AI Agents for Beginners is a course that teaches the fundamentals of building AI agents through a sequence of lessons. People learning generative AI and agent development use it to study topics and frameworks including AutoGen and Semantic Kernel. The catalogue entries provide skills, instructions, and an agent related to the course.
Borrowing it
Nothing to install: this file belongs to microsoft/ai-agents-for-beginners. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/ai-agents-for-beginners/main/.agents/skills/deploying-scalable-agents/SKILL.mdgit clone --depth 1 https://github.com/microsoft/ai-agents-for-beginnersWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/microsoft/ai-agents-for-beginners/deploying-scalable-agents)<a href="https://agentmods.dev/skills/microsoft/ai-agents-for-beginners/deploying-scalable-agents"><img src="https://agentmods.dev/badge/skills/microsoft/ai-agents-for-beginners/deploying-scalable-agents/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/microsoft/ai-agents-for-beginners/deploying-scalable-agents"><img src="https://agentmods.dev/badge/skills/microsoft/ai-agents-for-beginners/deploying-scalable-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00197 | $0.01327 |
| Opus 5 | $0.00098 | $0.00664 |
| Sonnet 5 | $0.00039 | $0.00265 |
| Haiku 4.5 | $0.00020 | $0.00133 |
Grade A, and why
deploying-scalable-agents scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deploying Scalable Agents with Microsoft Foundry
Companion skill for Lesson 16 – Deploying Scalable Agents. Use it to help a learner move an agent from prototype to a scalable, observable production deployment. Ground every recommendation in the lesson content and the runnable notebook; do not invent Foundry APIs.
Triggers
Activate this skill when a learner wants to:
- Deploy an agent to Microsoft Foundry as a hosted agent and make it versioned/observable.
- Choose between client-hosted, hosted-agent, and agent-workflow deployment patterns.
- Add model routing, response caching, or bounded concurrency to control latency and cost.
- Add an evaluation gate so a bad agent version cannot ship.
- Add a human-in-the-loop approval step for high-risk actions.
- Instrument an agent with OpenTelemetry tracing for production observability.
- Smoke-test a deployed agent as a fast post-deploy gate.
Core mental model
A production agent is mostly the operational skeleton around the model (~80%), not the model itself. Map every recommendation to one of these concerns:
| Concern | Prototype → Production |
|---|---|
| Hosting | notebook → versioned hosted service |
| Identity | your az login → managed identity + scoped RBAC |
| State | in-memory → externalised thread/memory store |
| Failure | traceback → retries, fallbacks, alerts |
| Cost | "a few cents" → tracked, routed, cached, budgeted |
| Quality | eyeballing → automated evaluation gate |
| Trust | you approve → policy + human-in-the-loop |
Deployment patterns (pick one, or combine)
- Client-hosted — the reasoning loop runs in your process. Max control; you own scaling/state.
- Hosted agent (Foundry Agent Service) — Foundry hosts the loop, stores threads, enforces RBAC/content safety, shows the agent in the portal. Less control, far less operational surface.
- Agent workflow — multiple agents/tools composed into a graph with branching, approval nodes, and durable checkpoints.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 107 lines · 197 tokens per session scan A dacdcaca3180
deploying-scalable-agents is a skill published in the GitHub repository microsoft/ai-agents-for-beginners (74,246 stars, last pushed 13d ago), licensed MIT. It adds 197 tokens to every session and 1,327 once invoked, about $0.0010 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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