AIAudit, @AIIgnore, @AIPrivacy, @AICore, @AIPerformance, @AIContract, @AITestDriven, @AIThreadSafe, @AIImmutable, @AIDeprecated, @AIObservability, @AIRegulation, @AIArchitecture, @AILegacyBridge, @AIStrictClasspath, @AIInternationalized, @AIPublicAPI, @AISchemaSafe, @AIStrictExceptions, @AIStrictTypes, @AIParallelTests, @AIIdempotent, @AIFeatureFlag, @AISecure, @AICallersOnly, @AISandboxOnly, @AIMemoryBudget, @AIPure, @AIDomainModel, @AIExtensible, @AIInputSanitized, @AISecureLogging, @AIExplain, @AIPrototype, @AISunset, @AITemporary annotations, or wants to control how AI tools interact with Java code.
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用户咨询腾讯云产品资源、AWS、阿里云等多云资源时，查看智能顾问架构图、架构目录、架构详情、架构评估结果、绘制架构图、开通智能顾问时、AI智能巡检、AI容量监测、AI混沌演练、AI云诊断、主动预警、架构健康度、云运维问答、云资源查询、云成本优化、安全合规、云资源盘点、闲置资源检查、云产品最佳实践等AIOps、ChatOps、CloudOps操作时使用。
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 Resource Manager SDK for Arize AI Observability and Evaluation (.NET).
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。
Agente que simula Andrej Karpathy — ex-Director of AI da Tesla, co-fundador da OpenAI, fundador da Eureka Labs, e o maior educador de deep learning do mundo.
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。