fandhe-ai/agent-reference-skills

nvidia-cuda

NVIDIA CUDA GPU 並列コンピューティングリファレンス。 CUDA C++ / CUDA Python, kernel, nvcc, Unified Memory, CUDA Graphs, Cooperative Groups, Driver API, マルチ GPU。 PTX ISA 命令セット, state space, MMA 命令。 Blackwell チューニング, Streaming Multiprocessor, NVLink。 CUTLASS / CuTe DSL / CuTe…

View source

How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/fandhe-ai/agent-reference-skills --skill nvidia-cuda

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

nvidia-cuda

NVIDIA CUDA — GPU 上で汎用並列計算を行うためのプログラミングモデル・ツールチェーン・ライブラリ群。 CUDA C++/Python によるカーネル記述、PTX ISA 命令セット、Blackwell アーキテクチャ向けチューニング、 CUTLASS/CuTe による高性能 GEMM 実装をカバーする。

ディレクトリ構成

text
skills/nvidia-cuda/
  SKILL.md
  references/
    programming-model/
      README.md
      introduction.md
      programming-model.md
      cuda-platform.md
      intro-to-cuda-cpp.md
      intro-to-cuda-python.md
      writing-cuda-kernels.md
      writing-tile-kernels.md
      asynchronous-execution.md
      understanding-memory.md
      nvcc.md
    advanced/
      README.md
      core/
        README.md
        advanced-host-programming.md
        advanced-kernel-programming.md
        driver-api.md
        multi-gpu-systems.md
        feature-survey.md
      features/
        README.md
        unified-memory.md
        cuda-graphs.md
        stream-ordered-memory-allocation.md
        cooperative-groups.md
        programmatic-dependent-launch.md
        green-contexts.md
        lazy-loading.md
        error-log-management.md
        async-barriers.md
        pipelines.md
        async-copies.md
        cluster-launch-control.md
        l2-cache-control.md
        memory-sync-domains.md
        inter-process-communication.md
        virtual-memory-management.md
        extended-gpu-memory.md
        dynamic-parallelism.md
        graphics-interop.md
        driver-entry-point-access.md
      appendices/
        README.md
        compute-capabilities.md
        environment-variables.md
        cpp-language-support.md
        cpp-language-extensions.md
        mathematical-functions.md
        device-callable-apis.md
        cuda-cpp-memory-model.md
        cuda-cpp-execution-model.md
    ptx-isa/
      README.md
      introduction.md
      programming-model.md
      machine-model.md
      syntax.md
      state-spaces-types-variables.md
      instruction-operands.md
      abi.md
      memory-consistency-model.md
      instruction-set-overview.md
      instructions-arithmetic.md
      instructions-comparison-logic.md
      instructions-data-movement.md
      instructions-texture-surface.md
      instructions-control-flow.md
      instructions-sync-communication.md
      instructions-matrix-multiply.md
      instructions-video-misc.md
      special-registers.md
      directives.md
      pragma-strings.md
      release-notes.md
    blackwell-tuning/
      README.md
      architecture.md
      best-practices.md
      streaming-multiprocessor.md
      memory-system.md
      nvlink.md
    cutlass/
      README.md
      cute-dsl/
        README.md
        overview.md
        functionality.md
        quick-start.md
        cute-dsl.md
        dsl-introduction.md
        dsl-code-generation.md
        dsl-control-flow.md
        dsl-jit-arg-generation.md
        dsl-dynamic-layout.md
