“tip”的搜索结果

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

中文简介正在准备中。当前显示原文说明。

Load this skill whenever the project contains tooltip components, hover- triggered informational popups, title attribute tooltips, or any content revealed on hover or focus. Under no circumstances create tooltips that are only triggered by hover without keyboard equivalent access. Absolutely always ensure tooltips are dismissible, persistent enough to read, and not the sole source of essential information.

中文简介正在准备中。当前显示原文说明。

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

中文简介正在准备中。当前显示原文说明。

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

中文简介正在准备中。当前显示原文说明。

Implements multiplicity control for confirmatory clinical trials using graphical procedures (Bretz-Maurer-Hommel), gatekeeping (parallel, serial, mixed), Hochberg/Hommel/Holm with PRDS, and the closed-testing principle (Marcus-Peritz-Gabriel; Goeman 2021 admissibility). Covers FDA Multiple Endpoints Final Guidance (October 2022), graphical procedures via R gMCP, primary + key-secondary + subgroup hierarchies, and FWER vs FDR distinction. Use when designing the multiplicity strategy for confirmatory trials with multiple primary or key secondary endpoints.

中文简介正在准备中。当前显示原文说明。

Agent fallback for C_MultiplayRules_vtable (auto-generated, category: func). Locate C_MultiplayRules_vtable in the CS2 client module via IDA Pro MCP and emit a fresh, minimal-unique artifact. The deterministic preprocessor could not resolve this symbol on the current gamever - your job is the re-sign. Trigger: C_MultiplayRules_vtable, C_MultiplayRules_vtable

中文简介正在准备中。当前显示原文说明。

为Android和KMP项目梳理模块结构与依赖关系，将业务逻辑、界面和数据获取分开设计，并通过实现示例明确各层职责。

• 规划Android或KMP项目结构
• 从界面代码中分离业务逻辑
• 设计本地与服务器数据获取方式

Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.

中文简介正在准备中。当前显示英语简介。

• Assessing risky permissions identified in BloodHound
• Validating account takeover without resetting a password
• Generating directory change records during security exercises

Adapt machine learning training to run across multiple GPUs or machines with Ray Train. Covers changes to existing code, comparing training settings with Ray Tune, and saving checkpoints so training can resume after failures.

中文简介正在准备中。当前显示英语简介。

• Adapting existing PyTorch code for multiple GPUs
• Training HuggingFace models across multiple machines
• Comparing learning rates and batch sizes with Ray Tune

Helps adapt machine learning training to multiple GPUs and machines with Ray Train. Covers resource allocation, recovery from saved training states, and Ray Tune searches that compare settings such as learning rate and batch size.

中文简介正在准备中。当前显示英语简介。

• Adapt existing PyTorch training to multiple GPUs
• Run HuggingFace training across multiple machines
• Compare learning rates and batch sizes with Ray Tune

Build game systems in Unity or Unreal Engine, including physics, AI, and multiplayer networking. The skill guides architecture, implementation, profiling, and testing to work toward frame rate targets and reduce memory use.

中文简介正在准备中。当前显示英语简介。

• Implementing game mechanics in Unity or Unreal Engine
• Reducing frame drops and memory use
• Building multiplayer networking with lag compensation

Coordinate multiple AI agents by assigning tasks, tracking dependencies, exchanging messages, and monitoring progress. Separate Git working directories help organize parallel changes, while context checks and snapshots support handoffs and recovery.

中文简介正在准备中。当前显示英语简介。

• Split feature development and testing between agents
• Track task dependencies and team progress
• Check overlapping changes before a handoff

Create and customize MATLAB charts and plots. Plot types (line, scatter, bar, histogram, heatmap, surface), axes configuration, annotations, data tips, interactive plots, animation, multiple axes with tiledlayout, colororder, and performance optimization. Works for standalone figures, Live Scripts, and uifigure apps. Use when plotting data, customizing axes, adding annotations or interactivity, animating charts, or arranging multiple axes. Triggers: plot, chart, graph, axes, uiaxes, annotation, data tips, animation, tiledlayout, colororder, heatmap, scatter, figure, visualization, export.

