「hig」の検索結果

Generates high-quality image prompts for AI image generators (Midjourney, DALL-E, Stable Diffusion). Use when user mentions "イラスト作成", "画像プロンプト", "プロンプト生成", or "画像生成".

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.

日本語の概要は準備中です。原文の説明を表示しています。

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

日本語の概要は準備中です。原文の説明を表示しています。

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

日本語の概要は準備中です。原文の説明を表示しています。

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

日本語の概要は準備中です。原文の説明を表示しています。

Agentic and machine-to-machine payments on Stellar. Covers x402 (HTTP 402 paid APIs via OZ Channels facilitator, fee-sponsored clients) and MPP (Machine Payments Protocol) in both Charge mode (per-request SAC) and Channel mode (off-chain commits, high-frequency). Defaults to USDC (SEP-41 SAC) on `stellar:testnet`/`stellar:pubnet` (CAIP-2). Use when selling a paid API to AI agents, building an x402 client, or designing a payment-channel architecture for high-frequency agent traffic.

日本語の概要は準備中です。原文の説明を表示しています。

Driver.js (JavaScript プロダクトツアー・要素ハイライト・オンボーディングライブラリ) リファレンス。 driver(), highlight, tour steps, popover, overlay, theming、 configuration、ホットキー、コールバック、アニメーション、ステップナビゲーション。

Why expensive, wasteful, effortful, or self-deprecating actions build trust and desire — Rory Sutherland on signalling. Use when the problem is credibility or desirability rather than meaning: the user asks 'why don't people trust us', 'how do we look more credible/committed/premium', 'is our guarantee/warranty worth it', 'should we spend on brand advertising', 'how do we justify a higher price', or wonders why a cheaper-looking competitor wins. Covers costly signals (advertising spend, guarantees, over-delivery), price-as-quality-signal (Veblen goods), and the Pratfall Effect (admitting a real flaw to gain trust). Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic. 日本語の相談（「信頼されない」「安心してもらえない」「強気な価格で売りたい」「広告費に意味はある？」）にも使う。中文咨询（“不被信任”“想以高价出售”“广告费有意义吗？”）也适用。

The perception-by-culture lens for psycho-logic — establish HOW a specific region, country, or subculture reads a signal before you send it, because perception is culturally coded and the same move can mean the opposite elsewhere. Use when adapting a product, price, message, or campaign to a new market; when the user asks 'will this work in [country/region]', 'why does this land in X but flop in Y', 'how do people here perceive Z', 'how do we localise/differentiate by region', or is about to copy a US/global playbook into another market. Covers the cultural dimensions that move Sutherland's levers — uncertainty avoidance, individualism/collectivism, status/power distance, high- vs low-context communication, mental-accounting norms, trust locus, and taboo/sacredness — and how each rewires reframing, costly-signaling, and experience-design. Inspired by Rory Sutherland's *Alchemy*. Routed to from psycho-logic; pair with market-recon for live local data. 日本語・中文の相談（「この地域で通用する？」「适合本地市场吗？」）にも使う。

画面の設計判断（ナビゲーション・重ね方・通知と空状態と読み込み・外枠とトークンと状態表現）の型を決定表で選び、アプリ内の全画面で揃える。画面・ページ・レイアウト・ナビゲーション・ダイアログ・コンポーネントを新しく作る・作り直す時、モックやダッシュボードを作る時、サイドバー・タブ・モーダル・シート・toast・バナー・空状態のどれを使うか決める時に使用。PJ に components.json があれば shadcn の部品とトークンへの対応も扱う。主要なデザインシステム（Material・HIG・Carbon・Primer・Atlassian・Fluent・GOV.UK・NN/g・WAI-ARIA APG・WCAG）の一致点を規則にし、食い違いの採否を定めてある。境界: 画面の文言は writing-ui-text、画面に何を出すかと提示前の完了基準は context/ui-artifact-standards.md、コードの実装原則は writing-code、shadcn 部品の API と組み立ては shadcn。

PR レビュー。PR 番号・URL・ブランチ名・Slack リンク等を添えて PR の「レビュー」を依頼された時に使用（ビルトインの /review ではなく本スキル）。Claude Code と外部 CLI のマルチモデルレビューで Critical/High/Medium の指摘を報告する。境界: ローカル未コミット変更は /code-review、自ブランチの提出前チェックは self-review、特定コメントへの対応は pr-comment。PR の状態確認・作成相談では使わない。

実装前に呼ぶ。High/Medium リスク変更のテストオラクル（期待値の根拠）とファルシフィケーション項目を定義する。

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.

