Instrument applications with Azure Application Insights and OpenTelemetry for end-to-end observability. Use this skill when users ask about telemetry, tracing, metrics, logging, or monitoring setup. Covers SDK setup, correlation, sampling, dashboards, and alerts per OpenTelemetry standards.
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 an Azure AI gateway layer for centralized model routing, policy enforcement, and operational control. Use this skill when users ask about centralized AI traffic management, model governance, rate limiting, or gateway 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。
Apply OpenAI's brand colors, typography, and visual identity standards to artifacts. Ensure design consistency with OpenAI branding for presentations, documents, and UI components.
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 in building products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.
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。
AI agent development workflow for building autonomous agents, multi-agent systems, and agent orchestration with CrewAI, LangGraph, and custom 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。
Validate Azure deployments against functional, security, performance, and operational criteria before production release. Use this skill when users ask for readiness checks, health verification, or production sign-off gates. Covers Well-Architected Framework validation, SLA verification, and release readiness.
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。
Assess and manage Azure service quotas and limits to prevent deployment and scaling failures. Use this skill when users ask about quota errors, capacity planning, regional availability, or resource limits.
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。
Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
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。
Convert human-written CLAUDE.md into AI-native structured-label format. Battle-tested across 4 models. Same rules, fewer tokens, higher 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。
Select and implement the right Azure compute platform for a workload. Decision tree guides choice based on workload characteristics, scaling needs, and operational maturity. Covers serverless, PaaS, containers, Kubernetes, and IaaS 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 persistent agents on Azure AI Foundry using the Microsoft Agent Framework Python SDK.
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 in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration.
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。