claudemods

来源nvidia/skills

nvidia/skills 已索引

Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end.

查看上游仓库

已索引 索引里有这个仓库的包记录。包数量是历史登记记录,不代表这些包现在仍可用。

仓库

规范名称
NVIDIA/skills
GitHub 仓库 ID
1167034425
包记录
394 (历史登记记录,不代表现在仍可用)

发现与队列

首个记录来源
marketplace:anthropics/claude-plugins-official
发现于
队列状态
ok
记录的错误次数
0
最近完成的处理
下次检查资格
起具备资格

首个记录来源是队列第一次保存的来源,不是完整的发现历史。错误次数在处理以错误状态结束时增加,成功处理后清零,不是全部尝试次数。「最近完成的处理」是结束时间,不是开始时间。

资格按 计算。它不是排期:采集器每次运行只处理有限数量的来源,具备资格也不保证何时检查。

最近保存的扫描

仓库元数据读取于
扫描状态
complete
扫描保存于
识别器版本
2
续扫记录
没有

扫描记录与队列状态分开:队列状态说明处理进度,扫描记录说明最近一次保存了什么。有续扫记录只表示存有未完成的状态,没有剩余数量。

源文件证据覆盖

已存储的包版本在这个仓库中引用的固定源文件的原始计数。它反映已记录了什么,不代表仓库有多完整。

范围与限制

统计所有已存储版本(来自任何包)中指向本仓库规范名称的不同固定文件链接(仓库、提交、路径)。本仓库所拥有的包的文件,只有被某个版本在这里链接时才会计入。不合并别名,也不会根据当前名称推测历史。

「已知」表示已记录普通文件身份,不表示整个目录或包已被覆盖。不是有效固定文件 URL 的链接不计入。

引用了 395 个固定源文件

  • 395 已知
  • 0 提交中不存在
  • 0 文件列表截断
  • 0 不受支持
  • 0 尚无记录
  • 0 读取失败

按仓库、提交和路径去重;同一路径出现在两个提交中,按两个文件身份计数。不是组件组数。

读取失败的提交 0

尚无记录的文件没有对应的提交读取失败记录。

关联的包 394

按仓库的已验证身份关联。数量是历史登记记录,不是当前可用性。

第 1–20 条,共 394 条结果

  • accelerated-computing-cudf技能

    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.

  • amc-run-rtsp-calibration技能

    Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.

  • amc-run-sample-calibration技能

    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技能

    Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.

  • amc-setup-calibration-stack技能

    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技能

    Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance.

  • cudaq-importing技能

    Use when porting circuits from another framework (e.g. Qiskit) into CUDA-Q kernels while preserving the source algorithm and validation fidelity.

  • cuopt-developer技能

    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技能

    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技能

    Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint).

  • cuopt-numerical-optimization-api技能

    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技能

    LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API.

  • cuopt-routing-api-python技能

    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技能

    cuOpt REST server — start server, endpoints, Python/curl client examples. Use when the user is deploying or calling the REST API.

  • dali-dynamic-mode技能

    DALI imperative dynamic mode (`nvidia.dali.experimental.dynamic`, ndd): use when working on ndd code or migrating pipelines; skip pipeline-only tasks.

  • data-designer技能

    Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline.

  • deepstream-dev技能

    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插件

    Build DeepStream GStreamer pipelines interactively. Collects input source, inference, tracker, and output preferences, then assembles a ready-to-run gst-launch-1.0 pipeline using BM25 retrieval over 270+ verified pipelines (zero external d…

  • deepstream-import-vision-model技能

    Use this skill to bring a supported object-detection 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…

  • deepstream-profile-pipeline技能

    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.

已保存的扫描说明 0

没有保存额外的扫描说明。

记录的别名 0

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没有记录到指向这个仓库的别名。

不支持的市场条目 0

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