Awesome Jev

Agent skills for building with TypeSafe's System One API

Drop-in TypeSafeClient replacement backed by LLM APIs

The official TypeScript/JavaScript library for the TypeSafe API

The official Python library for the TypeSafe API

Typesafe.ai System One Model Jev navigating a Neo4j graph by using a classifier over neighbouring relationships

High-throughput synthetic & pretraining dataset sifter powered by TypeSafe AI Jev (api.typesafe.ai). Stream, filter, and score Parquet & JSONL datasets at 1,500+ rows/sec using System One typed decisions (Choice, Score, Noul).

A curated list of tools, integrations, and experiments built on Jev, TypeSafe AI's System One model for fast, typed decisions.

A curated list of projects, integrations, and resources for Jev, TypeSafe AI's System One model.

An idiomatic, type-safe Elixir port of the official TypeScript AI SDK (ai / ai-sdk) providing unified LLM integrations, streaming text and structured outputs, tool calling, and agentic workflows. Jev is their current flagship model and is the first System One model.

OpenJev: an independent Jev-inspired System One decision API based on TypeSafe.ai concepts. Choice, score and noul primitives, local mock server, Python and TypeScript SDKs. Real inference planned; not affiliated with TypeSafe AI.

Community-maintained Go SDK for the TypeSafe AI System One evaluation API, with typed questions, fluent builders, retries, and examples.

Community Java client for the TypeSafe System One API (unofficial)

TypeSafe System One models (Jev) for RubyLLM: typed judgments, evaluations and reranking.

Automated database migration safety reviewer powered by TypeSafe AI (Jev System One model)

Decision circuits: typed questions to a System One model, calibrated probabilities back, gates in code. Zero-dependency Python SDK with LangChain, OpenAI Agents, and Claude Agent SDK integrations.

Typed decisions for AI agents as an MCP tool: yes/no probability (noul), choice, and score in one fast request. Backed by the TypeSafe System One model.

Ruby client for Jev, TypeSafe's System One model: typed questions, probabilistic answers. Zero runtime dependencies.

A curated list of TypeSafe Jev resources, SDKs, agents, MCP servers, integrations, benchmarks, examples, and open System One implementations.

Node.js bindings for TypeSafe's Jev — the System One model. Typed decisions, probabilities and confidence, with no text generation and no parsing.

grep for the questions you cannot write as a pattern. Reads every function instead of sampling a few. Powered by Jev, TypeSafe AI's System One model.

Open-weight System One model (Jev-compatible): calibrated noul / choice / score decisions in one forward pass, no text generation. Works with TypeSafe's typesafe-sdk unchanged.

Typed, calibrated decisions for Rust: a backend-agnostic client for System One models (TypeSafe AI's Jev), with cost-matrix decisions, caching, recording and calibration.

A usage-first curated list for Jev, TypeSafe's System One model: patterns, recipes, integrations, projects, and a tested cheatsheet.

A .NET client library for the TypeSafe AI System One API (https://api.typesafe.ai).

Small, standard-library-only Go library for typed decisions with Jev and other System One models.

Typed TypeScript client for Jev System One models, Choice, Score & Noul decisions with presets for TypeSafe, Zen & custom gateways

An Elixir SDK for Typesafe's API (https://docs.typesafe.ai/sdk)

Open-source AI Trading OS, agent trading, and vibe trading, with Jev System One integration. Research, build Python strategies, backtest, and paper/live trade across crypto, stocks, and forex. Launch your own multi-tenant trading SaaS with built-in user management, billing, payments, and settlement.

Ask your Postgres tables questions in plain language. A PostgreSQL extension powered by TypeSafe's Jev.

Build calibrated AI Functions from human feedback using Jev and GEPA.

One TypeScript interface for 40 AI providers across three inference types — generate, stream, and decide. Decide returns typed, calibrated judgments (boolean/choice/score) via TypeSafe Jev, not text. MCP-native, voice (TTS/STT/realtime), RAG, memory, file processors. Powers Tara, Yama and Clairvoyan

Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.

