Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Tyler-R-Kendrick/agent-skills --skill microsoft-foundrygit clone --depth 1 https://github.com/Tyler-R-Kendrick/agent-skillsWrote 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/tyler-r-kendrick/agent-skills/microsoft-foundry)<a href="https://agentmods.dev/skills/tyler-r-kendrick/agent-skills/microsoft-foundry"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/microsoft-foundry/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/tyler-r-kendrick/agent-skills/microsoft-foundry"><img src="https://agentmods.dev/badge/skills/tyler-r-kendrick/agent-skills/microsoft-foundry.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00092 | $0.04482 |
| Opus 5 | $0.00046 | $0.02241 |
| Sonnet 5 | $0.00018 | $0.00896 |
| Haiku 4.5 | $0.00009 | $0.00448 |
Grade A, and why
microsoft-foundry 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 11d 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 — 583 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Microsoft Foundry Skill
This skill helps developers work with Microsoft Foundry resources, covering model discovery and deployment, RAG (Retrieval-Augmented Generation) applications, AI agent creation, evaluation workflows, and troubleshooting.
When to Use This Skill
Use this skill when the user wants to:
- Discover and deploy AI models from the Microsoft Foundry catalog
- Build RAG applications using knowledge indexes and vector search
- Create AI agents with tools like Azure AI Search, web search, or custom functions
- Evaluate agent performance using built-in evaluators
- Set up monitoring and continuous evaluation for production agents
- Troubleshoot issues with deployments, agents, or evaluations
Prerequisites
Azure Resources
- An Azure subscription with an active account
- Appropriate permissions to create Microsoft Foundry resources (e.g., Azure AI Owner role)
- Resource group for organizing Foundry resources
Tools
- Azure CLI installed and authenticated (
az login) - Azure Developer CLI (azd) for deployment workflows (optional but recommended)
Language-Specific Requirements
For SDK examples and implementation details in specific programming languages, refer to:
- Python: See language/python.md for Python SDK setup, authentication, and examples
Core Workflows
1. Getting Started - Model Discovery and Deployment
Use Case
A developer new to Microsoft Foundry wants to explore available models and deploy their first one.
Step 1: List Available Resources
First, help the user discover their Microsoft Foundry resources.
Using Azure CLI:
Bash
# List all Microsoft Foundry resources in subscription
az resource list \
--resource-type "Microsoft.CognitiveServices/accounts" \
--query "[?kind=='AIServices'].{Name:name, ResourceGroup:resourceGroup, Location:location}" \
--output table
# List resources in a specific resource group
az resource list \
--resource-group <resource-group-name> \
--resource-type "Microsoft.CognitiveServices/accounts" \
--output table
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 583 lines · 92 tokens per session scan A 3518dc4af790
microsoft-foundry is a skill published in the GitHub repository Tyler-R-Kendrick/agent-skills (11 stars, last pushed 3mo ago), licensed MIT. It adds 92 tokens to every session and 4,482 once invoked, about $0.0005 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 2026-08-31.
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