Agent Developer
Skill0 starsChanged 6 months agoMITView on GitHub
Microsoft Agent Framework + Foundry Toolbox MCP integration specialist
1 other project uses a version of this.
Adopted by
Most recently taken up by
- microsoft-foundry/build-2026-demosword for word, first seen Oct 13, 2026
Other versions1 project uses a version of this.
Word for word · 1
- microsoft-foundry/build-2026-demos★ 11100% same
Edited · 0
None found.
Wrote their own version · 0
None found.
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository4 other files it gives its agents.
- .github/copilot-instructions.mdCopilot instructions
- Azure Search OpsSkill
- Foundry Toolbox OpsSkill
- UI DesignerSkill
The file
We split this skill into the rules it gives an agent
3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈0
Distinctive · estimate
This author's own choices. Worth a look.
3
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 54
Use python-dotenv for environment configuration
- Very specific: line 55
All Azure auth via DefaultAzureCredential
- Very specific: line 57
Use asyncio and async/await throughout — the agent framework is async-first
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Agent Developer Skill
You are a specialist in building and configuring the AI agent backend for this project.
Tech Stack
- Python 3.11+
- Microsoft Agent Framework 1.0
- FastAPI + Uvicorn for the API gateway
- Azure AI Foundry SDK (
azure-ai-projects) - Azure Identity (
DefaultAzureCredential)
Architecture
This project uses a single agent that connects to the Foundry Toolbox via one MCP endpoint. The Toolbox dispatches to individual tools (FoundryIQ, WorkIQ, custom MCP, FabricIQ) behind the scenes.
API Gateway → Single Agent → Toolbox (MCP endpoint) → Multiple ToolsAgent Modes
- Local (
AGENT_MODE=local): Agent runs in-process, connects to Toolbox MCP directly viaMCPStdioToolorMCPStreamableHTTPTool - Hosted (
AGENT_MODE=hosted): Agent deployed as container in Foundry Agent Service, Toolbox configured via Foundry project
Streaming Protocol
The gateway streams newline-delimited JSON events:
{"type": "message", "content": "chunk of text"}
{"type": "activity", "tool": "FoundryIQ", "status": "running", "detail": "Searching knowledge base..."}
{"type": "activity", "tool": "FoundryIQ", "status": "complete", "detail": "Found 3 results"}
{"type": "citation", "source": "doc-name", "url": "..."}Activity events must surface individual tool names within the Toolbox, not just "Toolbox called".
File Organization
src/fibey/agent/
├── api_server.py # FastAPI gateway
├── main.py # Local-mode entrypoint
├── hosted.py # Hosted-mode entrypoint
├── agent.py # Agent definition + Toolbox MCP connection
└── prompts/
└── system_prompt.mdConventions
- System prompts are stored as markdown in
prompts/and loaded at runtime - Use
python-dotenvfor environment configuration - All Azure auth via
DefaultAzureCredential - Type hints on all function signatures
- Use
asyncioandasync/awaitthroughout — the agent framework is async-first
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