Jev / TypeSafe System One 中文精选列表：官方资料、SDK、爆款应用、Agent 工具、开源复现与独立评测，附中文上手指南，每日自动收录 GitHub 热门项目。

Open-source AI email triage for Gmail. Sorts your inbox into Needs reply, Updates, Promos, Sales and Spam with Jev, TypeSafe AI's decision model, via Vercel AI Gateway. Read-only, runs locally, 1,000 emails in about a minute for 3 cents.

Ask your house a question, get a number back. Home Assistant integration for TypeSafe Jev: typed answers as sensors, four actions for automations, and a conversation agent for Assist.

Use cultivar to test your Agent Skills and Docs by running them in sandboxes, and across different agents.

ACP and MCP adapter that bridges TypeSafe Jev with any LLM — computer use and typed decisions alongside Codex, Claude, Grok, and OpenCode.

MCP server that puts TypeSafe Jev on the coding loop in Cursor, Codex, and any MCP client

Calibrate Jev questions against your own labels: tune criteria on labelled examples, confirm on a held-out set, get a verdict per question. Unofficial.

用 TypeSafe Jev 推荐已安装 Skill / Bounded installed-skill recommendations with TypeSafe Jev. Python CLI, Codex skill, bilingual docs and live examples.

100% free ₹0 agent-first SEO & GEO CLI suite and MCP server in Rust replacing Semrush and OpenSEO via DuckDuckGo and TypeSafe Jev System One https://akashpriyadarshii.github.io/jev-seo/

TypeSafe Jev for OTP: reply to Jev from a GenServer and pattern match on its answer

A simple Spring Boot 4 starter for TypeSafe Jev using Spring MVC and RestClient

Stops AI coding agents from claiming work is done without evidence. Deterministic hooks decide, TypeSafe's Jev advises. Append-only ledger, zero runtime dependencies.

Read-only trading journal and review harness: Jev typed judgments, agent integration, and a reproducible finance benchmark. No orders, no advice.

Typed semantic decisions for Unix pipelines and CI, powered by TypeSafe AI Jev.

Jev-powered conversation memory: find past sessions and revisit decisions with original sources. A macOS workspace for OpenAI Codex. Manage AI conversations and agents, explore code with CodeGraph, and work with Git, Ghostty terminals, and Apple Notes in one app.

Command-line tool for TypeSafe's Jev AI model

Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell

The decision layer for your Rails app. A Rails-native wrapper around TypeSafe's Jev System One API: typed, calibrated decisions in your control flow.

if you're experimenting with jev it will be easier from here

Systematic software development framework for AI coding agents upgraded with TypeSafe Jev System One typed decisions

Command-line tool for TypeSafe AI's Jev model. Ask yes/no, multiple-choice and rubric questions about any text and get calibrated probabilities back. Answers become exit codes for shells and CI, JSON for scripts, and MCP tools for AI agents.

Software, by reflex. A sentence becomes a call of a small program, chosen by Jev, TypeSafe AI's classifier, and run only when it is sure enough. Reflexes are recipes anyone can write, share and improve. A CLI you talk to, a package manager for reflexes from git, and a TypeScript SDK.

SDK-first, independently maintained SemIf fork for fast, self-hosted semantic decisions.

Jev-powered, rule-based grader for text files. Runs every rule against every line in parallel. No skimming, no missed lines.

Semantic decisions as ordinary Ruby — feels?, decide, score, Rails validations and pattern matching powered by Jev

Connect JEV to MCP clients and compare its judgments against general-purpose LLMs using shared datasets and measurable accuracy.

Every code file in a pull request, judged against Uncle Bob's Clean Code by TypeSafe's Jev, then reviewed by Luna. Built on eve and Next.js.

Aside agents decide with TypeSafe Jev (System One: Choice/Score/Noul). Not a Cua binding — Jev is the model, Aside is the browser runtime.

