「cro」の検索結果

Power Platform のテナント / 環境ガバナンスを確認・設定する管理スキル。開発着手前の環境チェック（既定環境ではないか・マネージド環境・Dataverse / Code Apps / MCP の有効化・セキュリティ ロール・管理 API アクセス）と DLP 事前チェックを非対話スクリプトで実行し、必要ならマネージド環境設定・カスタムコネクタの DLP 分類・ACP（Advanced connector policies）の許可コネクタを dry-run 付きで変更する。Microsoft 第一者サービスだけを許可する ACP 推奨プロファイルの適用と、クラシック DLP から ACP への移行も支援する。クラシック DLP と ACP は既定の混成モードで併用され、より制限の厳しい方が適用されるため両方を確認する。オプションとして、既定環境 / 個人開発者環境 / 市民開発者環境 / AI CoE セントラル / AI CoE 内製開発の 5 グループからなるテナント全体の環境戦略を、読み取り専用スキャン → 移行プラン（admin-migration-plan.md）→ レビュー → 適用の順で策定・実行する。設定は環境グループのルールで行うのを原則とし、グループ ルールに無い項目（既定環境ルーティング・Dataverse for Teams 禁止・Dataverse 検索・グループへの割り当て・Copilot クレジット配分）だけをテナント設定・環境個別設定・Dataverse の組織設定で補う。IP 制限・テナント分離・監査ログ・ライセンス配分などの管理設定は references にまとめる。

CSV / JSON などの既存データを Dataverse / Azure Databricks / Microsoft Fabric Lakehouse へ移行する。ソースのプロファイル → マッピング契約の生成とレビュー → 検証と hash 承認 → 冪等な投入（upsert / MERGE / 全件ロード）→ 件数・キー・列値の照合までをスクリプトで行う。投入先の作成は dataverse / data-platform スキルが担当する。

architecture で選定したデータ基盤（Microsoft Fabric / Azure Databricks / Foundry IQ）を、事前確認 → plan と hash 承認 → デプロイ → セマンティック層 → runtime 検証 → 計算停止まで API で構築し、MCP 接続情報を Cowork / Copilot Studio / Foundry へ引き渡す。Dataverse は dataverse スキル、データ投入は data-migration スキルへ委譲する。

メールと Teams に届いた本部通達を読み、自店でやること・期限・担当・売場変更の段取りに分けて一覧にするスキル。チャットにグラフ（Render UI）と一覧、整理の考え方を説明した HTML レポートも作る。必要なら To Do / Planner への登録案も作る（登録は承認後）。 Use when ユーザーが「本部の通達を整理して」「今日やることをまとめて」「通達から売場変更の段取りを作って」と依頼したとき。 Microsoft 365 の標準機能（メール・Teams・To Do / Planner）を使う。Dataverse MCP コネクタ（describe / read_query）は「今日」の日付と、通達に関係する在庫を確かめるときだけ読み取りで使う。

Power Apps Native Mobile Code Apps（Private Preview）を Microsoft 公式 Expo テンプレートから作成し、React Native UI、Power Platform 接続、ネイティブ機能、実機プレビュー、Wrap、デプロイまで実施する。

Batch download academic paper full-text (PDF/XML) from a list of DOIs. Handles 25 DOI prefixes across 19 publisher families via three layered routes: (1) publisher TDM APIs requiring institutional subscription (Elsevier ScienceDirect, Wiley Online, Springer Nature), (2) Open Access sources (Crossref, Unpaywall, OpenAlex), and (3) a browser-based fallback for paywalled publishers without TDM access (ACS, RSC, IEEE, AIP, IOP, APS, Annual Reviews, T&F, Chinese journals). Browser fallback offers two routes — Route A drives the user's logged-in Chrome via the OpenClaw `browser` tool with `profile="user"` (best for interactive sessions), Route B uses the standalone `auto-paper-harvester` CLI with its built-in Playwright (best for unattended bulk runs). Use when the user wants to harvest, scrape, fetch, or bulk-download papers from a DOI list, savedrecs export, or Excel; or wants to fill missing full-text PDFs for an existing literature collection. Triggers on phrases like "批量下载文献", "下载全文", "harvest papers", "scrape full text", "TDM API", "下载 Elsevier 全文", "Wiley 批量下载", "下载 PDF".

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。

Foundational concepts in nutrition science — macronutrients, micronutrients, energy balance, Atwater factors, reference intakes (DRI/RDA/AI/UL), food composition tables, and the methods of human nutrition research. Grounds the rest of the department in a shared vocabulary and in the measurement limits of the field, including controlled-trial history, observational-study limits, and the biochemical basis for calorie accounting. Use when a question asks what something "is" nutritionally, how energy and nutrients are measured, or what the reference numbers mean.

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。

Biochemical metabolism of macronutrients and key micronutrients — digestion, absorption, transport, utilization, and excretion — with emphasis on the pathways that matter for dietary-guideline debates (insulin response, lipoprotein metabolism, one-carbon metabolism, iron homeostasis). Use when a question asks what happens biochemically to a food after it is eaten, or when a claim about "metabolic effect" needs to be tested against mechanism.

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。

Measurement techniques for identifying composition, microstructure, and properties of engineering materials — optical and electron microscopy, x-ray diffraction, EDS and WDS spectroscopy, thermal analysis, mechanical testing, and fractography. Covers when to use which technique, sample-preparation pitfalls, and how to build a characterization plan that answers a specific engineering question rather than accumulating data for its own sake.

