VERIFYAgents & automation

Jev Agent Evaluation

Sai Teja@saiitoshii

33 views · 2 likes on X · does not affect score

Jev is an agent evaluation tool that uses LLM judges to assess agent performance, offering a low-cost and accurate alternative to other evaluation methods.

TakeLangChain just put Jev in the agent-eval seat. same Deep Agents traces, three LLM judges vs TypeSafe's System One model.

Pattern✦ Agent trace evaluation with typed judges

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Agent Decision Layer

This project implements a decision layer that sits before expensive agent actions, determining whether to act, escalate, or involve a human based on confidence scores.

yankis@yankis0x

452 views on XJev score 79

Jev Decision Model

Jev is a typed decision model that returns a probability for a given state (question, answer, evidence) instead of generating prose or structured data, making it faster and cheaper than traditional AI judges.

Jose Luis Latorre | #MVP | #K6 | @DotNetZurich@joslat

40 views on XJev score 79

TypeSafe Computer Use

This project enables a Mac to achieve plain-English goals by combining OCR and the Accessibility tree to drive actions, avoiding large model loops for screenshots.

Yash Chaudhary@YashChaudhary

4 views on XJev score 78

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Jev Decision Layer for Voice Pipelines

Jev acts as a decision layer in voice pipelines, utilizing typed primitives like Noul (yes/no with probability), Choice (labeled decision), and Score (scalar on a defined rubric) to process conversational turns before and during LLM responses.

Himanshu@Fabulous_7781

72 views on XJev score 76