Community .NET SDK for the TypeSafe AI System One API — typed noul, choice, and score questions with structured, confidence-scored answers. Not affiliated with TypeSafe AI.

One grounded Jev/Playwright core: typed SDK, persistent CLI, and MCP server with native browser operations and deterministic assertions.

daf-jev: composable Python toolkit for TypeSafe's Jev (System One) decision API — question builders, confidence gates, evaluator, calibration, CLI, MCP server, agent skill

R client for the TypeSafe Jev System One API

Go client for TypeSafe's System One API and its model Jev: typed judgments and calibrated probabilities instead of generated text

Shift every LLM call to the cheapest model that can handle it. Routing decided by TypeSafe Jev in ~180 ms. No training data. Policy in plain YAML. TypeScript and Python.

Idiomatic Java SDK for TypeSafe AI Jev System One decision engine

Community Go SDK for TypeSafe AI Jev / System One

Agent skill and CLI that turn natural language, an LLM prompt, or the code that runs one into a TypeSafe Jev decision: typed state, Choice/Score/Noul questions, and a runnable script

Async Python client for TypeSafe Jev. Typed questions in, probabilities and choices out, no prose to parse.

Sub-second Git pre-commit & pre-push semantic reflex gate powered by TypeSafe AI Jev

Zero-hallucination open-source repo and crate scout powered by TypeSafe AI Jev System One scoring

Browser use for coding agents, 3-5x faster than browser-use. MCP server + CLI; TypeSafe Jev decides every step in ~300 ms.

Unofficial Laravel integration for TypeSafe Jev AI with typed responses, async requests, scoped dependency injection, and testing fakes.

Community-maintained history of Jev / TypeSafe System One APIs, SDKs, agent guidance, and engineering best practices.

MCP server for typed decisions with Jev / System One via OpenRouter or TypeSafe

Use the TypeSafe Jev decision model (System One) anywhere: zero-dependency OpenAI-compatible bridge for 9Router, Claude Code, Cursor, Cline & any OpenAI SDK. Typed yes/no, choice & score judgments via CLI or HTTP.

Portable System-1 decision layer for agent harnesses with host-owned routing, receipts, replay, and fail-open integrations.

Local-first document evaluation workspaces powered by Jev

Dependency-free Go client for TypeSafe AI's System One API and the Jev model

用 TypeSafe Jev 给 AI coding agent 做持续代码质量 review 的校准审计层。持久化 19 维质量分数，输出趋势矩阵、假阳性置信检测、rubric 漂移与 ECE 校准曲线。Node 22+，零运行时依赖，CLI + GitHub Action，直接消费 jev_review 的 MCP 评估结果。

A Go client for the TypeSafe AI's System One API and its model, Jev.

Ultra-fast, fail-open advisory decisions and verbatim extractive reading view for AI coding agents and CLI pipelines

Go Jev harness for Claude Code, Codex, and Grok Build. No npx. Not an MCP server.

Let Claude code, chatgpt codex or control your own Chrome. Chrome extension + MCP server: Jev, TypeSafe's decision model, picks each click in ~0.5 s for a fraction of a cent. MIT, bring your own OpenRouter key.

Typed AI decisions for .NET: ask Jev (TypeSafe AI System One) yes/no, choice and score questions and get a C# enum with calibrated probabilities back.

Route form submissions to the right people with Jev and AI SDK.

Idiomatic Go SDK for the TypeSafe AI API

Pi Jev System One integration with TypeSafe Direct and Vercel AI Gateway transports

Agent skill for TypeSafe AI's Jev decision model: fit assessment, integration recipes, calibration, multi-Jev, benchmarks

Unofficial community Jev SDK for .NET 10. Typed decisions, examples, tests and NuGet packages.

A local MCP server that uses TypeSafe Jev to confidence-gate an AI agent’s next step, routing uncertain decisions to proceed, deeper review, or human input.

