feat: add Microsoft Foundry skill status and benchmark doc

doc/microsoft-foundry-skill-status.md

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+# Microsoft Foundry Skill Status and Benchmark
+
+Status and benchmark results for the `microsoft-foundry` skill, with prompts you can use to reproduce the same tests.
+
+The `microsoft-foundry` skill is used by Copilot-assisted agent development in Microsoft Foundry Toolkit.
+
+**Source code:** [`microsoft/azure-skills/skills/microsoft-foundry`](https://github.com/microsoft/azure-skills/tree/main/skills/microsoft-foundry)
+
+**Quick links:** [Install the skill](#install-the-skill) | [Current benchmark](#current-benchmark) | [Run the benchmark yourself](#run-the-benchmark-yourself)
+
+## Install the Skill
+
+Install from `microsoft/azure-skills`:
+
+```bash
+npx skills add https://github.com/microsoft/azure-skills --skill microsoft-foundry
+```
+
+The skill installs to:
+
+```text
+~/.agent/skills/microsoft-foundry
+```
+
+## Verify the Installation
+
+Start a fresh GitHub Copilot CLI session and ask:
+
+```text
+Use the microsoft-foundry skill. What can you help me do?
+```
+
+The response should mention Foundry agent workflows such as scaffolding, local testing, deployment, invocation, and evaluation.
+
+## Current Benchmark
+
+The Foundry skill performs consistently across different Copilot models. The benchmark tested Claude Opus 4.8, Claude Opus 4.6, Claude Sonnet 4.6, GPT-5.5, GPT-5.4, GPT-5.3-Codex, GPT-5 mini, and MAI-Code-1-Flash.
+
+Representative results:
+
+| Copilot model | Time | AI Credits |
+| --- | ---: | ---: |
+| Sonnet 4.6 | 10 min 30 s | 100 |
+| Auto (GPT-5.3-Codex) | 9 min 30 s | 60 |
+| Free plan / cheapest (GPT-5 mini) | 11 min 30 s | 20 |
+
+These results measure time cost and GitHub Copilot AI Credits for this golden path prompt:
+
+```text
+Create a Python hosted agent for B2B customer onboarding and deploy it to a new Foundry project. Use the Responses protocol. After it is done, run in locally to make sure it can run successfully; then deploy it to foundry and ensure it can respond to users correctly
+```
+
+## Run the Benchmark Yourself
+
+### Prerequisites
+
+- Azure subscription
+- Azure CLI (`az`)
+- Azure Developer CLI (`azd`)
+- Python
+
+### End-to-end Testing
+
+Use the golden path prompt:
+
+```text
+Create a Python hosted agent for B2B customer onboarding and deploy it to a new Foundry project. Use the Responses protocol. After it is done, run in locally to make sure it can run successfully; then deploy it to foundry and ensure it can respond to users correctly
+```
+
+### Stage-by-stage Testing
+
+Use these prompts when you want to isolate one scenario instead of measuring the full end-to-end path.
+
+| Scenario | Prompt |
+| --- | --- |
+| 1a Configuration and scaffolding (greenfield) | `Create a Python hosted agent for B2B customer onboarding and set up whatever I need.` |
+| 1b Configuration and scaffolding (brownfield) | `I have an existing agent built with the OpenAI SDK. I want to deploy it as a Foundry hosted agent. What do I need to change?` |
+| 2 Local testing | `Help me run this agent locally and test it before I deploy.` |
+| 3 Deployment | `I'm happy with it locally. Deploy this to Foundry.` |
+| 4 Direct Toolbox iteration | `Add a WorkIQ tool to my deployed Foundry agent and redeploy.` |
+| 4-iter Casual iteration | `Can my agent also look up emails and meetings from my Outlook to help with onboarding?` |