        dsl-struct-types.md
        dsl-jit-caching.md
        dsl-jit-compilation-options.md
        dsl-types.md
        framework-integration.md
        debugging.md
        iket-profiling.md
        autotuning-gemm.md
        compile-with-tvm-ffi.md
        dsl-ahead-of-time-compilation.md
        naming-conventions.md
        deprecation-policy.md
        mma-intro.md
        mma-wmma-programming.md
        mma-wgmma-programming.md
        mma-tcgen05-programming.md
        limitations.md
        faqs.md
        api-overview.md
        api-cute.md
        api-cute-arch.md
        api-cute-runtime.md
        api-cute-nvgpu.md
        api-cute-nvgpu-common.md
        api-cute-nvgpu-warp.md
        api-cute-nvgpu-warpgroup.md
        api-cute-nvgpu-cpasync.md
        api-cute-nvgpu-tcgen05.md
        api-pipeline.md
        api-utils.md
        api-utils-sm90.md
        api-utils-sm100.md
      operator-api/
        README.md
        overview.md
        tutorials.md
        tutorial-000-gemm.md
        tutorial-001-gemm-fused-epilogue.md
        tutorial-002-bring-your-own-kernel.md
        tutorial-003-host-latency-best-practices.md
        tutorial-004-fake-tensors.md
        tutorial-005-grouped-gemm-contiguous-offset.md
        tutorial-006-block-scaled-gemm.md
        api-reference.md
        api-operator.md
        api-arguments.md
        api-discovery.md
        api-metadata.md
        api-misc.md
      cpp/
        README.md
        overview.md
        getting-started.md
        quickstart.md
        ide-setup.md
        build.md
        build-windows-visual-studio.md
        build-clang-host-compiler.md
        functionality.md
        terminology.md
        fundamental-types.md
        programming-guidelines.md
        gemm-heuristics.md
        efficient-gemm.md
        pipeline.md
        profiler.md
        gemm-performance-measurement.md
        dependent-kernel-launch.md
        blackwell.md
        blackwell-sm100-gemm.md
        blackwell-cluster-launch-control.md
        code-organization.md
        cute.md
        cute-quickstart.md
        cute-layout.md
        cute-layout-algebra.md
        cute-tensor.md
        cute-algorithms.md
        cute-mma-atom.md
        cute-gemm-tutorial.md
        cute-predication.md
        cute-tma-tensors.md
        cutlass-3x.md
        cutlass-3x-design.md
        cutlass-3x-backwards-compatibility.md
        gemm-api-3x.md
        cutlass-2x.md
        layout-2x.md
        gemm-api-2x.md
        tile-iterator-concept.md
        utilities.md
        grouped-scheduler.md
        implicit-gemm-convolution.md
  samples/
    README.md
    async-copy-pipeline.md
    cooperative-groups-reduction.md
    cuda-graph-explicit-nodes.md
    cuda-graph-stream-capture.md
    cute-dsl-gemm.md
    cutlass-cpp-device-gemm.md
    cutlass-operator-api-gemm.md
    explicit-memory-transfer.md
    multi-gpu-peer-to-peer.md
    shared-memory-tiled-matmul.md
    stream-ordered-allocation.md
    stream-overlap.md
    tile-kernel-vector-add.md
    unified-memory.md
    vector-add-kernel.md
  scripts/
    README.md
    install.md
    nvcc-build.md
    binary-utilities.md
    sanitize.md
    debug.md
    nsight-systems.md
    nsight-compute.md
    gpu-query.md
    cutlass-build.md