Use the Jev (System One) decision-model paradigm with any OpenAI-compatible LLM — no TypeSafe key required. A jev_decide tool for DeepSeek Harness (dsh).

Jev-backed guardrails for agent tool calls: library, native OpenCode/Hermes/DeepSeek Harness hooks, and a hosted eval-credit service.

Command-line tool for the TypeSafe Jev decision model, through the official API or OpenRouter: typed yes/no, choice and score questions with calibrated confidence, and confidence gating as exit codes.

A Claude Code skill for TypeSafe's Jev (System One) model — Choice/Score/Noul design guidance, patterns, and SDK reference.

Typed client and benchmark harness for Jev, TypeSafe AI's System One decision model, through the Vercel AI Gateway. Measure accuracy, calibration and cost on your own data before you trust a threshold.

Haskell client for TypeSafe's System One (Jev) decision API — typed, batched Choice/Score/Noul over http-client

CLI and MCP server for TypeSafe's Jev model, built for scripts, agents, and automation.

Season stats lie by omission. Sabr-Jev grades Batter|Pitcher seasons with typed AI judgments behind a confidence latch: act, review, or escalate — full probabilities, never hype.

A wrapper that gets more value out of TypeSafe's JEV model: transcript compaction, cost-control modes, and a local usage ledger for Claude Code and Codex.

Agent-ergonomic CLI for TypeSafe Jev: typed judgments (choice, noul, score) for agents

Jev 优质应用与生态精选｜System One 决策模型：开源应用·SDK·平台集成·开源复刻·教程 | curated apps & SDKs for TypeSafe AI's Jev model

Offline $0 decision layer for coding agents: Choice/Score/Noul primitives, BELKI confidence gatekeeper, ultra-planning, red-teaming, research and RLVR self-improvement -- as an MCP server + CLI + Claude Code skill.

A configurable OpenAI-compatible model router using Jev decisions, with a trace and control UI.

A live, graphical dojo for TypeSafe's Jev (System One) typed decision model — routing, a Tetris-playing agent, parallel swarms, and an honest Jev-vs-Claude gauntlet.

¿Jev entiende tu acento? Pre-registered audit of TypeSafe AI's Jev on Spanish — accuracy, calibration and token cost — plus a CLI to run the same comparison on your own labelled data.

Typed Go client for the TypeSafe System One API (Jev): structured questions and answers your code can act on. Community SDK, MIT.

An unofficial Go client for TypeSafe's System One Jev model

Score every Cognigy conversation against rubrics you write, using TypeSafe Jev instead of an LLM. CLI, local web UI, and an agent skill.

Jev-compatible adapter for vLLM: use any vLLM-served LLM for Choice, Score, and Noul decisions via logprobs—without modifying the model or vLLM service.

Typed decision model judge for GitHub PRs — sub-second, ~$0.0001 per triage (TypeSafe Jev via OpenRouter)

Jev-style /v1/systemone API in front of any OpenAI-compatible LLM server (one-token logprob scoring, MIT)

jev × DeepSeek Harness: System One decision client, MCP server, per-turn router and effort plugins

jevkit: fast typed decisions for agents. CLI and MCP tools (route, triage, guard, grep, rank, compact, judge) on TypeSafe Jev. Zero dependencies.

Email triage app built around Spark CLI and TypeSafe Jev. Early development: TanStack Start, React and TypeScript; email integration is not implemented yet.

用 TypeSafe JEV 对 HTTP/应用 payload 做落地检测，覆盖 XSS、SQL 注入、XXE、命令注入、路径穿越、SSRF、SSTI 等常见类型。一次 system_one 调用同时给出攻击概率、攻击类型和严重度，再按阈值决策放行、复核或拦截。提供 CLI 与 FastAPI 接口，便于接入 WAF / 网关。

Biologically-inspired memory for AI agents. Decay, retrieval strengthening, consolidation. Zero runtime deps, SQLite, MCP. Benchmarked retrieval with an opt-in TypeSafe Jev reranker.

A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.

