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.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
8/8 packs
Scoring metrics
0/8 packs
Judge rubrics
8/8 packs
Use-case maps
0/8 packs
Pack context
8/8 packs
Available eval packs for Microsoft AutoGen
8 packs ready to run.
Autogen Agent Definitions
Evaluates Microsoft AutoGen's Agent Definitions (AssistantAgent / UserProxyAgent) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Autogen Autogen Studio And Workbench
Evaluates Microsoft AutoGen's AutoGen Studio & Workbench across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Autogen Code Execution
Evaluates Microsoft AutoGen's Code Execution (Docker / Local) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Autogen Model Clients And Providers
Evaluates Microsoft AutoGen's Model Clients & Providers across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Autogen Multi Agent Teams
Evaluates Microsoft AutoGen's Multi-agent Teams (RoundRobin / Selector / Swarm / MagenticOne) across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Autogen Safety And Governance
Evaluates Microsoft AutoGen's Safety & Governance across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Autogen Termination Conditions
Evaluates Microsoft AutoGen's Termination Conditions across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
Autogen Tool Use And Function Calling
Tool SelectionEvaluates Microsoft AutoGen's Tool Use & Function Calling across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's Multi-agent Framework eval coverage.
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.