「anti」の検索結果

Improve UX writing, marketing copy, labels, microcopy, instructions, and error messages so interfaces and product messaging are easier to understand and act on. Use when the user mentions confusing copy, unclear labels, bad error text, weak CTAs, hard-to-follow instructions, or wanting better UX writing.

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。

Systematically audit and remediate accessibility issues in UI, focusing on keyboard navigation, screen reader support, color contrast, semantic HTML, ARIA usage, and motion sensitivity. Use when the user wants to improve accessibility, make a component accessible, fix WCAG violations, add keyboard support, or ensure screen reader compatibility.

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。

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。

You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create actionable remediation plans.

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 Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in the latest Python ecosystem including uv, ruff, pydantic, and FastAPI. Use PROACTIVELY for Python development, optimization, or advanced Python 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。

Build financial models, backtest trading strategies, and analyze market data. Implements risk metrics, portfolio optimization, and statistical arbitrage. Use PROACTIVELY for quantitative finance, trading algorithms, or risk 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。

Analyzes keyword usage in provided content, calculates density, suggests semantic variations and LSI keywords based on the topic. Prevents over-optimization. Use PROACTIVELY for content optimization.

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 Python 3.12+ with modern features, async programming, performance optimization, and production-ready practices. Expert in uv, ruff, pydantic, and FastAPI.

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。

Build high-performance async APIs with FastAPI, SQLAlchemy 2.0, and Pydantic V2. Master microservices, WebSockets, and modern Python async patterns. Use PROACTIVELY for FastAPI development, async optimization, or API architecture.

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。

Write idiomatic C++ code with modern features, RAII, smart pointers, and STL algorithms. Handles templates, move semantics, and performance optimization. Use PROACTIVELY for C++ refactoring, memory safety, or complex C++ 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。

Applies SOLID and DRY principles. C# anti-patterns, fixes, SRP compliance checks.

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 guide for AutoFixture and Bogus integration. Use when you need to combine AutoFixture with Bogus to generate test data that is both anonymous and realistic. Covers SpecimenBuilder integration, hybrid generators, test data factories, and circular reference handling. Keywords: autofixture bogus integration, autofixture bogus, bogus integration, Faker, EmailSpecimenBuilder, PhoneSpecimenBuilder, NameSpecimenBuilder, realistic test data, semantic data, hybrid generator, HybridTestDataGenerator, OmitOnRecursionBehavior, circular reference

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。

Implements accessible .NET UI. SemanticProperties, ARIA, AutomationPeer, testing per platform.

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 C# code smells during review. Anti-patterns, async misuse, DI mistakes, fixes.

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 fileless malware and in-memory attacks that execute entirely in RAM without writing persistent files to disk, evading traditional antivirus. Use when building detections for PowerShell-based attacks, reflective DLL injection, WMI persistence, and registry-resident malware. Activates for requests involving fileless malware detection, in-memory attacks, PowerShell exploitation, or living-off-the-land techniques.

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。

Automate AWS GuardDuty threat detection findings processing using EventBridge and Lambda to enable real-time incident response, automatic quarantine of compromised resources, and security notification workflows.

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。

Responds to phishing incidents by analyzing reported emails, extracting indicators, assessing credential compromise, quarantining malicious messages across the organization, and remediating affected accounts. Covers email header analysis, URL/attachment sandboxing, and mailbox-wide purge operations. Activates for requests involving phishing response, email incident, credential phishing, spear phishing investigation, or phishing remediation.

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 malicious VBA macros embedded in Microsoft Office documents (Word, Excel, PowerPoint) to identify download cradles, payload execution, persistence mechanisms, and anti-analysis techniques. Uses olevba, oledump, and VBA deobfuscation to extract the attack chain. Activates for requests involving Office macro analysis, VBA malware investigation, maldoc analysis, or document-based threat examination.

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 bootkit and advanced rootkit malware that infects the Master Boot Record (MBR), Volume Boot Record (VBR), or UEFI firmware to gain persistence below the operating system. Covers boot sector analysis, UEFI module inspection, and anti-rootkit detection techniques. Activates for requests involving bootkit analysis, MBR malware investigation, UEFI persistence analysis, or pre-OS malware detection.

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。

One-shot brand-faithful presales redesign of a website page. The user provides only the URL; everything else — extraction, tension identification, three differentiated variants (one fully cinematic), validation — is derived from the captured brand surface. Use when the user asks to "uplift", "refresh", or "redesign a site for presales" without wanting to coordinate the extract / direct / prototype chain themselves.

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 the user wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI 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。

Rewrite AEM Edge Delivery Services page content for AI search discoverability (GEO — Generative Engine Optimization). Analyzes content structure, semantic clarity, and factual density, then produces optimized rewrites that rank in both traditional search and AI-powered search engines. Use when optimizing pages for search visibility, AI discoverability, or content clarity.

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。

Improve search engine visibility with proper meta tags, structured data, sitemaps, and semantic HTML.

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, edit, fix, or explain Mermaid diagrams for relationships, decision branches, interactions, lifecycles, and data models; also use when the parent selects a diagram to materially clarify an explanation. Do not trigger for simple status, one fact, short lists, quantitative charts, or marketing slides.

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。