Pre-alpha PostgreSQL extension for TypeSafe AI (Jev) categorical classification

Ruby client for decision models such as Typesafe Jev

⚡ Adaptive multi-model LLM router — 80+ providers, Jev System One single-pass routing (model=jev-auto), pheromone-trail failover, parallel ensemble merge. npm: adaptive-memory-multi-model-router

Jev decision layer for agents: MCP server, embeddable DecisionModel library, and an escalate-only Claude Code plugin (TypeSafe AI's Jev)

Independent async and blocking Rust SDK for the TypeSafe AI System One API

Ask Jev typed questions from the shell: noul, choice, and score answers as numbers, not prose

System One TypeSafe AI Rust Client (unofficial)

CLI and agent skill for TypeSafe System One (Jev): typed Choice, Score, and Noul judgments.

A VGI worker exposing TypeSafe System One questions (choice, noul, score) to DuckDB/SQL as LATERAL-joinable table functions

Claude Code plugin that replaces the compaction summary with Jev decisions: every tool call and result is scored in one fast request, stale ones are dropped or truncated, everything kept stays verbatim.

Route to the cheapest model in claude code for your task using jev-router

Per-turn model & reasoning routing for Codex, driven by Jev (TypeSafe System One): picks the model, thinking depth and speed mode for every turn.

Fastest and cheapest web agent

Awesome Jev: a source-backed field guide to TypeSafe's System One model, with SDKs, live demos, agent tools, and independent evaluations.

A source-backed Jev project directory with a reusable Jev-only GitHub review workflow.

A skill for writing and improving programs that call Jev, TypeSafe's System One model

Typed decisions with TypeSafe's Jev, the first System One model

A curated list of Jev use cases, projects, SDKs, and resources. Jev is TypeSafe AI's System One model for fast, typed decisions in software — Choice, Score, and Noul with calibrated probabilities.

A calibrated context sieve for Claude Code: every tool result is judged by a System One model before it enters context.

NanoJev Snake Arena: 1v4 human-vs-AI battleship + 100-agent swarm simulator. Local demo of Jev System-One model (open-source mini replica).

Agent skill for the decision-model class (classifiers, encoders/decoders, specialized AR heads, System One). TypeSafe Jev is the dominant exemplar. Composition algebra, question design, validation gates. MIT.

⚡ Foq — the FREE, local, open-source alternative to Jev. Typed System 1 decisions in ~25 ms — no waitlist, no cloud, no per-token cost. foq.fr

Local, open-source Jev alternative: browser agent decisions with Laya (System One model) on your own machine. No cloud, no API key. Playwright/CDP, MCP-friendly.

Verdict-based context compaction for DeepSeek Harness — replaces lossy LLM summaries with fast keep/truncate/drop decisions from jev-latest; everything kept stays verbatim. Port of tamaratran/fast-jev-compaction.

MCP server wrapping TypeSafe's Jev System One models — typed noul/choice/score judgments for AI agents

An eval-first MCP server for TypeSafe's Jev, a System One model that returns typed judgments (noul, choice, score) with probabilities instead of generated text.

Hands-on research lab for TypeSafe's Jev (System One model): reproducible benchmarks of Noul/Choice/Score primitives, confidence gating, fan-out latency, agent control — plus a living audit of the Jev ecosystem.

Claude Code & Codex skills powered by Jev, TypeSafe's System One model. 256 calibrated judgements for $0.0005 in 0.72s — 360x cheaper than Claude Opus 5. Includes the first published Jev calibration curve, measured on 4,995 real agent decisions.

Experimental opt-in Jev skills and config for Claude Code — the companion to jev-codex-tools.

Native SystemOne (Jev) provider for CLIProxyAPI: chat-compatible jev-1.13 models with weighted key pool and failover

TypeSafe AI is a San Francisco AI lab building System One models — a class of model trained to return typed, calibrated decisions for software instead of generated text. Its flagship and first System One model, Jev, is served by a single HTTP endpoint: POST /v1/systemone takes a state (a string, JSO

A playground for TypeSafe AI's Jev (System One model), built around five real production workflows: support triage, RAG relevance gating, agent action firewall, inline moderation, and CI eval judging.

