AI Infrastructure · GitHub ·37 ★

EvalsforAgentsInterop

Redefine agentic evaluation in enterprise AI. By simulating realistic scenarios, these evals enables rigorous, multi-dimensional assessment of LLM-powered productivity agents.

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Details

Author
microsoft
Category
AI Infrastructure
Platform
GitHub
Framework
custom
Language
typescript
Stars
37
First indexed
2026-05-15
Last active
2026-04-02
Directory sync
2026-05-15
@microsoft

Overview

Redefine agentic evaluation in enterprise AI. By simulating realistic scenarios, these evals enables rigorous, multi-dimensional assessment of LLM-powered productivity agents.

Quick start

git

git clone https://github.com/microsoft/EvalsforAgentsInterop

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What EvalsforAgentsInterop can do

llmragdefi
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Defi — Interacts with decentralised finance protocols.

Frequently asked questions

What is EvalsforAgentsInterop?
Redefine agentic evaluation in enterprise AI. By simulating realistic scenarios, these evals enables rigorous, multi-dimensional assessment of LLM-powered productivity agents.
How do I install EvalsforAgentsInterop?
Use git: `git clone https://github.com/microsoft/EvalsforAgentsInterop`. Full setup details on the source page linked above.
Is EvalsforAgentsInterop open source?
EvalsforAgentsInterop is published on GitHub.
What are alternatives to EvalsforAgentsInterop?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for EvalsforAgentsInterop is sourced from GitHub, published by microsoft.

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