探索手順

タスクからカテゴリを引き、カテゴリの README.md で目的のページを特定する:

  1. 下記マッピング表でタスクに対応するカテゴリを探す
  2. そのカテゴリの references/{category}/README.md(advanced/ cutlass/ はサブディレクトリの README.md)を参照して目的のページを特定する
  3. 該当ページの .md を Read して詳細を確認する

GB10 Grace Blackwell 実機のハードウェア仕様・DGX OS・PXE/fleet 運用・playbook 起動手順は dgx-spark スキル、 リモート接続管理・VS Code 起動等のデスクトップアプリ操作は nvidia-sync スキルを参照。 本スキルは CUDA C++/Python の書き方・PTX 命令・CUTLASS API を担当する。

タスク → カテゴリ マッピング

タスクカテゴリ参照 README
CUDA とは何か・GPU 階層モデル・CUDA プラットフォームの全体像を知りたいprogramming-modelreferences/programming-model/README.md
CUDA C++/Python でカーネルを書く、nvcc でビルドする、非同期実行・ストリームを扱うprogramming-modelreferences/programming-model/README.md
advanced カテゴリ全体の構成(core / features / appendices)を確認したいadvancedreferences/advanced/README.md
Driver API・マルチ GPU・advanced host/kernel programming を調べたいadvanced/corereferences/advanced/core/README.md
CUDA Graphs / Cooperative Groups / Unified Memory / VMM / IPC 等の機能 API を調べたいadvanced/featuresreferences/advanced/features/README.md
Compute Capability・環境変数・C++ 言語拡張・メモリ/実行モデルの技術付録を調べたいadvanced/appendicesreferences/advanced/appendices/README.md
PTX 命令セット・state space・レジスタ・memory consistency model を調べたいptx-isareferences/ptx-isa/README.md
Blackwell アーキテクチャ・SM occupancy・NVLink・メモリシステムのチューニングを知りたいblackwell-tuningreferences/blackwell-tuning/README.md
CUTLASS/CuTe 全体のカテゴリ構成(CuTe DSL / Operator API / C++)を確認したいcutlassreferences/cutlass/README.md
CuTe DSL (Python) で GEMM・MMA・レイアウトを書きたいcutlass/cute-dslreferences/cutlass/cute-dsl/README.md
CUTLASS Operator API(Python、コンパイル済みカーネル呼び出し)を使いたいcutlass/operator-apireferences/cutlass/operator-api/README.md
CUTLASS C++ / CuTe C++ でテンプレートベースの GEMM カーネルを実装したいcutlass/cppreferences/cutlass/cpp/README.md
典型的な使い方を知りたい(vector add, tiled matmul, GEMM, CUDA Graphs 等)samplessamples/README.md
インストール・nvcc ビルド・nsight プロファイリング・compute-sanitizer コマンドを知りたいscriptsscripts/README.md
from this repository

More skills

All skills
fandhe-ai
Community

better-auth

Better Auth (TypeScript 認証フレームワーク) v1.7 リファレンス。 認証・認可、サインアップ・サインイン、セッション管理、OAuth、パスキー、二要素認証 (2FA / TOTP)、SSO / SAML、SCIM、 OAuth Provider (OAuth 2.1 / OIDC)、MCP 認可 (@better-auth/mcp)、Infrastructure (dash / sentinel)、 プラグイン (organization, admin, magic-link, anonymous 等)。betterAuth, createAuthClient, signUp, signIn, getSession。 Next.js, Nuxt, SvelteKit, Hono, Express, Expo, TanStack, Effect 統合。

installs
2
GitHub stars
4
Updated
Oct 24
fandhe-ai
Community

anthropic-api-core

Claude API (platform.claude.com) の Messages API リファレンス。 streaming (SSE), thinking (adaptive) / effort, prompt caching, context editing, compaction, structured outputs, Message Batches, token counting, vision / PDF, Files API, citations, embeddings (Voyage AI)。 errors, rate limits, beta headers, Amazon Bedrock / Vertex AI / Foundry 経由アクセスを含む。

installs
1
GitHub stars
4
Updated
Oct 14
fandhe-ai
Community

anthropic-claude-code-admin

Claude Code (code.claude.com) の権限・セキュリティ・企業管理リファレンス。 permissions (allow / ask / deny), permission modes, auto mode, sandboxing (sandboxed Bash), sandbox environments, zero data retention, data usage, admin setup, server-managed settings, corporate launcher, network config, authentication (SSO), analytics, monitoring (OpenTelemetry), costs, large codebases。

installs
1
GitHub stars
4
Updated
Oct 14
fandhe-ai
Community

anthropic-claude-code-deploy

Claude Code (code.claude.com) のデプロイ・CI/CD リファレンス。 Amazon Bedrock / Google Cloud Agent Platform (Vertex AI) / Microsoft Foundry / Claude Platform on AWS 経由、Claude apps gateway、LLM gateway (protocol / rollout)、 GitHub Actions (claude-code-action) / GitLab CI/CD / GitHub Enterprise Server (GHES)、 code review 自動化・ultrareview、Slack (Claude Tag)、headless mode、cloud environments、 devcontainer、self-hosted environments(runner 構成・identity 検証・本番デプロイ)。

installs
1
GitHub stars
4
Updated
Oct 14