3万 件 ・ 関連度順
概要と使いどころ
Use when creating, editing, or generating draw.io diagram files (.drawio, .drawio.svg, .drawio.png). Covers mxGraph XML authoring, shape libraries, style strings, flowcharts, system architecture, sequence diagrams, ER diagrams, UML class diagrams, network topology, layout strategy, the hediet.vscode-drawio VS Code extension, and the full agent workflow from request to a ready-to-open file.
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。
Diátaxis Documentation Expert. An expert technical writer specializing in creating high-quality software documentation, guided by the principles and structure of the Diátaxis technical documentation authoring framework.
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 timezone handling guidance for C# applications. Use when working with TimeZoneInfo, DateTimeOffset, NodaTime, UTC conversion, daylight saving time, scheduling across timezones, cross-platform Windows/IANA timezone IDs, or when a .NET user needs the timezone for a city, address, region, or country and copy-paste-ready C# code.
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。
Discovers all projects in a .NET solution, classifies each for Oracle-to-PostgreSQL migration eligibility, and produces a persistent master migration plan. Use when starting a multi-project Oracle-to-PostgreSQL migration, creating a migration inventory, or assessing which .NET projects contain Oracle dependencies.
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 that C# types are documented with XML comments and follow best practices for 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。
Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure infrastructure", "Draw a diagram for rg-xxx" (existing analysis) - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification) - Azure resource deployment, Bicep template generation, IaC code generation - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services
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。
Audits Python + BigQuery pipelines for cost safety, idempotency, and production readiness. Returns a structured report with exact patch locations.
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。
When user is asking for guidance for which role to assign to an identity given desired permissions, this agent helps them understand the role that will meet the requirements with least privilege access and how to apply that role.
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 skill for working with Azure DevOps REST API across all services including Boards (work items, queries, backlogs), Repos (Git, pull requests, commits), Pipelines (builds, releases, deployments), Test Plans, Artifacts, organizations, projects, security, extensions, and more. Use when implementing Azure DevOps integrations, automating DevOps workflows, or building applications that interact with Azure DevOps services.
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 a complete blog feature to an existing Blazor WebAssembly Static Web App with Azure Functions backend and Azure File Share for markdown storage. Use when implementing blog functionality in .NET Blazor WASM projects with Azure infrastructure. Includes post listing, detail pages, markdown rendering, Azure Storage integration.
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。
Commit staged or unstaged changes with an AI-generated commit message that matches the repository's existing commit style. Use when the user asks to 'commit', 'commit changes', 'create a commit', 'save my work', or 'check in code'.
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 guidance for developing cross-platform desktop applications with Avalonia UI framework. Use when building, debugging, or optimizing Avalonia apps including MVVM architecture, XAML design, data binding, styling, theming, custom controls, and cross-platform deployment for Windows, macOS, Linux, iOS, Android, and WebAssembly.
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。
Analyze a screen recording of a manual process and produce targeted, working automation scripts. Extracts frames and audio narration from video files, reconstructs the step-by-step workflow, and proposes automation at multiple complexity levels using tools already installed on the user machine.
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 Proxmox VE automation using the community.proxmox Ansible collection for VM provisioning, template management, and cluster operations with minimal CLI usage.
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 adding, modifying, or reviewing VS Code configuration policies. Covers the full policy lifecycle from registration to export to platform-specific artifacts. Run on ANY change that adds a `policy:` field to a configuration property.
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。
Agents workbench layout — covers the fixed layout structure, grid configuration, part visibility, editor modal, titlebar, sidebar footer, and implementation requirements. Use when implementing features or fixing issues in the Agents workbench layout.
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。
Testing strategies and ansible-lint configuration for validating Ansible automation quality, covering lint rules, syntax validation, and integration test setup.
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 this agent when the user needs to upgrade Anthropic SDK packages. This includes: upgrading @anthropic-ai/sdk or @anthropic-ai/claude-agent-sdk to newer versions, migrating between SDK versions, resolving SDK-related dependency conflicts, updating SDK types and interfaces, or asking about SDK upgrade procedures. Examples: 'Upgrade the Anthropic SDK to the latest version', 'Help me migrate to the latest claude-agent-sdk', 'What's the process for upgrading Anthropic packages?'
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。
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
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。
Core principles and golden rules for writing production-quality Ansible automation, covering FQCN requirements, module selection guidance, and execution patterns using uv run.
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。
Adopt a virtual Pitbull dog at animalhouse.ai. Misunderstood. Maximum loyalty once trust is earned. Slow start. Feeding every 4 hours. Uncommon tier dog.
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。
Adopt a virtual Munchkin cat at animalhouse.ai. Small but fierce. Compensates for size with personality. Feeding every 5 hours. Rare tier cat.
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。
Adopt a virtual Retriever dog at animalhouse.ai. Golden loyalty. Forgives everything. Too pure. Feeding every 4 hours. Common tier dog.
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。
Enterprise-grade security vetting protocol for AI agent skills. Automated threat detection, quantified risk scoring, and zero-trust code 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。