中文简介正在准备中。当前显示原文说明。

Generate TipKit infrastructure with inline/popover tips, rules, display frequency, and testing utilities. Use when adding contextual tips or feature discovery to an iOS/macOS app.

中文简介正在准备中。当前显示原文说明。

Helps coding agents integrate and work with the Tiptap rich text editor. Use when building or modifying a rich text editor with Tiptap, installing Tiptap extensions, or implementing features like collaboration, comments, AI, or document conversion.

中文简介正在准备中。当前显示原文说明。

Expertise in real-time multiplayer networking, lag compensation, and authoritative server architectureUse when "multiplayer game, netcode, client-server game, P2P networking, lag compensation, rollback networking, game server, matchmaking, lobby system, player synchronization, state replication, dedicated server, authoritative server, tick rate, network prediction, interpolation, extrapolation, GGPO, lockstep, real-time multiplayer, networking, multiplayer, gamedev, realtime, client-server, p2p, netcode, synchronization, lag-compensation, matchmaking" mentioned.

中文简介正在准备中。当前显示原文说明。

Create or edit Czech club-member tips in src/jg/coop/data/tips for Discord synchronization. Use for tip content, filenames, headings, emoji identity, symbolic Discord references, voice, or parser compatibility.

中文简介正在准备中。当前显示原文说明。

"Apply case study research design (Yin) to investigate how and why questions within real-life contexts using single or multiple case designs and triangulation. Use this skill when the user needs to choose between single and multiple case designs, apply holistic versus embedded units of analysis, triangulate evidence from multiple sources, or when they ask 'how should I structure a case study', 'single or multiple cases', or 'how do I ensure validity in case research'.".

中文简介正在准备中。当前显示原文说明。

Unity 6 multiplayer and networking guide. Use when building multiplayer games, working with Netcode for GameObjects, NetworkManager, NetworkObject, NetworkBehaviour, RPCs (ServerRpc, ClientRpc), NetworkVariables, or Unity multiplayer services (Relay, Lobby). Covers client-server architecture, state synchronization, and scene management. Based on Unity 6.3 LTS documentation.

中文简介正在准备中。当前显示原文说明。

Correlate events across multiple log files from different sources, systems, or time periods. Build unified timelines, identify causal relationships between events, and highlight anomalies that span multiple data sources. Supports timezone normalization and gap detection. Use when analyzing logs from multiple systems (frontend, backend, database, infrastructure), investigating distributed system failures, or building event timelines across services. Triggers: "correlate these logs", "build timeline from multiple logs", "cross-system analysis", "find related events across logs", "multi-source log analysis", "distributed trace analysis"

中文简介正在准备中。当前显示原文说明。

Kotlin Multiplatform (KMP) / Compose Multiplatform (JetBrains, Kotlin) の公式リファレンス。 expect/actual, source set hierarchy, Multiplatform Gradle DSL, org.jetbrains.compose, Compose Resources (Res), Compose for iOS / Compose Desktop (Window, Tray, MenuBar, nativeDistributions) / Web, iOS 統合 (SwiftPM export, CocoaPods), Navigation / ViewModel / Lifecycle, Compose Hot Reload, Kotlin Toolchain, CI (GitHub Actions / TeamCity), Maven Central / npm 公開, AGP 9 移行, 互換性表。

中文简介正在准备中。当前显示原文说明。

为多个 AI 智能体分配负责范围和完成条件，用看板共享进度与阻碍。通过分支或独立工作目录分开编辑，并在测试、差异审查和风险检查后整合成果。

• 向多个 AI 智能体分配并行任务
• 跨会话共享进度与阻碍
• 通过分支或 worktree 分开编辑

帮助使用Compose为Android、iOS、Desktop和Web构建共享界面，整理状态与操作事件，实现导航和主题，并改善重组与列表渲染性能。

• 在多个平台共享界面
• 整理界面状态与操作事件
• 实现页面和对话框导航

以少量修改让现有PyTorch训练代码适用于多GPU或多台机器，指导混合精度、节省内存的DeepSpeed与FSDP配置，以及训练启动方法。

• 将单GPU训练迁移至多GPU
• 配置混合精度训练
• 通过DeepSpeed或FSDP节省内存