「rop」の検索結果

Guide for diagnosing and improving MSBuild project evaluation performance. Only activate in MSBuild/.NET build context. USE FOR: builds slow before any compilation starts, high evaluation time in binlog analysis, expensive glob patterns walking large directories (node_modules, .git, bin/obj), deep import chains (>20 levels), preprocessed output >10K lines indicating heavy evaluation, property functions with file I/O ($([System.IO.File]::ReadAllText(...))), multiple evaluations per project. Covers the 5 MSBuild evaluation phases, glob optimization via DefaultItemExcludes, import chain analysis with /pp preprocessing. DO NOT USE FOR: compilation-time slowness (use build-perf-diagnostics), incremental build issues (use incremental-build), non-MSBuild build systems. INVOKES: binlog MCP server tools (evaluations, evaluation_global_properties, evaluation_properties, imports, properties); falls back to dotnet msbuild -pp:full.xml for preprocessing, /clp:PerformanceSummary.

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Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring, and behavioral heuristics. Identifies mass file modification patterns, abnormal entropy spikes in written data, and suspicious process behavior characteristic of ransomware encryption routines. Activates for requests involving ransomware behavioral detection, entropy-based file monitoring, I/O anomaly detection, or real-time encryption activity alerting.

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。

Windows アプリ開発 (WinUI 3 / XAML) の UI 基盤リファレンス。 レイアウトパネル Grid, StackPanel, Canvas, RelativePanel, SplitView, ScrollViewer、 XAML マークアップ x:Bind, x:Name, x:Class, StaticResource, ThemeResource、 添付プロパティ, 依存関係プロパティ、 スタイル・テーマ Style, ControlTemplate, DataTemplate, VisualStateManager, ResourceDictionary, Acrylic, Mica, SystemBackdrop、 データバインディング Binding, INotifyPropertyChanged, ObservableCollection, IValueConverter, DataContext, MVVM、 アニメーション Storyboard, DoubleAnimation, EasingFunction, ThemeTransition, ConnectedAnimation, ImplicitAnimation。

Python と TypeScript 向け Anthropic Claude API パターン。Messages API、ストリーミング、ツール使用、ビジョン、拡張思考、バッチ、プロンプトキャッシング、Claude Agent SDK をカバー。Claude API や Anthropic SDK を使ったアプリケーション構築時に使用。

MCP server for scraping Italian rental/sale property listings from multiple real estate portals (Immobiliare.it, Casa.it, and extensible to others) using Camoufox (anti-detection browser) and BeautifulSoup. Plugin architecture — each site is a self-contained adapter with its own URL templates, query param mappings, and CSS selector chains. Use this skill whenever the user wants to search for apartments, houses, or properties in Italy, scrape real estate listings, compare rental prices across Italian cities, or extract property data from Italian portals. Triggers on mentions of immobiliare, casa.it, Italian rentals, affitto, vendita, apartment hunting in Italy, or property scraping.

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。

Detects ransomware encryption activity in real time using entropy analysis, file system I/O monitoring, and behavioral heuristics. Identifies mass file modification patterns, abnormal entropy spikes in written data, and suspicious process behavior characteristic of ransomware encryption routines. Activates for requests involving ransomware behavioral detection, entropy-based file monitoring, I/O anomaly detection, or real-time encryption activity alerting.