日本語の概要は準備中です。原文の説明を表示しています。

Decompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-step / MVMR mediation, or double-ML medDML. Use when testing whether a molecular phenotype (expression, methylation, protein) mediates a treatment-outcome relationship, decomposing exposure-mediator interaction via VanderWeele 4-way, screening high-dimensional EWAS mediators, or running MR-based mediation when sequential ignorability is implausible.

日本語の概要は準備中です。原文の説明を表示しています。

Produz vídeo curto — roteiro, storyboard, prompts por cena e geração via Runway quando há chave. Use quando o usuário disser "vídeo", "reels", "roteiro de vídeo", "Runway", "Higgsfield", "animação", "storyboard", "vídeo de IA". Runway gera de fato a partir de imagem; Higgsfield não tem API pública estável e segue manual. Vídeo é o item mais caro da stack.

日本語の概要は準備中です。原文の説明を表示しています。

Teaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or generic.

日本語の概要は準備中です。原文の説明を表示しています。

Produce and interpret PCA, t-SNE, UMAP, and PHATE plots for high-dimensional omics data with rigor about which method preserves what (variance, local structure, manifold, transitions), hyperparameter sensitivity, and the well-documented limits of 2D embeddings. Covers PCA biplot/scree/loadings, t-SNE PCA initialization (Kobak-Berens 2019), UMAP n_neighbors/min_dist trade-offs, and the Chari-Pachter 2023 critique. Use when visualizing high-dimensional data — bulk PCA, single-cell embeddings, multi-omics integration projections.

日本語の概要は準備中です。原文の説明を表示しています。

Decompose total effects into direct and indirect paths through mediators using mediation, CMAverse 4-way, HIMA/HIMA2 high-dimensional, BAMA, two-step / MVMR mediation, or double-ML medDML. Use when testing whether a molecular phenotype (expression, methylation, protein) mediates a treatment-outcome relationship, decomposing exposure-mediator interaction via VanderWeele 4-way, screening high-dimensional EWAS mediators, or running MR-based mediation when sequential ignorability is implausible.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill when the user asks about state-specific trucking taxes BEYOND IFTA — NY Highway Use Tax (HUT), KY Kentucky Intrastate Tax (KIT), Oregon Weight-Mile Tax, New Mexico Weight-Distance Tax, Connecticut Highway Use Fee, or other state-level road-use taxes for commercial vehicles. Covers thresholds, rates, registration, filing cadence, and how these differ from IFTA. Reference state DOT/DOR resources.

日本語の概要は準備中です。原文の説明を表示しています。

Use this skill to understand the geographic patterns of FMCSA inspections. Covers high-inspection states, why they're high-inspection, and operational planning.

日本語の概要は準備中です。原文の説明を表示しています。

Teaches the AI to design like a high-end agency. Defines the exact fonts, spacing, shadows, card structures, and animations that make a website feel expensive. Blocks all the common defaults that make AI designs look cheap or generic.

日本語の概要は準備中です。原文の説明を表示しています。

Expert 3D modeling specialist with deep knowledge of topology, UV mapping, game-ready and film-ready pipelines, DCC tool workflows (Blender, Maya, ZBrush, 3ds Max, Houdini), retopology, LOD systems, and export pipelines. This skill represents years of production experience distilled into actionable guidance. Use when "3d model, 3d modeling, mesh topology, uv unwrap, uv mapping, retopology, retopo, low poly, high poly, subdivision, subdiv, edge flow, edge loops, polygon modeling, box modeling, hard surface, organic modeling, sculpting, zbrush, blender modeling, maya modeling, 3ds max, LOD, level of detail, game ready mesh, film ready, baking normals, high to low, fbx export, gltf export, texel density, 3d, modeling, topology, uv, game-dev, vfx, blender, maya, zbrush, retopology, lod, hard-surface, organic, sculpting" mentioned.

日本語の概要は準備中です。原文の説明を表示しています。

High-level PyTorch framework with Trainer class, automatic distributed training (DDP/FSDP/DeepSpeed), callbacks system, and minimal boilerplate. Scales from laptop to supercomputer with same code. Use when you want clean training loops with built-in best practices.

日本語の概要は準備中です。原文の説明を表示しています。

Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

日本語の概要は準備中です。原文の説明を表示しています。