「performance」の検索結果

Creates marketing analytics reports, KPI dashboards, ROI calculations, and performance summaries for SME marketing teams. Handles weekly/monthly reporting, campaign analysis, content performance reviews, and data-driven recommendations. Use when user asks about marketing metrics, reporting, KPIs, dashboards, ROI analysis, performance review, or data-driven marketing decisions.

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。

Measure real frontend performance — Core Web Vitals (LCP, CLS, INP), page-load traces, CPU and network throttling, Lighthouse accessibility/SEO scores, and heap growth — using chrome-devtools-mcp against a live browser. Trigger when asked "is the page fast enough", "measure Core Web Vitals", "why is this route slow", "run Lighthouse", "check for a memory leak", before any performance-gated certification (Built for Shopify, Core Web Vitals thresholds, store listing review), and before any launch or traffic-multiplier event. Measurement only — this skill never drives functional journeys.

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。

Measure, root-cause, fix, verify and record performance contention on a developer machine: cloud-sync daemons (iCloud Drive, OneDrive, Dropbox, Google Drive), file indexers, AI-tool MCP server fleets, and automation browsers left behind by tests and browser skills. Trigger when the machine is slow, apps freeze, browser or MCP tool calls time out, load exceeds the core count, or before and after any UI/UX/performance test run. Includes the L0–L4 optimisation scale and the test-hygiene contract.

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。

[Debugging] Use when analyzing or optimizing performance bottlenecks: database queries, N+1 fan-out, indexing, API latency, memory/GC, concurrency and pool saturation, algorithmic complexity (O(n²)), network/protocol round trips, frontend rendering and Core Web Vitals, caching, and distributed/resilience paths. Calibration constants and domain laws (latency ladder, Little's Law, utilization knee, CWV thresholds, symptom→cause triage) live in references/performance-knowledge.md.

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。

Capture and compare Clawix UI performance budgets for critical flows before optimizing visible or runtime UI behavior.

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 for release-level accessibility and performance review, including WCAG 2.2 AA, keyboard/focus, target size, reduced motion, semantic controls, Core Web Vitals, images/fonts/JavaScript, and animation or 3D performance budgets.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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。

Ensure architecture/design docs state traffic assumptions, performance budgets, resource limits, and cost risks for critical paths.

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。

Diagnoses and prevents mobile performance regressions on every stack — Flutter, native Android, native iOS, React Native and Kotlin Multiplatform. Covers startup time, rendering and jank, memory, battery and background work, app size, the profiler and benchmark to use on each platform, and regression detection in CI. Use when an app is slow, janky, heavy or draining the battery, when setting performance budgets, or when a release must not regress.

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。

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

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。

Axis-by-axis interview methodology for establishing engineering performance budgets during architecture PRD compilation. Use when conducting the Step 10.5 performance budget interview in /create-prd-compile.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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 en performance des agents IA (optimisation latence, streaming, caching, traitement par lots)

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 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.

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。

Diagnose MSBuild build performance bottlenecks using binary log analysis. Only activate in MSBuild/.NET build context. USE FOR: identifying why builds are slow by analyzing binlog performance summaries, detecting ResolveAssemblyReference (RAR) taking >5s, Roslyn analyzers consuming >30% of Csc time, single targets dominating >50% of build time, node utilization below 80%, excessive Copy tasks, NuGet restore running every build. Covers timeline analysis, Target/Task Performance Summary interpretation, and 7 common bottleneck categories. Use after build-perf-baseline has established measurements. DO NOT USE FOR: establishing initial baselines (use build-perf-baseline first), fixing incremental build issues (use incremental-build), parallelism tuning (use build-parallelism), non-MSBuild build systems. INVOKES: binlog MCP server tools (overview, errors, search, items, properties); falls back to dotnet msbuild binlog replay + grep/cat when the MCP is unavailable.

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 website and web application performance including loading speed, Core Web Vitals, bundle size, caching strategies, and runtime performance

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。

Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.

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。

Audit and improve SwiftUI runtime performance. Use when diagnosing slow rendering, janky scrolling, high CPU, memory usage, excessive view updates, layout thrash, body evaluation cost, identity churn, view lifetime issues, lazy loading, Instruments profiling guidance, and performance audit requests.

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 website and web application performance including loading speed, Core Web Vitals, bundle size, caching strategies, and runtime performance

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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。

Performance optimization, profiling, caching strategies, lazy loading, bundle optimization, and monitoring. Use when optimizing application performance, reducing bundle size, implementing caching, or analyzing bottlenecks.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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。

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

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。