Preregistered calibration test of TypeSafe Jev 1.13 as a judge of agent completion reports (2026-09-20): protocol, errata, harness, corpus, result

Makes Claude Code and Codex ask whether a step needs a generative LLM at all — or whether it belongs on Jev, TypeSafe's System One model. Architecture arbitrage before the code is written.

Decision Maker at Meteora - a decision agent for Meteora DLMM liquidity on Solana. Named after Jev, TypeSafe AI's System One model (https://console.typesafe.ai/home), which answers its typed Noul and Score questions. Ranks the live pool universe, runs live rug cards, and holds 3-5 pools under explic

UiPath bring-your-own-guardrail connector backed by the TypeSafe Jev System One model: plain-language agent policies enforced as calibrated probabilities.

TypeSafe Jev 1.13 vs Claude Fable 5.1, GPT-6 Astra, Kimi K3, MiniMax M3 and DeepSeek V4.1 Flash on 200 typed decisions: accuracy, calibration, agreement with 100 human annotators, latency and cost

Map where Jev and System One models actually belong in your project, test the strongest ideas, then implement them. A skill for Claude Code and Codex.

AI agents can generate code, but still struggle to understand what they build. Reticle brings Jev-style machine-native runtime perception to web & desktop applications.

A staged code-review workflow and local dashboard built with TypeSafe Jev.

Jev-powered model routing, memory, compaction, skill selection, computer and browser use for Hermes agents (also Claude Code and Codex)

An awesome collection of Jev use cases, workflows, and agent skills.

5–10x faster browser operations: Jev clicks, Codex thinks and verifies. Built at EZCollegeApp.

Awesome Jev: source-backed open-source ecosystem radar, plain-language project discovery, and automatic GitHub sync

Calibrated 151M Non-Autoregressive Decision Engine beating TypeSafe Jev & Laya on LocalLLaMA/typed-decisions (77.10% acc, 0.0636 Brier, 0.0144 ECE)

Fast, cheap, typed judgments from TypeSafe's Jev model, as MCP tools.

Local-first MCP plugin for continuous software-quality review by AI coding agents, powered by Jev.

A lightweight Jev-powered router for models, tools, and subagents

Claude Code plugin: trim long Bash output with TypeSafe Jev before the model sees it

TypeSafe Jev as a decision layer for the Pi coding agent: a measured tool-call gate plus jev_ask for typed, calibrated answers

Camera-only autonomous drone in MuJoCo with a small judgment model (TypeSafe Jev) in the loop at 2.5Hz

Agentic RL 中文零基础教程（25 章）：从概念到 GRPO 实战，含 TRL 最小可跑示例。第 25 章讲清 Jev / TypeSafe System One 判别模型与 RL 的能力边界 | Chinese Agentic RL tutorial, 25 chapters + Jev-vs-RL boundary analysis

An easy way to use jev with your coding agent for tool calling reasoning

Code quality and coverage for coding agents

Connect TypeSafe Jev to Grok Bot as a cheap decision layer - usage gates, skill template, examples

Awesome list of TypeSafe AI Jev use cases: 74 demos ranked by likes, 150+ GitHub repos, limits, cost and API examples. CC0, sponsored by AY Automate.

TypeSafe Jev action selection inside Codex Computer Use

Jev-powered Instagram, TikTok, and LinkedIn research: typed routing, real browser evidence, streamed post cards, video capture, and cited socai reports.

Skill for Hermes, and other agents, to ask typesafe's jev

Open reproduction of TypeSafe Jev: a 150M typed decision engine (noul/choice/score in one non-autoregressive pass, calibrated confidence). 0.697 vs Jev's 0.727, 2.5x better calibrated, 4x faster, free. Trains on a Colab T4 in 30 min.

