Eval directory
Evals for Microsoft AutoGen
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Microsoft AutoGen AI products.
About Microsoft AutoGen
Microsoft is a global technology company and a leading cloud and AI provider. Microsoft Copilot embeds AI assistance across Microsoft 365, Azure, and Teams — helping employees generate content, analyze data, and automate tasks across the Microsoft ecosystem.
Available eval packs for Microsoft AutoGen
8 packs ready to run.
Autogen Agent Definitions
Microsoft AutoGen evals — Agent Definitions (AssistantAgent / UserProxyAgent) (relift v3 InfraRed)
Autogen Autogen Studio And Workbench
Microsoft AutoGen evals — AutoGen Studio & Workbench (relift v3 InfraRed)
Autogen Code Execution
Microsoft AutoGen evals — Code Execution (Docker / Local) (relift v3 InfraRed)
Autogen Model Clients And Providers
Microsoft AutoGen evals — Model Clients & Providers (relift v3 InfraRed)
Autogen Multi Agent Teams
Microsoft AutoGen evals — Multi-agent Teams (RoundRobin / Selector / Swarm / MagenticOne) (relift v3 InfraRed)
Autogen Safety And Governance
Microsoft AutoGen evals — Safety & Governance (relift v3 InfraRed)
Autogen Termination Conditions
Microsoft AutoGen evals — Termination Conditions (relift v3 InfraRed)
Autogen Tool Use And Function Calling
Tool SelectionMicrosoft AutoGen evals — Tool Use & Function Calling (relift v3 InfraRed)
Why eval Microsoft AutoGen AI
Microsoft AutoGen's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for Microsoft AutoGen measures four dimensions teams care about most when deploying ai platform agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against Microsoft AutoGen's public product surface and runnable in Corsac with your own data.