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。

Embedded firmware development for microcontrollers including memory-mapped I/O, GPIO, interrupts, timers, UART/SPI/I2C serial protocols, PWM generation, ADC sampling, interrupt-driven versus polled architectures, RTOS fundamentals, and the bring-up sequence from power-on reset through first printf. Covers AVR/Arduino, ARM Cortex-M, and ESP32 patterns. Use when writing, porting, debugging, or reviewing firmware that directly manipulates hardware peripherals.

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。

Service-oriented and microservices architecture patterns for cloud-scale systems. Covers service boundaries, API versioning and backward compatibility, eventual consistency at the API layer, idempotency keys, saga and choreography patterns, bulkheads, circuit breakers, service meshes, and the Vogels "you build it, you run it" operating principle. Use when designing service decomposition, API contracts, inter-service communication, or reviewing a proposed microservices architecture for coupling and resilience.

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。

Bridge layer connecting the Agentic AI Foundation (AAIF) governance structure — Linux Foundation stewardship of MCP, goose, AGENTS.md — to the plurigrid/asi skill graph. Formalizes AAIF-compatible skill registration, IPSIE identity profiles, and the cross-protocol interoperability surface. Maps the AAIF platinum member ecosystem (AWS, Anthropic, Block, Bloomberg, Cloudflare, Google, Microsoft, OpenAI) to specific ASI skill integration points.

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 when writing Python scripts that must run on Windows, Linux, and macOS — especially when Rich or Typer output breaks on Windows, when dealing with Unicode/encoding errors, ANSI escape handling, terminal detection, path separators, or console color support. Provides verified cross-platform patterns covering stdout/stderr encoding guards, Windows console quirks, terminal capability detection, and portable I/O for CLI, TUI (Rich/Textual), and GUI environments.

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。

Execute large-scale automated code transformations safely and idempotently. Use when renaming symbols across a codebase, migrating API call-sites, enforcing new patterns at scale, or applying structural edits to many files at once. Triggers on: 'codemod', 'mass rename', 'migrate all usages', 'transform codebase', 'apply pattern at scale', AST-based refactoring, or any task requiring consistent edits across 10 or more files.

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。

Validate and iterate on the SDLC Layer Separation Architecture implementation across the check categories defined in its Evaluation Checklist — cross-references, doc completeness, knowledge-explorer layer filters, research entry metadata, integration points, and plan consistency. Produces a structured findings report and optionally applies safe fixes. Use when validating a first-pass implementation, before claiming layer work complete, auditing layer docs or schema, or running --dry-run to preview findings without changes.

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。

Advises on setting up and validating topic models for survey and experimental text. Covers the discovery-versus-measurement question, choosing STM, LDA, or BERTopic, preprocessing consequences, prevalence and content formulas, topic-count selection across coherence, exclusivity and FREX, held-out likelihood, and residuals, validation of topics against human judgment, robustness, and DA-RT-compliant reporting. Use when the user has open-ended responses or another corpus and asks what topics are present, how many topics to use, about STM, searchK, coherence, or FREX, or wants topic prevalence compared across treatment arms or countries. Fixed-codebook coding goes to text-classification.

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。

Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.

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。

When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," or "in-app pricing." Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.

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。

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

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。

Microsoft.Extensions.Options patterns including IValidateOptions, strongly-typed settings, validation on startup, and the Options pattern for clean configuration management.

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。

Cross-verify Claude-generated plans and code using OpenAI Codex and Google Gemini CLI. Provides code review, plan validation, and comparative analysis. Use when needing second opinions on Claude's code or plans, validating technical decisions, or seeking consensus from multiple AI models.

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。

Personal research-paper radar. Fetches the latest papers and code repos for the user's keyword subscriptions across arXiv, Crossref (IEEE/ACM), Semantic Scholar, GitHub, HuggingFace, Papers with Code and RSS; deduplicates against history; then YOU (the assistant) expand the queries, filter for computer-science relevance, write Chinese summaries, detect hot sub-fields, and emit a Markdown + HTML digest (optionally emailed). Use when the user asks to "run my paper radar / 文献雷达", "check for new papers", "what's new in my topics", "今天有什么新论文 / 最新文献", "today's research digest", or to configure their keyword subscriptions / sources / schedule.

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。

适用于 ROS 1 / ROS 2 机器人开发、迁移与联调的 skill。覆盖 catkin/catkin_tools、colcon/ament、package.xml、CMakeLists.txt、launch、URDF/Xacro、RViz、TF、Navigation2、ros2_control、串口/CAN、MCU 与 micro-ROS 等常见工程场景。

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VNX-specific domain expertise for the intelligence system, central state databases, and dispatch lifecycle. Use when working on quality_intelligence.db / runtime_coordination.db / dispatch_tracker.db, code_snippets FTS5, snippet_metadata linkage, success_patterns / antipatterns, T0 state projection (t0_state.json), intelligence_injections lifecycle, dispatch → receipt → events → archive flow, central state architecture, project_id propagation across VNX, or any code that reads/writes VNX governance state. Triggers include: editing intelligence injection code, querying central DB for cross-project insights, debugging "intelligence not appearing in T0 state", modifying schema in `schemas/quality_intelligence.sql` or `schemas/runtime_coordination_v*.sql`, working with `scripts/quality_db_init.py` or `scripts/lib/coordination_db.py`.

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。