「application」の検索結果

Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to "dogfood", "QA", "exploratory test", "find issues", "bug hunt", "test this app/site/platform", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.

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。

Generate a complete, production-ready application from an OpenAPI specification

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。

Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, review experiments, inspect datasets, and query the GraphQL API. Use when debugging AI/LLM applications, analyzing trace data, working with Phoenix observability, or investigating LLM performance issues.

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。

Microsoft Store Developer CLI (msstore) for publishing Windows applications to the Microsoft Store. Use when asked to configure Store credentials, list Store apps, check submission status, publish submissions, manage package flights, set up CI/CD for Store publishing, or integrate with Partner Center. Supports Windows App SDK/WinUI, UWP, .NET MAUI, Flutter, Electron, React Native, and PWA applications.

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。

Adds .NET Aspire cloud-native orchestration to existing .NET solutions. Analyzes solution structure to identify services (APIs, web apps, workers), creates AppHost and ServiceDefaults projects, configures service discovery, adds NuGet packages, and sets up distributed application orchestration. Use when adding Aspire to .NET solutions or creating new cloud-ready distributed applications.

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。

Open-source embedding database for AI applications. Store embeddings and metadata, perform vector and full-text search, filter by metadata. Simple 4-function API. Scales from notebooks to production clusters. Use for semantic search, RAG applications, or document retrieval. Best for local development and open-source projects.

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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

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。

Specialized skill for ASP.NET Core integration testing. Use when testing Web API endpoints, HTTP request/response, middleware, and dependency injection. Covers WebApplicationFactory, TestServer, HttpClient testing, in-memory database configuration. Keywords: integration testing, web api testing, WebApplicationFactory, TestServer, HttpClient testing, controller testing, endpoint testing, RESTful API testing, Microsoft.AspNetCore.Mvc.Testing, CreateClient, ConfigureWebHost, AwesomeAssertions.Web, Be200Ok, Be404NotFound, middleware testing, 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。

Security hardening and best practices for .NET applications. Navigation skill covering OWASP Top 10, authentication, authorization, cryptography, secrets management, and secure coding. For building secure applications. Keywords: security, owasp, authentication, authorization, cryptography, jwt, oauth, secrets, hardening

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 ASP.NET Core Web API integration testing. Use when performing integration testing on Web API endpoints or validating ProblemDetails error format. Covers WebApplicationFactory, IExceptionHandler, Testcontainers multi-container orchestration, Flurl URL construction, and AwesomeAssertions HTTP validation. Keywords: webapi integration testing, WebApplicationFactory, asp.net core integration test, webapi integration test, IExceptionHandler, ProblemDetails, ValidationProblemDetails, AwesomeAssertions, Flurl, Respawn, Be201Created, Be400BadRequest, multi-container testing, Collection Fixture, global exception handling

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 and measurement for .NET applications. Navigation skill covering Span, ArrayPool, memory management, benchmarking, profiling, Native AOT, and optimization patterns. For building high-performance applications. Keywords: performance, optimization, span, arraypool, benchmarking, profiling, memory, gc, aot, native-aot

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 patterns and architectural guidance for .NET applications. Navigation skill covering vertical slices, domain modeling, messaging patterns, resilience, caching, and system design. For building scalable, maintainable applications. Keywords: architecture, patterns, vertical slices, domain modeling, messaging, resilience, caching, design 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。

Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.

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。

Parses and analyzes the Windows Amcache.hve registry hive to extract evidence of program execution, application installation, and driver loading for digital forensics investigations. Uses Eric Zimmerman's AmcacheParser and Timeline Explorer for artifact extraction, SHA-1 hash correlation with threat intel, and timeline reconstruction. Activates for requests involving Amcache forensics, program execution evidence, Windows artifact analysis, or application compatibility cache investigation.

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。

This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.

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。

This skill should be used when the user asks to "intercept HTTP traffic", "modify web requests", "use Burp Suite for testing", "perform web vulnerability scanning", "test with Burp Repeater", "analyze HTTP history", or "configure proxy for web testing". It provides comprehensive guidance for using Burp Suite's core features for web application security 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。

Main application building orchestrator. Creates full-stack applications from natural language requests. Determines project type, selects tech stack, coordinates agents.

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 stateful Agents on Cloudflare Workers with current, source-verified SDK APIs. Covers durable state, RPC, chat, schedules, queues, fibers, Workflows, MCP, and channels while keeping authorization and external effects application-owned. NOT for assuming SDK helpers grant application authorization or effect approval.

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 production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.

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。

How to design contextual inputs for an always-on AI agent with episodic memory. Covers what data to feed the agent, how to structure observations and triggers, ambient context capture (screen, audio, calendar), context window budgeting, and retrieval strategies that keep the agent grounded in what's actually happening. Activate on: "what should the agent observe", "context inputs for agent", "ambient context capture", "agent triggers", "agent input design", "screenpipe integration", "context window budget", "what data to feed my agent", "/always-on-agent-inputs". NOT for: memory architecture and storage (use always-on-agent-architecture), application ideas (use always-on-agent-applications), safety concerns (use always-on-agent-safety).

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。

Architecture and systems design for agents that retain bounded state across sessions. Covers durable event history, owned state, derived memory, retrieval indexes, framework evaluation, recovery, deletion, and rebuild behavior. Uses constructed implementation examples and workload calibration rather than universal vendor, latency, similarity, retention, or cost claims. Activate on: "always-on agent", "persistent agent architecture", "episodic memory system", "agent memory design", "long-running agent", "stateful agent", "agent that remembers", "MemGPT architecture", "Letta deployment", "/always-on-agent-architecture". NOT for: choosing what data to feed the agent (use always-on-agent-inputs), brainstorming applications (use always-on-agent-applications), safety and privacy concerns (use always-on-agent-safety), general agentic patterns (use agentic-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。

Safety-case design for always-on agents with episodic memory. Covers data hygiene, privacy and security risk surfaces, cost controls, scope, user dependency concerns, retention, incident containment, and responsible deployment evidence. It identifies hazards and asks for named controls, tests, owners, and residual uncertainty; it does not provide legal, clinical, youth-safety, or jurisdictional determinations. Activate on: "agent safety", "always-on agent privacy", "agent cost control", "persistent agent risks", "AI companion safety", "agent data hygiene", "runaway agent costs", "parasocial AI risk", "/always-on-agent-safety". NOT for: architecture design (use always-on-agent-architecture), input design (use always-on-agent-inputs), application brainstorming (use always-on-agent-applications), healthcare compliance specifically (use hipaa-compliance).

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。

Discordのデスクトップアプリで、ログイン済みの本人アカウントから承認済みの告知などを投稿し、送信先・本文の確認から投稿結果の確認まで進めるスキル。

• 本人アカウントでリリース告知を投稿したいとき
• 指定チャンネルに承認済みの文面を送りたいとき
• 投稿前に送信先と本文を確認したいとき

MyBatisを使うJavaのデータ保存・取得処理を設計、レビューします。SQLと結果の対応付け、動的SQLの安全性、トランザクションや検索性能を扱います。

• マッパーとXMLの対応付けの設計
• 動的SQLと入力値の安全性確認
• 複数更新のトランザクション確認