327 件 ・ 関連度順
概要と使いどころ
Apply and enforce cloud resource tagging strategies across AWS, Azure, GCP, and Kubernetes for cost allocation, ownership tracking, compliance, and automation. Use when implementing cloud governance, optimizing costs, or automating infrastructure 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。
Use dotnet-diagnostics-mcp for MCP-driven .NET CPU, allocation, GC, and test-host profiling. USE FOR: profiling unit tests or investigating runtime bottlenecks. DO NOT USE FOR: writing test assertions, coverage collection, or precise microbenchmark timing. INVOKES: connect the MCP server, select target processes, collect bounded profiles, and attribute hotspots to source.
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。
Route C# and .NET requests to the exact installed specialist or smallest dotnet/skills marketplace plugin. USE FOR: "which specialist should own this" or "how do I add the skill" requests involving ASP.NET Core endpoints, Blazor, MAUI binding, Windows Forms specialist selection or installation, EF Core queries, test or framework migration, runtime CPU/allocation evidence, file-based C#, editor/compiler defects, a surviving MSBuild `.binlog`, or a plugin missing from `/skills`; also use for C# semantics when no narrower specialist exists. DO NOT USE FOR: requests that already name the exact installed specialist to invoke, or work unrelated to C# or .NET.
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 `pvanalyze` to inspect existing .NET `.nettrace` files from the command line, including GC, JIT, CPU stacks, allocation, DATAS, events, exceptions, timeline, and call-tree analysis with JSON or SpeedScope. USE FOR: the user mentions pvanalyze, PerfView-style CLI trace analysis, or cross-platform .nettrace inspection; the task starts from an existing .nettrace file and needs. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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 the free official .NET diagnostics CLI tools for profiling and runtime investigation in .NET repositories. USE FOR: the repo needs performance or runtime profiling for a .NET application; the user asks about slow code, high CPU, GC pressure, allocation growth, exception storms, lock. DO NOT USE FOR: replacing realistic performance tests or load tests with ad-hoc tracing alone; production heap collection when the pause risk has not been. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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。
Scans .NET code for ~50 performance anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O with tiered severity classification. Use when analyzing .NET code for optimization opportunities, reviewing hot paths, or auditing allocation-heavy patterns.
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 a native app, service, or user-mode driver host allocation fails; distinguish VA exhaustion, fragmentation, and commit pressure. Not for managed .NET heap growth, proving a leak from one snapshot, or corruption.
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 you need to refactor Java code based on trusted profiling analysis findings — including reviewing repository-owned or maintainer-sanitized docs/profiling-problem-analysis and docs/profiling-solutions files, identifying specific performance bottlenecks, and implementing targeted code changes to address CPU, memory, or threading issues. This should trigger for requests such as Refactor the code with profiling; Apply profiling; Optimize hot path; Reduce allocations found in profiling; Fix CPU bottlenecks from profiling analysis. Part of Plinth Toolkit
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 you need to analyze Java profiling data collected during the detection phase — including interpreting flamegraphs, memory allocation patterns, CPU hotspots, threading issues, systematic problem categorization, evidence documentation with profiling-problem-analysis and profiling-solutions markdown files, or prioritizing fixes using Impact/Effort scoring. This should trigger for requests such as Analyze JFR profile; Analyze the profile; Analyze the performance; Analyze the memory; Analyze the threading; Analyze GC logs from profiling; Prioritize Java profiling bottlenecks by impact. Part of Plinth Toolkit
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。
Creates, updates, or reviews a project's gen-env command for running multiple isolated instances on localhost. Handles instance identity, port allocation, data isolation, browser state separation, and cleanup.
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。
Review a complete mathematical-modeling competition paper with an atomic checklist covering abstract readability, page structure, typography, headings, pagination, figures, tables, equations, anonymity, metadata, visual balance, and page allocation. Return the review in chat or Markdown by default, and provide the bundled single-sheet checklist when the user requests a reusable form. Use when the user provides a PDF or Word paper and asks for a full-paper format and writing-compliance audit; do not replace technical model correctness review.
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 managing multiple initiatives across time horizons (now/next/later, H1/H2/H3), balancing risk vs return across portfolio, sizing and sequencing bets with dependencies, setting exit/scale criteria for experiments, allocating resources across innovation types (core/adjacent/transformational), or when user mentions portfolio planning, roadmap horizons, betting framework, initiative prioritization, innovation portfolio, or resource allocation across horizons.
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 guide for Backend.AI distributed computing platform. Automatically activates when users ask about: - Backend.AI architecture, components (Manager, Agent, Storage Proxy, Webserver, App Proxy) - Features (session scheduling, Sokovan orchestrator, multi-tenancy, resource allocation) - APIs (REST, GraphQL), authentication, RBAC authorization - Container runtime (kernels, jail sandbox, hook library, virtual folders) - Accelerator support (CUDA, ROCm, TPU, NPU, Graphcore IPU) - Client SDKs (Python, Java, JavaScript, PHP) - Setup, requirements (Python 3.13+, Docker, PostgreSQL, Redis, etcd) - How WebUI connects to/interacts with Backend.AI backend - Plugin interfaces, development setup, infrastructure Use when user mentions "Backend.AI", "backend.ai", "Sokovan", component names, or asks about the backend platform this WebUI connects to. allowed-tools: WebFetch, Read
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。
Extract and analyze key clauses from construction contracts. Identify payment terms, change order procedures, dispute resolution, warranties, and risk allocation provisions.
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。
Allocate and track labor resources across project activities. Balance workload, track attendance, and optimize crew assignments.
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。
Optimize construction site logistics including material delivery scheduling, crane positioning, storage area allocation, and traffic flow using operations research and simulation.
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。
Analyze construction labor productivity using data analytics. Track worker performance, identify inefficiencies, predict resource needs, and optimize crew allocation for maximum efficiency.
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。
Optimize shared resource pools across multiple construction projects. Balance resource allocation, minimize conflicts, and maximize utilization across the portfolio.
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。
Review investment portfolios for risk, diversification, fees. Asset allocation recommendations, tax-loss harvesting, rebalancing.
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。
Vendor breach notification cascade management per GDPR Article 33(2). Covers processor-to-controller notification without undue delay, escalation paths, coordinated multi-party breach response, liability allocation, and regulatory notification coordination.
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。
Guides the establishment and management of joint controller arrangements under GDPR Article 26, including determination of joint controllership, allocation of responsibilities, and transparency obligations. Activate when two or more controllers jointly determine purposes and means of processing, or when evaluating shared data platforms. Keywords: joint controller, Article 26, shared responsibility, arrangement, joint determination.
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。
Design privacy-preserving analytics systems using differential privacy, k-anonymity, l-diversity, and t-closeness. Covers privacy budget allocation with epsilon tracking, references Google DP library, OpenDP, and Apple PPML. Includes Python differential privacy implementation for GDPR-compliant statistical 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。
Comprehensive portfolio analysis using Alpaca MCP Server integration to fetch holdings and positions, then analyze asset allocation, risk metrics, individual stock positions, diversification, and generate rebalancing recommendations. Use when user requests portfolio review, position analysis, risk assessment, performance evaluation, or rebalancing suggestions for their brokerage account.
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。
Master prioritization frameworks, roadmap planning, timeline estimation, and resource allocation. Create executable roadmaps that drive focus and alignment.
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。