「used」の検索結果

This skill should be used when the user asks to 'plan my day', 'help me plan today', 'morning planning', 'what should I work on today', 'daily planner', 'evening reflection', 'reflect on my day', 'migrate tasks', 'carry tasks forward', 'rapid log', 'brain dump my tasks', or mentions ADHD-friendly planning, time-blindness, swim lanes, energy-based task management, bullet journal for ADHD, or dopamine menu. Provides a BuJo-style daily planning system with swim lanes, migration, reflection, and dopamine rewards. Part of the ADHD-founder.com ecosystem.

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。

Design focused empty states for zero-data, no-results, permission, and error situations with clear value framing, strong CTAs, and less dead chrome. Use when the user mentions blank pages, zero-data screens, no results, permission states, or dead controls—not broader onboarding strategy.

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。

Add focused Bun unit tests for mission-critical behavior and edge cases — not blanket coverage.

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 an expert team communication specialist focused on async-first standup practices, AI-assisted note generation from commit history, and effective remote team coordination 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。

xUnit test project creation and setup specialized skill. Used when creating test projects, setting up project structure, configuring NuGet packages, and organizing test folders. Covers csproj setup, package management, project structure, xunit.runner.json configuration, etc. Keywords: xunit project, xunit setup, create test project, test project setup, create test project, project structure, project structure, folder structure, xunit package, nuget packages, testing packages, how to create test project, xunit configuration

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。

.NET unit test fundamentals and FIRST principles specialized skill. Used when creating unit tests, understanding testing basics, learning 3A Pattern, and mastering testing best practices. Covers FIRST principles, AAA Pattern, Fact/Theory, testing pyramid, etc. Keywords: unit test, unit test, unit testing, test fundamentals, testing fundamentals, FIRST principle, FIRST principle, 3A pattern, AAA pattern, Arrange Act Assert, Fact, Theory, InlineData, how to write tests, testing best practices, create unit test

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。

Test Data Builder Pattern complete implementation guide. Used when using builder pattern to create maintainable test data or simplify complex object test preparation. Covers fluent interface, semantic methods, default value design, and Builder composition patterns. Keywords: test data builder, builder pattern test, test data builder, object mother, fluent interface, fluent interface, UserBuilder, ProductBuilder, .With(), .Build(), AUser(), test data preparation, complex object creation, semantic testing

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。

Using NSubstitute to create test doubles (Mock, Stub, Spy) specialized skill. Used when isolating external dependencies, simulating interface behavior, and validating method calls. Covers Substitute.For, Returns, Received, Throws and complete guidance. Keywords: mock, stub, spy, nsubstitute, mock, test double, test double, IRepository, IService, Substitute.For, Returns, Received, Throws, Arg.Any, Arg.Is, isolate dependencies, simulate external services, dependency injection testing

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。

Test naming conventions and best practices specialized skill. Used when naming test methods, improving test readability, and establishing naming standards. Covers three-part naming method, Chinese naming recommendations, test class naming, etc. Keywords: test naming, test naming, naming conventions, naming conventions, three-part naming, three-part naming, method_scenario_expected, method_scenario_expected, how to name tests, test readability, naming best practices, test report, test documentation

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。

Using AwesomeAssertions for fluent and readable test assertion skill. Used when writing clear assertions, comparing objects, validating collections, handling complex comparisons. Covers Should(), BeEquivalentTo(), Contain(), ThrowAsync() and complete API. Keywords: assertions, awesome assertions, fluent assertions, assertion, fluent assertion, Should(), Be(), BeEquivalentTo, Contain, ThrowAsync, NotBeNull, object comparison, collection validation, exception assertion, AwesomeAssertions, FluentAssertions, fluent syntax

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。

Using AutoFixture to automatically generate test data basic skill. Used when quickly generating test objects, reducing boilerplate code, and implementing anonymous testing. Covers Fixture.Create, CreateMany, circular reference handling, and xUnit integration. Keywords: autofixture, fixture, auto-generate test data, test data generation, anonymous testing, anonymous testing, fixture.Create, CreateMany, fixture.Build, Create<T>, AutoFixture.Xunit2, OmitOnRecursionBehavior, IFixture, generate test data, generate test data

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。

Using Bogus to generate realistic fake data specialized skill. Used when generating realistic names, addresses, phone numbers, emails, company info and other test data. Covers Faker class, multi-language support, custom rules, bulk data generation, etc. Keywords: bogus, faker, fake data, fake data, realistic data, realistic data, fake name, fake address, fake email, Faker<T>, RuleFor, Generate, faker.Name, faker.Address, faker.Internet, generate fake data, generate fake data, seed data

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。

Mandatory final risk-focused review for any repository change. Checks security, architecture boundaries, test coverage, and release readiness before closeout.

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。

Perform repository-aware code reviews focused on bugs, regressions, architectural violations, missing tests, and operational risks. Use when the user asks for review of diffs, pull requests, patches, or implementation quality.

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。

Identifies and exploits insecure local data storage vulnerabilities in Android and iOS mobile applications including unencrypted databases, world-readable files, insecure SharedPreferences, plaintext credential storage, and improper keychain/keystore usage. Use when performing mobile penetration testing focused on OWASP M9 (Insecure Data Storage) or assessing compliance with MASVS-STORAGE requirements. Activates for requests involving mobile data storage security, local storage exploitation, SharedPreferences analysis, or mobile data leakage assessment.

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。

The Metasploit Framework is the world's most widely used penetration testing platform, maintained by Rapid7. It contains over 2,300 exploits, 1,200 auxiliary modules, and 400 post-exploitation modules

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。

Exploit PHP type juggling vulnerabilities caused by loose comparison operators to bypass authentication, circumvent hash verification, and manipulate application logic through type coercion attacks.

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。

Detecting and exploiting HTTP request smuggling vulnerabilities caused by Content-Length and Transfer-Encoding parsing discrepancies between front-end and back-end servers.

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 and analyzes process injection techniques used by malware including classic DLL injection, process hollowing, APC injection, thread hijacking, and reflective loading. Uses memory forensics, API monitoring, and behavioral analysis to identify injection artifacts. Activates for requests involving process injection detection, code injection analysis, hollowed process investigation, or in-memory threat 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。

Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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 defense evasion techniques used by adversaries in endpoint logs including log tampering, timestomping, process injection, and security tool disabling. Use when investigating suspicious endpoint behavior, building detection rules for evasion tactics, or conducting threat hunting for stealthy adversary activity. Activates for requests involving evasion detection, defense evasion analysis, log tampering detection, or MITRE ATT&CK TA0005.

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 anomalies in DNP3 (Distributed Network Protocol 3) communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.

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 abuse of legitimate Windows binaries (LOLBins) used for living off the land attacks. Monitors process creation, command-line arguments, and parent-child relationships to identify suspicious LOLBin execution 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。