「zat」の検索結果

User story mapping for backlog management and outcome-based prioritization. Load during Phase 2.5 (User Story Mapping) to produce story-map.md and prioritization.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。

JTBD opportunity scoring and prioritization - outcome statement format, opportunity algorithm, scoring interpretation, feature prioritization, and opportunity matrix template

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。

Harden Laravel apps with Policies for model authorization, Gate-based RBAC, validated mass assignment, and CSRF protection. Use when creating authorization policies, securing env config access, or preventing mass assignment vulnerabilities.

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。

Apply SAP HANA database standards for SQL parameterization, in-memory engine optimization, dynamic IN query chunking, column aliasing on joins, and datatype casting. Use when writing SQL for SAP HANA, optimizing HANA queries, or diagnosing HANA driver 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。

Validates cyber exercise authorization, scope, exclusions, runtime controls, expiry, stop and restart gates. Use when planning or reviewing authorized security activity, scope drift, or unsupported execution 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。

Optimization techniques including OnPush, @defer, and Image Optimization. Use when optimizing Angular rendering, deferring blocks, or improving Core Web Vitals.

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。

Systematic experimental results analysis workflow for ML/AI research papers. Connects experimental data to publication-ready Results sections with statistical validation, visualizations, and quality checks. Triggers on "analyze experimental results", "generate results section", "statistical analysis of experiments", "compare model performance", "create results visualization".

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。

Multi-agent coordination, critical path method, dependency DAG, and agent allocation optimization

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When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.

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 comprehensive dashboard and analytics interfaces that combine data visualization, KPI cards, real-time updates, and interactive layouts. Use this skill when building business intelligence dashboards, monitoring systems, executive reports, or any interface that requires multiple coordinated data displays with filters, metrics, and visualizations working together.

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。

Constructs secure, efficient CI/CD pipelines with supply chain security (SLSA), monorepo optimization, caching strategies, and parallelization patterns for GitHub Actions, GitLab CI, and Argo Workflows. Use when setting up automated testing, building, or deployment workflows.

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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.

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Design, implement, optimize, and review SIMD code in .NET. USE FOR: vectorizing scalar loops with TensorPrimitives, Vector64/128/256/512, or platform hardware intrinsics; reviewing existing SIMD code, including the generic Vector type, for contract equivalence, tail handling, memory safety, portability, fallbacks, and measured performance. DO NOT USE FOR: performance work unrelated to SIMD or vectorization.

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Migrate a .NET 9 project or solution to .NET 10 and resolve all breaking changes. USE FOR: upgrading TargetFramework from net9.0 to net10.0, fixing build errors after updating the .NET 10 SDK, resolving source and behavioral changes in .NET 10 / C# 14 / ASP.NET Core 10 / EF Core 10, updating Dockerfiles for Debian-to-Ubuntu base images, resolving obsoletion warnings (SYSLIB0058-SYSLIB0062), adapting to SDK/NuGet changes (NU1510, PrunePackageReference), migrating System.Linq.Async to built-in AsyncEnumerable, fixing OpenApi v2 API changes, cryptography renames, and C# 14 compiler changes (field keyword, extension keyword, span overloads). DO NOT USE FOR: .NET Framework migrations, upgrading from .NET 8 or earlier (use migrate-dotnet8-to-dotnet9 first), greenfield .NET 10 projects, or cosmetic modernization. LOADS REFERENCES: csharp-compiler, core-libraries, sdk-msbuild (always); aspnet-core, efcore, cryptography, extensions-hosting, serialization-networking, winforms-wpf, containers-interop (selective).

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Use ManagedCode.MarkItDown when a .NET application needs deterministic document-to-Markdown conversion for ingestion, indexing, summarization, or content-processing workflows. USE FOR: ManagedCode.MarkItDown integration; document ingestion flows; Office or rich-text conversion to Markdown; indexing and summarization pipelines. 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。

Guide for theming .NET MAUI apps — light/dark mode via AppThemeBinding, ResourceDictionary theme switching, DynamicResource bindings, system theme detection, and user theme preferences. Use when: "dark mode", "light mode", "theming", "AppThemeBinding", "theme switching", "ResourceDictionary theme", "dynamic resources", "system theme detection", "color scheme", "app theme", "DynamicResource". Do not use for: localization or language switching (see .NET MAUI localization documentation), accessibility visual adjustments (see .NET MAUI accessibility documentation), app icons or splash screens (see .NET MAUI app icons documentation), or Bootstrap-style class theming (see Plugin.Maui.BootstrapTheme NuGet package).

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。

Create effective, publication-ready data visualizations. Use when choosing chart types, designing presentation visuals, building dashboard charts, or applying visual design best practices to data output.

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 code performance through iterative improvements (max 2 rounds). Benchmark execution time and memory usage, compare against baseline implementations, and generate detailed optimization reports. Supports C++, Python, Java, Rust, and other languages.

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。

Use when you need to design, review, or improve security in Micronaut applications — including micronaut-security authentication, @Secured and intercept-url-map rules, JWT/session strategies, SecurityService checks, CORS, CSRF awareness for browser apps, rejection handlers, and sensitive-data-safe logging. This should trigger for requests such as Add Micronaut security support; Review Micronaut security configuration; Improve API authorization in Micronaut; Add JWT security in Micronaut; Harden Micronaut route authorization rules. 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。

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。

Anti-rationalization enforcement for maximum-rigor task execution.

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 performance specialist covering analysis, optimization, load testing, and framework-specific performance. Use when identifying bottlenecks, optimizing code, conducting load tests, analyzing Core Web Vitals, fixing memory leaks, or improving application performance across all layers (application, database, frontend). Includes React-specific optimization 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。