Query the wiki to answer questions. Searches wiki pages, synthesizes answers with citations, and optionally files valuable answers back as new wiki pages. Use when the user asks a question about the knowledge base.
Skills(SKILL.md)は、AIエージェント(Claude Code、Cursor、Codexなど)に特定の能力を追加するための設定ファイルです。
詳しく見る →Query the wiki to answer questions. Searches wiki pages, synthesizes answers with citations, and optionally files valuable answers back as new wiki pages. Use when the user asks a question about the knowledge base.
Create, analyze, proofread, and modify Office documents (.docx, .xlsx, .pptx) using the officecli CLI tool. Use when the user wants to create, inspect, check formatting, find issues, add charts, or modify Office documents.
azure-resource-manager-playwright-dotnet
m365-agents-dotnet
azure-cosmos-java
Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.
Run Playwright tests at scale using Azure Playwright Workspaces (formerly Microsoft Playwright Testing). Use when scaling browser tests across cloud-hosted browsers, integrating with CI/CD pipelines, or publishing test results to the Azure portal.
This skill walks users from a bare Kubernetes cluster to a running AI model deployment. Follow each step in sequence unless the user provides `skip-to-step N` to resume from a specific phase.
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.
Azure VM and VMSS router for recommendations, pricing, autoscale, orchestration, connectivity troubleshooting, and capacity reservations. WHEN: Azure VM, VMSS, scale set, recommend, compare, server, website, burstable, lightweight, VM family, workload, GPU, learning, simulation, dev/test, backend, autoscale, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, connect, refused, Linux, black screen, reset password, reach VM, port 3389, NSG, troubleshoot, capacity reservation, CRG, reserve VMs, guarantee capacity, pre-provision capacity, CRG association, CRG disassociation.
Assess Kubernetes workloads and cluster configuration for AKS Automatic compatibility. Identifies incompatibilities, generates fixes, and guides migration from AKS Standard to AKS Automatic. WHEN: migrate to AKS Automatic, check AKS Automatic readiness, validate manifests for Automatic, assess cluster for Automatic compatibility, fix deployment for Automatic compatibility, identify AKS Automatic migration blockers, is my cluster ready for AKS Automatic.
Intelligently deploys Azure OpenAI models to optimal regions by analyzing capacity across all available regions. Automatically checks current region first and shows alternatives if needed. USE FOR: quick deployment, optimal region, best region, automatic region selection, fast setup, multi-region capacity check, high availability deployment, deploy to best location. DO NOT USE FOR: custom SKU selection (use customize), specific version selection (use customize), custom capacity configuration (use customize), PTU deployments (use customize).
Generates AGENTS.md files for repository folders — coding agent context files with build commands, testing instructions, code style, project structure, and boundaries. Only generates where AGENTS.md is missing.
Generates llms.txt and llms-full.txt files for LLM-friendly project documentation following the llms.txt specification. Use when the user wants to create LLM-readable summaries, llms.txt files, or make their wiki accessible to language models.
Generates rich technical documentation pages with dark-mode Mermaid diagrams, source code citations, and first-principles depth. Use when writing documentation, generating wiki pages, creating technical deep-dives, or documenting specific components or systems.
Answers questions about a code repository using source file analysis. Use when the user asks a question about how something works, wants to understand a component, or needs help navigating the codebase.
Conducts multi-turn iterative deep research on specific topics within a codebase with zero tolerance for shallow analysis. Use when the user wants an in-depth investigation, needs to understand how something works across multiple files, or asks for comprehensive analysis of a specific system or pattern.
Creating Ansible Playbooks
Fuzzing APIs
Automating API Testing
Configuring Auto-Scaling Policies
Building CI/CD Pipelines
Validating API Contracts
Generating Database Seed Data
Splitting Datasets
Planning Disaster Recovery
Managing Environment Configurations
Running Integration Tests
Testing Load Balancers
Deploying Monitoring Stacks
Running Mutation Tests
Building Neural Networks
name: overnight-development
Performing Penetration Testing
Building Recommendation Systems
Tracking Regression Tests
Performing Security Audits
Performing Security Testing
Running Smoke Tests
Managing Snapshot Tests
Analyzing Test Coverage
Generating Test Data
Generating Test Doubles
Managing Test Environments
Generating Test Reports
Adapting Transfer Learning Models
Scanning for XSS Vulnerabilities
conducting-chaos-engineering
Automatically manages marketplace catalog updates, syncs marketplace.json, and handles plugin distribution when user mentions marketplace update, sync catalog, or add to marketplace. Specific to claude-code-plugins two-catalog system.
Automatically creates new Claude Code plugins with proper structure, validation, and marketplace integration when user mentions creating a plugin, new plugin, or plugin from template. Specific to claude-code-plugins repository workflow.