apple-silicon
Apple Silicon GPU コンピュート／数値計算リファレンス。MSL (address space, atomic, SIMD-group, TensorOps, cooperativetensor, matmul2d), threadgroup sizing, argument buffer, indirect command buffer, unified memory, GPU counters, MTLTensor, MTL4MachineLearningCommandEncoder, MPS / MPSGraph / MPSMatrix / MPSNDArray / MPSNNGraph, MLX (mx.array, lazy evaluation, grad / vmap, mx.compile, mx.fft, exportfunction, mlx.nn, distributed)。
- Installs
- 275
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/fandhe-ai/agent-reference-skills --skill apple-silicon- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads apple-silicon automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
apple-silicon
Apple Silicon 上の GPU コンピュートと数値計算スタック。Metal Shading Language (MSL) の言語仕様、 compute dispatch のエンコーディングと unified memory 最適化、MPS/MPSGraph による行列演算・ニューラルネットワーク推論、 Apple 研究チーム発の配列フレームワーク MLX をカバーする。
ディレクトリ構成
skills/apple-silicon/
SKILL.md
references/
metal-compute/
README.md
compute-pass-encoding.md
threadgroup-sizing.md
compute-pipeline-configuration.md
indirect-command-buffers.md
indirect-compute-commands.md
gpu-counters.md
counter-sample-buffers.md
argument-buffers.md
unified-memory.md
tensors.md
machine-learning-passes.md
msl/
README.md
data-types.md
address-spaces.md
function-qualifiers.md
argument-attributes.md
atomic-functions.md
simdgroup-functions.md
math-functions.md
numerical-compliance.md
tensor-types.md
tensor-operations.md
mps/
README.md
mpskernel.md
mpsimage.md
image-filters.md
mpsmatrix.md
matrix-arithmetic.md
matrix-decomposition-solve.md
mpsndarray.md
mpsnngraph.md
cnn-kernels.md
mpsgraph.md
mpsgraph-tensor.md
mpsgraph-executable.md
mpsgraph-operations.md
ray-tracing.md
mlx/
README.md
array.md
lazy-evaluation.md
unified-memory-model.md
function-transforms.md
compilation.md
nn-module.md
optimizers.md
nn-layers.md
nn-losses-activations.md
indexing.md
saving-loading.md
random.md
linalg.md
devices-streams.md
memory-management.md
fast-custom-kernels.md
distributed.md
tree-utils.md
data-types.md
operations.md
fft.md
export.md
kv-cache.md
precision.md
environment-variables.md
metal-backend.md
samples/
README.md
compute-kernel-dispatch.md
nonuniform-threadgroup-dispatch.md
shared-storage-mode-buffer.md
resource-group-argument-buffer.md
cpu-encoded-indirect-compute.md
blit-and-compute-single-pass.md
mpsgraph-matrix-multiplication.md
mpsgraph-training-loop.md
mps-image-filter.md
mlx-array-lazy-evaluation.md
mlx-unified-memory.md
mlx-mlp-training-loop.md
mlx-function-transforms.md
scripts/
README.md
toolchain-setup.md
metal-compile.md
metal-symbols.md
metal-binary-archives.md
metal-dynamic-libraries.md
metal-debug-env.md
metal-performance-hud.md
mlx-install.md
mlx-distributed.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:
- 下記マッピング表でタスクに対応するカテゴリを探す
- そのカテゴリの
references/{category}/README.md（samples/scripts/は直下の README.md）を参照して目的のページを特定する - 該当ページの
.mdを Read して詳細を確認する
Metal のレンダリングパイプライン（MTLRenderCommandEncoder / MTLRenderPipelineState）・Core Animation・
Core Graphics・Core Image・SpriteKit・SceneKit は apple-graphics を参照。本スキルは Metal のコンピュート
（MTLComputeCommandEncoder 以下）・MSL 言語仕様・MPS/MPSGraph・MLX を担当する。
Core ML / Create ML による .mlmodel のオンデバイス推論・Vision・Natural Language・Speech、および Core AI (iOS 27, NDArray / ComputeUnitKind) は apple-ml を参照。
Compute Graph (RealityKit) は apple-spatial、MetalFX denoising は apple-graphics を参照。
MLX のみ出典が developer.apple.com ではなく、Apple 研究チームが公開する OSS ドキュメント
（ml-explore.github.io）である点に注意する。
タスク → カテゴリ マッピング
| タスク | カテゴリ | 参照 README |
|---|---|---|
| compute pass のエンコーディング・threadgroup/grid サイズ計算・compute pipeline 設定を知りたい | metal-compute | references/metal-compute/README.md |
| argument buffer・indirect command buffer・GPU counter・unified memory (storage mode) を調べたい | metal-compute | references/metal-compute/README.md |
| MSL のデータ型・address space・kernel 関数属性・引数バインディング属性を調べたい | msl | references/msl/README.md |
| MSL の atomic 関数・SIMD-group/quad-group 関数・数学関数・数値精度 (IEEE 754) 準拠を調べたい | msl | references/msl/README.md |
| MPSKernel/MPSImage/MPSMatrix/MPSNDArray による画像フィルタ・行列演算・分解を調べたい | mps | references/mps/README.md |
| MPSGraph/MPSNNGraph によるグラフ構築・実行・CNN 推論・ray tracing を調べたい | mps | references/mps/README.md |
| Metal 4 の MTLTensor 作成・ML pass (MTL4MachineLearningCommandEncoder) のエンコードを調べたい | metal-compute | references/metal-compute/README.md |
| MSL の tensor / cooperative_tensor / TensorOps (matmul2d, convolution, execution scope) を調べたい | msl | references/msl/README.md |
| MLX の array/dtype・lazy evaluation・indexing・保存/読み込みを調べたい | mlx | references/mlx/README.md |
| MLX の dtype 一覧・演算一覧・FFT (stft)・関数 export (.mlxfn) を調べたい | mlx | references/mlx/README.md |
| MLX の環境変数・数値精度 (TF32, Winograd)・KV cache・Metal capture を調べたい | mlx | references/mlx/README.md |
| MLX の grad/vmap 等の関数変換・mx.compile・unified memory model・distributed を調べたい | mlx | references/mlx/README.md |
| mlx.nn のレイヤー/損失関数・mlx.optimizers・tree utils を調べたい | mlx | references/mlx/README.md |
| 典型的な使い方を知りたい（compute kernel dispatch, argument buffer, MPSGraph 学習ループ, MLX 学習ループ等） | samples | samples/README.md |
Metal Toolchain セットアップ・.metal のコンパイル/リンク・デバッグ環境変数・MLX インストールを知りたい | scripts | scripts/README.md |
FAQ
What does the apple-silicon skill do?
Apple Silicon GPU コンピュート／数値計算リファレンス。MSL (address space, atomic, SIMD-group, TensorOps, cooperativetensor, matmul2d), threadgroup sizing, argument buffer, indirect command buffer, unified memory, GPU counters, MTLTensor, MTL4MachineLearningCommandEncoder, MPS / MPSGraph / MPSMatrix / MPSNDArray / MPSNNGraph, MLX (mx.array, lazy evaluation, grad / vmap, mx.compile, mx.fft, exportfunction, mlx.nn, distributed)。
How do I install apple-silicon?
Run npx skills add https://github.com/fandhe-ai/agent-reference-skills --skill apple-silicon in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/apple-silicon/ (personal) or .claude/skills/apple-silicon/ (project).
Which AI agents can use apple-silicon?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is apple-silicon safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains apple-silicon?
It is published by fandhe-ai in fandhe-ai/agent-reference-skills. It has 275 recorded installs.
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