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Back to the labJEVLAB / FIELD NOTES
Fresh from the lab
A dated reading list of newly added resources and JEVLAB NEWS. Come back for what changed, or follow the RSS feed in your own reader.
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Dates show when an item became available in JEVLAB, in UTC, not when its original source was published. Translation-only edits do not count as new resources.
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jev-trade
This repository provides a live trading implementation for the Hyperliquid platform using Jev. It demonstrates how to integrate automated trading logic with the exchange's API to execute market operations in real-time.
github.comLLMs vs. Jev Comparison
This resource contrasts Jev with LLMs, highlighting how Jev evaluates predefined decisions directly. It demonstrates how this architectural difference allows for the parallel processing of independent questions, distinguishing its operational approach from standard generative language models.
x.comJevPromptCoach
JevPromptCoach is a Claude Code plugin that evaluates your coding agent prompts. It tracks your prompting habits over time using the TypeSafe Jev model, aiming to provide feedback on your interaction quality without introducing additional latency.
github.comAgent-JEV-Tetris
This project demonstrates an implementation of the JEV model applied to the classic game Tetris. It serves as an experimental showcase for how the model handles real-time decision-making and spatial logic within a structured gaming environment.
github.comYouTube sponsor skipper
This Chrome extension utilizes Jev to identify and automatically bypass sponsor segments within YouTube videos. It demonstrates a practical application of real-time content analysis to streamline the viewing experience for users.
x.comJev and Fable 5.1 Builder Challenge
This event features 100 developers using Jev and Fable 5.1 to build a post scheduler. The demonstration highlights the speed of the Jev framework during rapid application development cycles.
x.comllama-index-jev
This project demonstrates integrating LlamaIndex reranking and routing with TypeSafe Jev. It explores using typed scores and choices to manage decision-making processes, aiming to provide a more cost-effective alternative to traditional LLM-as-judge evaluation methods.
github.comFraud Detection with Jev and Kimi K3
This project demonstrates a multi-layered approach to email fraud detection. It utilizes Jev for initial classification, while delegating uncertain cases to Kimi K3 to improve overall accuracy in identifying potentially malicious communications.
x.comWhose Jev Is It Anyway?
This creative experiment explores the potential role of Jev within the context of improv comedy judging. The author presents a hypothetical framework for how automated systems might evaluate spontaneous performance art.
x.comai-cli
This command-line interface tool by Vercel Labs enables developers to interact with AI models directly in the terminal. It demonstrates how to integrate Jev as an evaluation model for automated performance testing and quality assessment tasks.
github.comjev-decisions
This repository provides safety validation mechanisms for AI agents like Hermes. It demonstrates how to implement automated checks that require human approval or verification before an agent executes specific actions or modifies system states.
github.comjev-pr-labeler
This tool automates GitHub pull request labeling by applying Jev-based typed decisions. It categorizes changes based on conceptual scope rather than traditional line counts to provide more meaningful context for code reviews.
github.comscam-shield
This tool utilizes the Jev model to filter incoming text messages for potential scams. It demonstrates a practical application of TypeSafe AI technology for enhancing mobile communication security through automated content analysis.
github.comdaf-jev
This Python toolkit provides a modular framework for interacting with the Jev decision API. It features tools for building questions, implementing confidence gates, and managing agent skills through a dedicated CLI and MCP server interface.
github.comtypesafe-on-neon
This project provides a Neon Function proxy designed for the Neon AI Gateway. It demonstrates how to implement TypeSafe Jev routing to manage AI service requests within a structured and reliable development environment.
github.comjev-skill-router
This project demonstrates an implementation of Jev for intelligent skill routing within an agent-based architecture. It showcases how community-driven development patterns can be applied to manage task distribution and decision-making processes in autonomous systems.
x.comJev plays Geometry Dash
This community experiment showcases Jev interacting with the platformer game Geometry Dash. It demonstrates the model's ability to process visual gameplay input and execute corresponding control commands within a real-time gaming environment.
