精选 Skills 索引（第 81 页）
按质量分排序的前 8,000 个 Skills，每个都有可收录的独立页面。需要全库 15.8 万条检索时，请使用 Skills 目录。
- zoom-meeting-sdk-ios
Zoom Meeting SDK for iOS native apps. Use when embedding Zoom meetings in iOS with default/custom UI, PKCE + SDK auth, host start with ZAK, and mobile lifecycle handling.
- zoom-meeting-sdk-macos
Zoom Meeting SDK for macOS native apps. Use when embedding Zoom meetings in macOS with default/custom UI, PKCE + SDK auth, host start/join flows, and desktop meeting feature controllers.
- zoom-meeting-sdk-react-native
Zoom Meeting SDK for React Native. Use when embedding Zoom meetings in React Native iOS/Android apps with @zoom/meetingsdk-react-native, JWT auth, join/start flows, platform setup, and native bridge troubleshooting.
- zoom-meeting-sdk-unreal
Zoom Meeting SDK for Unreal Engine wrapper integrations. Use when building Unreal projects that embed Zoom meetings with C++ and Blueprint wrappers, including wrapper-to-SDK mapping concerns.
- zoom-meeting-sdk-web
Zoom Meeting SDK for Web - Embed Zoom meeting capabilities into web applications. Two integration options: Client View (full-page, familiar Zoom UI) and Component View (embeddable, Promise-based API). Includes SharedArrayBuffer setup for H…
- zoom-meeting-sdk-web-client-view
Zoom Meeting SDK Web - Client View. Full-page Zoom meeting experience with the familiar Zoom interface. Uses ZoomMtg global singleton with callback-based API. Ideal for quick integration with minimal customization. Provides the same UI as…
- zoom-meeting-sdk-web-component-view
Zoom Meeting SDK Web - Component View. Embeddable Zoom meeting components with Promise-based API for flexible integration. Ideal for React/Vue/Angular apps and custom layouts. Uses ZoomMtgEmbedded with async/await patterns and embeddable U…
- zoom-meeting-sdk-windows
Zoom Meeting SDK for Windows - Native C++ SDK for embedding Zoom meetings into Windows desktop applications. Supports custom UI architecture with raw video/audio data, headless bots, and deep integration with meeting features. Includes SDK…
- zoom-oauth
Reference skill for Zoom authentication. Use after routing to an auth workflow when choosing app credentials, grant types, scopes, token refresh behavior, or debugging Zoom OAuth failures.
- zoom-rtms
Reference skill for Zoom RTMS. Use after routing to a live-media workflow when processing real-time audio, video, chat, transcripts, screen share, or contact-center voice streams.
- zoom-video-sdk-android
Zoom Video SDK for Android native apps. Use when building custom Android video experiences with full UI control, session tokens, raw media options, and event-driven participant state.
- zoom-video-sdk-flutter
Zoom Video SDK for Flutter. Use when building custom video session apps in Flutter with flutter_zoom_videosdk, event-driven architecture, session lifecycle handling, and mobile platform integration patterns.
- zoom-video-sdk-ios
Zoom Video SDK for iOS native apps. Use when building custom iOS video sessions with full UI control, token-based session auth, and event-driven media/participant flows.
- zoom-video-sdk-macos
Zoom Video SDK for macOS native desktop apps. Use when building custom macOS video sessions with native UI control, tokenized join, and desktop-oriented media/device workflows.
- zoom-video-sdk-react-native
Zoom Video SDK for React Native. Use when building custom mobile video session experiences with @zoom/react-native-videosdk, event listeners, helper-based APIs, and backend JWT token flows.
- zoom-video-sdk-unity
Zoom Video SDK for Unity wrapper integrations. Use when building custom Unity-based video session experiences and mapping Unity scene/UI state to Video SDK events.
- accelerated-computing-cudf
Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
- aiq-deploy
Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.
- aiq-research
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
- amc-run-sample-calibration
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
- amc-run-video-calibration
Calibrate a new dataset from pre-recorded video files via the AutoMagicCalib REST API. Use when user has local MP4s and says 'calibrate my videos', 'run AMC on these videos', or similar. For RTSP/live streams, use amc-run-rtsp-calibration…
- amc-setup-calibration-stack
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API…
- cudaq-guide
CUDA-Q onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.
- cuopt-developer
Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions.
- cuopt-install
Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from source, see cuopt-developer.
- cuopt-multi-objective-exploration
Trace and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).
- cuopt-numerical-optimization-api
LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface.
- cuopt-numerical-optimization-formulation
LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API.
- cuopt-routing-api-python
Vehicle routing (VRP, TSP, PDP) with cuOpt — Python API only. Use when the user is building or solving routing in Python.
- cuopt-server-api-python
cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API.
- cupynumeric-hdf5
Read and write large cuPyNumeric arrays to HDF5 with Legate's parallel, distributed HDF5 I/O (legate.io.hdf5: to_file, from_file, from_file_batched). Use when a developer needs to save a cuPyNumeric array to an .h5/.hdf5 file, load an HDF5…
- cupynumeric-install
Install and verify cuPyNumeric for Python — requirements, commands, verification. Source builds are out of scope.
- cupynumeric-migration-readiness
Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer clea…
- cupynumeric-parallel-data-load
Load a sharded, on-disk dataset (sharded .npy, Parquet/Arrow, raw binary, sharded HDF5, custom layouts) into a distributed cuPyNumeric ndarray via a manual partition + leaf @task launch with CPU/OMP/GPU variants. Use when no single-call lo…
- dali-dynamic-mode
DALI imperative dynamic mode (`nvidia.dali.experimental.dynamic`, ndd): use when working on ndd code or migrating pipelines; skip pipeline-only tasks.
- data-designer
Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline.
- deepstream-dev
NVIDIA DeepStream SDK development with Python pyservicemaker API. Use when building video analytics pipelines, GStreamer-based video processing, TensorRT inference integration, object detection/tracking, or Kafka/message broker integration.
- deepstream-generate-pipeline
Build DeepStream GStreamer pipelines interactively. Use when the user asks about pipelines for video/image inference, detection, tracking, or streaming — including natural phrases like 'pipeline to infer on image', 'run inference on video'…
- deepstream-import-vision-model
Use this skill to bring any vision model from HuggingFace or NVIDIA NGC into an NVIDIA DeepStream pipeline with end-to-end automation: ONNX download, SafeTensors export, TRT engine build, custom nvinfer bbox parser, multi-stream benchmark,…
- deepstream-profile-pipeline
Profile a DeepStream pipeline with Nsight Systems and derive its configs from the measurement. Use when the user asks for an efficient, performant, or profiled pipeline — or to benchmark, tune, or measure FPS.