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。

Obsidianの公式CLIでノートを検索・作成・編集し、日々の記録やタスク、リンク、プロパティも扱います。ノート保管庫を指定した操作にも対応します。

• 会議メモやプロジェクト記録を探したいとき
• 日次ノートに記録を追加したいとき
• 未完了タスクを確認・完了したいとき

参考映像から測定した色やカットのリズムを使い、生成動画と既存映像を編集・合成して、数値で照合した完成動画と再編集用のタイムラインを作るスキル。

• 参考映像のスタイルで動画を作りたいとき
• 既存映像に生成クリップを追加したいとき
• 映像素材や3D小物の合成

論文や研究計画を共通の評価基準で読み、研究方法、根拠、引用、文章構成を点検するスキル。評価の理由と修正の優先順位、次に直す内容を整理します。

• 投稿前の論文を見直したいとき
• 引用が主張を支えるか確認したいとき
• 研究方法と限界を評価したいとき

新機能や企画案を、PM・設計・開発・QAの4つの立場から同時に検討します。各役割の懸念や最初の行動を整理し、共通点と意見の対立をまとめるスキルです。

• 新機能を4つの立場で検討したいとき
• 実装前に提案の懸念を確認したいとき
• 新しい取り組みの初動を整理したいとき

公開データベースで化合物の活性や分子の性質、薬の相互作用を調べます。経口薬の候補としての特徴や遺伝子と疾患の関連を整理し、創薬研究の調査を支援します。

• 作用対象に合う活性化合物を探す
• 経口薬候補の分子特性を評価
• 相互作用と有害事象報告の調査

Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.

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。

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.

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 reviewing stylesheets, component styles, and responsive behavior related to Use CSS logical properties for i18n and RTL support. Check the rendered layout across breakpoints and interaction states before proposing a fix.

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 reviewing stylesheets, component styles, and responsive behavior related to Use CSS custom properties for design tokens. Check the rendered layout across breakpoints and interaction states before proposing a fix.

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 implementing animated gradients, complex CSS transitions that involve custom property values, or building a typed design token system where custom property misuse should produce visible errors.

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。

Search, read, upload, organize, and share files and folders in the user's Dropbox cloud storage. Use to upload or download files, collect client uploads with file requests, inspect or create shared links, and create, copy, move, or delete content through Dropbox's official APIs.

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。

Detect data exfiltration via DNS tunneling (tools like iodine, dnscat2, dns2tcp) by analyzing query entropy, subdomain length, query volume to single domains, TXT/CNAME/NULL record abuse, and oversized response payloads using passive DNS monitoring and statistical/ML methods. Use when hunting for covert DNS-based data exfiltration or building a passive DNS anomaly detection capability.

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。

Detect DNS-based data exfiltration by analyzing Zeek dns.log for high-entropy subdomains, oversized TXT/NULL records, and anomalous query volume or patterns. Use when investigating suspected DNS tunneling, covert C2 over DNS, or data exfiltration hidden in DNS queries against network traffic captured by Zeek.

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。

Deobfuscates malicious JavaScript found in phishing pages, web skimmers, and dropper scripts by reversing encoding layers, eval chains, string manipulation, and control-flow obfuscation to reveal the original malicious logic. Use when investigating a phishing page's obfuscated JavaScript, analyzing a Magecart-style web skimmer, or deobfuscating a JavaScript dropper that fetches second-stage malware.

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。

Run a compliance check on a proposed action, product feature, or business initiative, surfacing applicable regulations, required approvals, and risk areas. Use when launching a feature that touches personal data, when marketing or product proposes something with regulatory implications, or when you need to know which approvals and jurisdictional requirements apply before proceeding.

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。

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

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 an RFP, RFI, RFQ, security questionnaire, vendor questionnaire, or proposal request arrives and the team needs a structured response — parsing multi-section buyer-dictated requirements (MANDATORY vs WEIGHTED vs NICE-TO-HAVE), building a Shipley-method proof-point matrix mapping each requirement to a verifiable proof point, articulating 3-5 win-themes that ladder up across requirements, and producing a Shipley-derived winrate estimate that informs a bid / no-bid / partner-bid recommendation. For Bid Managers, Proposal Leads, Directors of Sales, and Sales Engineers at the response-strategy moment. Surfaces GAP requirements explicitly — never invents claims. NOT free-form proposal narrative authoring, NOT contract redline, NOT marketing collateral.

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。

Analyzes RFP/RFI responses for coverage gaps, builds competitive feature comparison matrices, and plans proof-of-concept (POC) engagements for pre-sales engineering. Use when responding to RFPs, bids, or proposal requests; comparing product features against competitors; planning or scoring a customer POC or sales demo; preparing a technical proposal; or performing win/loss competitor analysis. Handles tasks described as 'RFP response', 'bid response', 'proposal response', 'competitor comparison', 'feature matrix', 'POC planning', 'sales demo prep', or 'pre-sales engineering'.

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。