Ruflo is a multi-agent orchestration platform for AI coding agents (Claude Code, Cursor, Codex, Copilot, Gemini, Amp, +12 more). Use this skill when the user wants to (1) install/init ruflo in a project, (2) run multi-agent swarms with hierarchical coordination, (3) use ruflo's 314+ MCP tools for memory, routing, hooks, sub-agents, or workflows, (4) check ruflo status/version/doctor health, or (5) discover which of ruflo's 30+ plugins fits their task.
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Take a working agent prototype to a scalable, observable production deployment on Microsoft Foundry. Covers deployment patterns (client-hosted, hosted agents, agent workflows), the agent lifecycle, model routing, response caching, evaluation gates, human-in-the-loop approval, observability with OpenTelemetry, cost optimisation, and smoke-testing deployed agents with the AI Smoke Test action. Based on Lesson 16 of AI Agents for Beginners. USE FOR: deploy an agent to production, scale an agent, Microsoft Foundry hosted agent, Foundry Agent Service, model routing, response caching, evaluation gate, release gate, human approval workflow, agent observability, agent tracing, agent cost optimisation, smoke test a hosted agent, production customer support agent. DO NOT USE FOR: building your first agent (start with Lesson 01), running agents locally on-device (use local-ai-agents / Lesson 17), Azure infrastructure provisioning unrelated to agents, non-Foundry deployment targets.
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Query official Microsoft documentation to find concepts, tutorials, and code examples across Azure, .NET, Agent Framework, Aspire, VS Code, GitHub, and more. Uses Microsoft Learn MCP as the default, with Context7 and Aspire MCP for content that lives outside learn.microsoft.com.
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Use when asked to validate, test, smoke-test, or run the course's notebook and code samples against a live Microsoft Foundry / Azure OpenAI configuration. Covers environment setup (.env, az login, packages), the scripts/validate-notebooks.ps1 runner, interpreting PASS/FAIL results, and which lessons need extra resources (Azure AI Search, GitHub MCP, Foundry Local, Playwright).
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الفئات التالية تقع **خارج** learn.microsoft.com. استخدم الأداة المحددة بدلاً من ذلك.
### Aspire — استخدم Aspire MCPServer (المفضل) أو Context7
مستندات Aspire تقع على **aspire.dev**، ليست في Learn. أفضل أداة تعتمد
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ব্যবহার করবেন
নিম্নলিখিত বিভাগগুলি **learn.microsoft.com এর বাইরে** রয়েছে। নির্দিষ্ট সরঞ্জামগুলি ব্যবহার করুন।
### Aspire — Aspire MCPServer (প্রাধান্যপ্রাপ্ত) বা Context7 ব্যবহার করুন
Aspire ডকুমেন্টগুলি **aspire.dev** এ থাকে, Learn এ নয়। সেরা
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přiřaďte každému hostovanému agentovi spravovanou identitu s nejmenšími právy.
- **MCP v produkci**: považujte každý MCPserver za nedůvěryhodnou hranici — připněte verzi, omezte jeho identitu, ověřujte výstupy, omezujte rychlost, nikdy nezveřejňujte
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hver hostet agent en administreret identitet med mindst privilegium.
- **MCP i produktion**: behandl hver MCP-server som en ikke-pålidelig grænse — fastlås version, afgræns identitet, valider output, rate-limiting, udsæt
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model til at styre pålidelige lokale værktøjskald.
- Tilføje **lokal RAG** (Chroma) eller en **lokal MCP-server**.
- Designe en **hybrid** lokal/cloud routingstrategi.
## Kerne mental model
En SLM bytter bredde for privatliv
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kategorier ligger **uden for** learn.microsoft.com. Brug det angivne værktøj i stedet.
### Aspire — Brug Aspire MCPServer (foretrukket) eller Context7
Aspire-dokumenter findes på **aspire.dev**, ikke Learn. Det bedste værktøj afhænger
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gehosteten Agenten eine Managed Identity mit minimalen Rechten.
- **MCP in Produktion**: Behandeln Sie jeden MCP-Server als unvertrauenswürdige Grenze — fixieren Sie die Version, begrenzen Sie die Identität, validieren Sie Ausgaben
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verwenden möchte, um zuverlässige lokale Werkzeugaufrufe zu steuern.
- **Lokales RAG** (Chroma) oder einen **lokalen MCP-Server** hinzufügen möchte.
- Eine **hybride** lokale/Cloud-Routing-Strategie entwerfen möchte.
## Kern-Mentalmodell
Ein SLM tauscht Breite gegen
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A folder with a SKILL.md file: a name, a description of when to use it, and instructions. Claude loads a skill only when the task matches its description.
How do I use one I find here?
Copy the folder into your project's .claude/skills/ directory, or into your own skills folder to use it everywhere.
What do the warnings mean?
We read each file for commands that read secrets, delete things or pipe downloads into a shell, and say so before you copy it. No warning is not a promise that a file is safe.
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