agentic-architecture-patterns
Decision framework for designing production agentic systems on GitHub platform and Azure AI Foundry. Covers model routing tiers (mini to frontier), prompt caching and semantic caching, short and long term memory, context curation and RAG, tools and MCP, identity and guardrails, evaluation, observability (OpenTelemetry GenAI), and cost control. Use when architecting an AI agent or multi-agent system, choosing a model router, deciding a caching or memory strategy, planning context windows, or reviewing an agent design for reliability, security, and cost. Pairs with azure-managed-redis-cache, foundry-agent-blueprint, azure-api-center, apim-ai-gateway, and azure-architecture-diagrams.
2026-06-22
Front model and tool backends with Azure API Management as an AI gateway: token rate limiting (token-per-minute and quota), multi-backend load balancing and circuit breaker across model deployments, semantic caching, token metric emission for cost attribution, managed identity to backends, and content safety integration. Use when designing the runtime gateway for an agentic platform, enforcing token budgets, load balancing across model endpoints, adding a semantic cache at the gateway, or governing tool API calls. Routes to the installed azure-aigateway skill for policy detail. Pairs with azure-api-center (governance), azure-managed-redis-cache (cache backend), and agentic-architecture-patterns.
2026-06-22
Validate an architecture document (the {app}_Architecture.md produced by the Senior Cloud Architect agent) against a hard Definition of Done: required sections, the five required diagrams, well-formed Mermaid, the seven explanation parts per diagram, and the repository copy conventions. Use when producing, reviewing, or finishing an architecture document, or whenever you need to confirm a Mermaid-based architecture deliverable is complete and will render before presenting it.
2026-06-22
Govern APIs and agent tools at enterprise scale with Azure API Center: a central catalog of APIs, versions, definitions (OpenAPI), environments, and deployments, plus registration of agent tools and MCP servers for discovery and reuse. Use when designing API governance for an agentic platform, building a tool or MCP registry for agents, enforcing API standards with the API Center linter, or making backend APIs discoverable to agent builders. Pairs with apim-ai-gateway (runtime gateway), foundry-agent-blueprint (tool consumption), and agentic-architecture-patterns (tools and MCP).
2026-06-22
azure-architecture-diagrams
Produce complete, professional architecture diagrams that use the official Azure, Microsoft, and GitHub (Octicons) icon sets, output as editable draw.io (.drawio) files and exported SVG. Covers the official icon catalogs and their terms of use, the draw.io mxGraph file format, layout and connector conventions, and a bundled draw.io MCP server (Python FastMCP) that creates and edits .drawio diagrams programmatically (add nodes with official icons, connect edges, group, and lay out). Use whenever the deliverable includes an architecture diagram, a system context, a component or deployment diagram, or any cloud diagram that must use official vendor icons. Pairs with ai-native-engineer and agentic-architecture-patterns, and complements svg-professional for hand-crafted SVG.
2026-06-22
azure-managed-redis-cache
Design and provision Azure Managed Redis as the cache, semantic cache, vector store, session store, and agent memory backend for AI-native systems. Covers SKU selection (Balanced, MemoryOptimized, ComputeOptimized, FlashOptimized), the fact that Redis Enterprise is retired for new creations, vector search and RedisVL for semantic caching and long term memory, session and short term state, tenant isolation, managed identity (Entra) access, private networking, and a Bicep sample. Use when an agent design needs caching, a semantic cache, a vector memory store, or session state on Redis. Pairs with agentic-architecture-patterns and apim-ai-gateway.
2026-06-22
Design and provision agents on Azure AI Foundry Agent Service: model catalog and deployments, connections (Azure AI Search, Azure Managed Redis, Bing, storage), threads and runs for short term memory, tools (function, OpenAPI, MCP, code interpreter, file search), evaluation, and tracing. Use when the target runtime is Azure AI Foundry, when choosing models from the Foundry catalog, when wiring agent tools and connections, or when planning Foundry evaluation and observability. Routes to the installed microsoft-foundry, azure-ai, and vscode-microsoft-foundry skills for provisioning detail. Pairs with agentic-architecture-patterns, azure-managed-redis-cache, azure-api-center, and apim-ai-gateway.
2026-06-22
Creates professional Markdown documents with YAML frontmatter, versioning, author attribution, table of contents, and consistent formatting. Use for Markdown documents, README, ADR, spec, guide, changelog, runbook, RFC, technical docs, and converting PPTX or PowerPoint files to narrative Markdown reading editions with markitdown. Trigger on 'md file', 'markdown', '.md', 'documento markdown', 'criar um readme', 'escrever documentação', 'write a spec', 'draft a guide', 'convert PPTX to Markdown', 'extract PPTX', or 'PowerPoint to Markdown'. Do not use for creating PPTX presentations, Word documents, diagrams, or PDFs.
2026-06-22