Agent evals and guardrails in one request. Built on Jev, Kev and Laya.

Retrieve by relevance, not resemblance: filter an AI assistant's memories with TypeSafe's Jev

Semantic tool routing and typed System One decisions for the Pi coding agent using TypeSafe Jev

A prose linter that sniffs out AI writing tells. Zero dependencies, countable rules plus one judgment model.

Independent, evidence-based map of when TypeSafe's Jev actually holds up vs. breaks down — real API-call receipts, not a leaderboard. 中文為主的雙語 repo。

Rank Pi Agent Skills for the current task with TypeSafe Jev

An agent skill to discover TypeSafe Jev opportunities, design typed questions, and learn from recent community experiments.

Context-pruning proxy for Claude Code and Codex: Jev judges which history is still needed, measured not claimed. POC here now, heading soon into https://github.com/compozy/compozy

Jev (TypeSafe System One) backed auto mode for the Pi coding agent: semantically auto-approves bash, write, and edit tool calls and fails closed when a decision cannot be made.

📡 全网最全 · The world's most comprehensive tracker of the Jev (TypeSafe AI System One) ecosystem — 220+ documented cases · 108 confidence-graded entries · verified & rescanned every 3 hours · API access guide included

🚀🚀 A 0.8B JEV-like multimodal model playing GUI games directly from raw pixels.

Jev-powered search infrastructure for AI agents: zero API keys, MCP-ready, LLM-context aware, with local neural evidence verification.

Evidence-backed index of real-world Jev (TypeSafe AI System One) use cases: repos, patterns, benchmarks, and measured results

Open-source, local decision models inspired by TypeSafe’s Jev and System One - built on Qwen3 for NVIDIA DGX Spark.

Configurable semantic linting powered by Jev, with file-level NOUL judgments and a magic-strings plugin.

The agent loop where decisions don't cost a large language model call. Zero deps, runs offline, no API key needed.

TypeSafe (Jev) skill routing for Hermes Agent: names the one skill worth loading, before the model call. Opt-in, stdlib only, ~$0.001 per routed turn.

Hand the browser work off: an MCP server where a decision model drives the page for your agent, so a flow costs one tool call instead of a turn per click. Ref-based element tables, code-checked assertions, zero-model macro replay. Speaks CDP to your Chrome.

AskJev — Jev autopilot for any website + guard on irreversible clicks (TypeSafe System One, not Claude)

A language for safe, universal spatiotemporal composability (Cordis paradigm) and orchestration.

Jev-powered MCP tool routing for Codex

Jev-Mem: System-One Controlled Agentic Memory

Pure Jev that can "type" and drive towards task completion.

Paper trading agents on a live tape, decided every second by TypeSafe's Jev (System One). Electron desktop app.

Natural-language MCP tool dispatcher powered entirely by TypeSafe's Jev — no general-purpose LLM. Discovers a simple MCP server's tool signatures at runtime and uses Jev's typed primitives (Choice/Noul) to pick the right tool and extract its arguments straight out of the sentence.

TypeSafe Jev (System One) decision tools for Hermes Agent: jev_check / jev_route / jev_score / jev_evaluate

Jev (TypeSafe System One) vs Claude Opus 5 driving a simulated robot arm in MuJoCo

DSH bundle that registers jev_ask for TypeSafe Jev noul, choice, and score answers.

Jev-powered tool and skill selection, context search, and output triage for Codex via MCP

Jev (System One decision model) plugin suite for DeepSeek Harness (dsh)

Jev (TypeSafe) vs Claude Haiku 4.5 on 2 000 phishing emails: accuracy, calibration, latency, cost. Reproducible benchmark.

A Codex overlay incorporating JEV to make the best decisions regarding model selection and depth of reasoning. All while automating the process via an automated Kanban system.

A UiPath coded agent with a custom PII detection guardrail on the LLM boundary, built on the TypeSafe Jev model as a LangChain awrap_model_call middleware.