x.comFunction calling
This official TypeSafe AI reference explains the mechanics of function calling. It demonstrates how to integrate external tools and structured data processing into LLM workflows to improve task execution and enable dynamic interaction with external systems.
docs.typesafe.aiMaxFusion Ad Library Processing
This demonstration showcases Jev processing a large volume of advertising data. The creator claims the system can handle nearly two thousand ads in under twenty seconds, suggesting potential for high-speed market analysis workflows.
x.comjev-mcp
This proof of concept demonstrates an implementation of the Model Context Protocol for the Jev AI model. It serves as an experimental integration tool for developers exploring Jev connectivity within agentic workflows.
github.comjev-code
This project provides an interactive TypeScript CLI that utilizes Jev for typed routing and decision-making. It demonstrates the implementation of validated formal trees to structure and execute code-based agentic workflows.
github.comJev System One Overview
This resource outlines the core functions and evaluation metrics of Jev, presented as the System One model by TypeSafe. It provides an overview of how the system operates and the criteria used to assess its performance in agentic workflows.
skillsagentes.comdsh-jev-tools
This project integrates Jev into the DeepSeek Harness framework. It demonstrates how developers can utilize Jev for automated judgment tasks within existing evaluation pipelines to streamline model assessment workflows.
github.comJev Skill Installation Guide
This guide provides instructions for installing Jev skills. It explores the potential for these specialized modules to serve as an alternative to conventional large language model workflows by streamlining task execution within the Jev ecosystem.
x.comJev on Vercel AI Gateway
This resource provides a hosted implementation of typesafe-ai/jev for AI SDK evaluate calls. It demonstrates how to integrate Jev directly through the Vercel AI Gateway, bypassing the need for a separate TypeSafe waitlist for these specific operations.
vercel.comJevcal confidence-threshold calibration
This open-source tool provides a mechanism for calibrating confidence thresholds within Jev systems. It demonstrates a practical approach for users to adjust sensitivity settings to better align model outputs with specific operational requirements.
x.comLogical-fallacy detector
This Brave browser extension analyzes social media posts to identify logical fallacies in real time. It marks content with a green flag when it detects well-reasoned arguments, aiming to assist users in evaluating the quality of online discourse.
x.comjev-cua
This project provides a local computer-use interface tailored for Codex and Waku environments. It demonstrates a streamlined workflow for developers seeking to integrate automated task execution directly within their local machine setups.
github.comgg-friggin-ez
This Node.js library utilizes TypeSafe AI Jev to detect profanity and toxic language. It is designed to identify obfuscated text, including leetspeak and character spacing, across several Indian languages like Hindi, Bengali, and Telugu.
github.comharnessjudge
harnessjudge provides a framework for evaluating agentic workflows using TypeSafe Jev. It demonstrates how to systematically categorize agent steps as successful, requiring retries, needing escalation, or stopping execution based on defined operational logic.
github.comask-jev
This project demonstrates the use of the RLCD-type Jev model from TypeSafe AI to evaluate agentic coding sessions. The creator claims this approach provides an independent and cost-effective method for assessing automated programming tasks.
github.comjevmail
jevmail is an open-source tool that uses Jev to categorize Gmail messages into specific folders like Needs reply or Spam. The creator claims it processes 1,000 emails per minute locally while maintaining read-only access to your inbox.
github.comjev (dannote)
This library provides TypeSafe Jev integration for OTP environments. It demonstrates how to handle Jev replies within a GenServer process, allowing developers to perform pattern matching on the received responses for improved reliability.
github.comTypeSafe AI Demos
This official resource provides a collection of reference demonstrations for TypeSafe AI. It serves as a central index for users to explore practical implementations and verified examples of the platform's core capabilities and architectural patterns.
docs.typesafe.aiJev Drone Navigation Experiment
This experiment demonstrates Jev performing real-time obstacle avoidance for a drone navigating through a simulated asteroid field. The project highlights autonomous decision-making capabilities in dynamic environments.
x.comLitJev
LitJev is a reproduction of the Jev framework that enables Qwen models to function as decision-making engines. It implements the /v1/systemone schema to output choices and scores without requiring model training or generating additional text.
github.com
