「toolkit」の検索結果

Design and execute DAG-based automation workflows using the NV oOS Pro Workflow Builder — a ReactFlow visual builder for chaining tool calls, agent runs, and actions into repeatable pipelines. Covers the visual builder UI, 10 preset categories (incl. AI Fashion Production, v1.1.92+), 10 node types, Kahn's algorithm execution engine, scheduling via Pro Schedule Manager, template variable syntax, and best practices. Use when designing workflows, debugging DAG execution failures, choosing between a workflow schedule and raw tool chaining, or building CRM/PM automation pipelines with toolkit_cpt nodes.

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Manage AI assistant configurations and peer-to-peer mesh network connections in the NV oOS Pro Toolkit. Covers assistant creation, model configuration, provider setup, peer discovery, mesh networking, cross-assistant communication, and detecting from a coding-agent session (Zed) which NV oOS assistants / MCP servers are enabled. Use when creating or editing AI assistants, configuring model providers, setting up peer connections, managing mesh network topology, debugging assistant behavior, or answering "is agent X available" / "what tools does this MCP have".

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Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, an

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。

Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

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。

Mandatory skills, conventions, and behavioral rules for Avalonia UI development using the Zafiro toolkit.

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scikit-learn compatible Python toolkit for time series ML: classify, cluster, regress, segment, transform with 30+ algorithms (ROCKET, InceptionTime, KNN-DTW, HIVE-COTE, WEASEL). Handles panel, multivariate, and unequal-length series. Maintained successor to sktime. Alternatives: sktime (larger ecosystem), tslearn (fewer algorithms), catch22 (features only).

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Pick the right serving container for a SageMaker model deployment and find its current image URI. Use this skill whenever about to deploy a model to a SageMaker endpoint and an image URI needs to be chosen — including when the user says "deploy this LLM", "host this HuggingFace model", "serve this fine-tuned model", "deploy this embedding model", "host a reranker", "serve a sentence-transformers model", or when about to hardcode any container URI in deployment code. HuggingFace-curated Deep Learning Containers are ALWAYS preferred: HuggingFace vLLM (LLMs and generative rerankers), HuggingFace vLLM-Omni (multimodal), TEI (embeddings/cross-encoder rerankers), HF Inference Toolkit (other transformers). Generic images (AWS vLLM, DJL-LMI, SGLang) are used only when no HuggingFace image is compatible — never merely because they carry a newer version. Never hardcode a container URI from memory and never default to TGI. Prevents stale-image failures and wrong-region URIs.

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。

Complete App Store Optimization (ASO) toolkit for researching, optimizing, and tracking mobile app performance on Apple App Store and Google Play Store

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。

Essential tools and frameworks for modern product management, from discovery to delivery.

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。

6 production-ready AI engineering workflows: prompt evaluation (8-dimension scoring), context budget planning, RAG pipeline design, agent security audit (65-point checklist), eval harness building, and product sense coaching.

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。

Complete toolkit for senior architect with modern tools and 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。

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

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。

Essential tools and frameworks for modern product management, from discovery to delivery.

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。

自然语言 → Mermaid 图表（16 种）+ 网页原型，本地 Web 面板实时预览/导出。

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This skill should be used when the user asks to "calculate overtime", "未払残業代計算", "残業代を計算", "労基法37条", "割増賃金", "深夜労働", or wants deterministic computation of unpaid overtime wages under the Labor Standards Act Article 37.

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。

This skill should be used when the user asks to "analyze a lawsuit", "訴訟分析", "事件分析", "書面分析", "case analysis", "判決分析", "訴訟書類の整理", or wants to extract structured information from litigation documents.

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。

This skill should be used when the user asks to "calculate property division", "離婚の財産分与", "財産分与計算", "清算金", "夫婦共有財産の分与", or wants deterministic computation of divorce property division under 民法 768.

This skill should be used when the user asks to "calculate traffic accident damages", "交通事故の損害額を計算", "損害賠償額を算出", "赤い本基準で計算", "逸失利益を計算", "後遺障害の慰謝料", "過失相殺後の金額", or wants deterministic computation of personal-injury damages under the Red Book (赤い本) standard.

This skill should be used when the user asks to "recalculate debt", "利息制限法で引き直し", "引き直し計算", "過払金", "過払い金", "サラ金", "貸金業者との取引履歴から引き直し", or wants deterministic recalculation of loan transactions under the Interest Rate Restriction Act.

This skill should be used when the user asks to "analyze a koseki", "戸籍の分析", "家族関係", "相関図", "family tree", "戸籍謄本", "親族関係", "家系図", "戸籍を読んで", "相続関係図", "法定相続情報", "戸籍から相関図を作って", or wants to extract family relationships from documents.

This skill should be used when the user asks to "calculate inheritance shares", "法定相続分を計算", "相続分を出して", "相続割合", "誰がどれだけ相続する", "遺留分", or wants to compute statutory inheritance shares from a family tree.

This skill should be used when the user asks to "create a template", "テンプレート作成", "書式を登録", "XLSXをテンプレート化", "テンプレート登録", "この書式を登録して", "テンプレートを追加", or wants to register a new court document template from an XLSX file.

This skill should be used when the user asks to "fill a template", "テンプレート入力", "書式入力", "裁判所書類の作成", "テンプレートに入力", "書式に記入", "この書式に入れて", "PDFからテンプレートに", "書類を作成して", "これも追加して", "このデータも入れて", or wants to auto-populate or incrementally add data to court documents.