A curated list of resources for Jev — TypeSafe AI's System One decision model. Maintained by RoboKrunch.

System-architecture skill for TypeSafe AI Jev/System One — find fuzzy semantic judgment and turn it into small Choice/Score/Noul primitives.

Route any task to the right AI agent in under 1 second using Jev (TypeSafe System One). Supports Claude, ChatGPT, Cursor, and Antigravity with auto-launch on macOS, Windows, and Linux.

A local proxy that sits between Claude Code and the Anthropic API and uses TypeSafe's Jev to route each subagent to the model the task actually needs. Your main conversation keeps whatever model you picked

Java/Spring Boot MCP server for TypeSafe Jev

Millisecond-class test-failure triage for coding agents: RETRY / FIX_CODE / FIX_ENV, powered by TypeSafe Jev.

Lightweight MCP server exposing TypeSafe Jev decision tools via OpenRouter for Hermes Agent

Framework for agents on TypeSafe Jev: turns candidates into valid Jev questions and answers into validated choices; loop, cross-checks, fallbacks and traces built in. No network code.

MCP relay that adds use_jev to every server: Jev picks the tool calls, the calling model writes the values Jev cannot choose, the relay executes. Built on jev-dev-kit.

Jev Engineering: Typed Decision Systems for Reliable Agent Workflows. Paper, diagrams, and companion examples by Av1dlive.

INSTRUCT_JEV - TypeSafe AI Jev / System One instruction corpus (choice/noul/score), compiled by DeckerGUI. 119 rows. Mirrored on HuggingFace.

Independent, source-linked research on TypeSafe AI's Jev (System One), with 947 rubric-scored public repositories, recurring patterns, datasets, and bilingual documentation.

MCP-first toolkit for TypeSafe/Jev — the System One decision model. One stdio server (jev mcp) serves any MCP-capable harness, backed by one local event log and Prometheus impact metrics you can scrape into your own Grafana.

音视频结构化分析 MCP (Jev + whisper.cpp 本地转写): 主题/情绪/敏感点抽取 + 发布门控

合同条款风险点标注 MCP (Jev noul): 10 类风险概率 + 人工复审建议

论文审稿打分 MCP (Jev decision model): 多维序数打分 soundness/novelty/clarity + accept/reject/revise 决策

Single-purpose MCP server (one tool, one job): a code-review gate powered by TypeSafe Jev (System One decision model).

Single-purpose MCP server (one tool, one job): a content-moderation gate powered by TypeSafe Jev (System One decision model).

opencode plugins that replace lossy compaction with Jev decisions: score every tool call and result, drop or truncate the stale ones, keep everything else verbatim.

Reproducible calibration and selective-risk benchmarks for Jev/TypeSafe decisions in DSPy workflows

Find out which qualities of your writing actually predict engagement. Rates every post you have published against a pre-registered rubric using Jev's calibrated judgments, then tests those ratings against your real engagement numbers. Refuses to report findings your sample cannot support.

Practical agent skills and examples for building with Jev. API setup, routing, ranking, and evidence checks.

A zero-dependency MCP server for TypeSafe's Jev — calibrated, typed judgments for Claude Code, with a local answer cache and cost tracking.

A curated list of Jev / TypeSafe System One projects, SDKs, tutorials, and evaluations. English and 简体中文.

DSH plugin: register TypeSafe Jev (System One decision model) as an agent tool — jev_decide returns calibrated probabilities (noul/choice/score) for routing/triage/guardrail judgments, no text generation. 把 TypeSafe Jev 决策模型注册为 DSH agent 工具

Utilizing Jev, the RLCD-type model provided by TypeSafe AI, to independently and cheaply judge agentic coding sessions.

TypeSafe Jev hooks for Claude Code, Codex and pi: per-turn skill suggestion and subagent model routing

Open lab: Jev (TypeSafe System One) routing in front of Claude Code - measured bugs, patch, and a hard fallback with alerts

Jev MCP Hub is a small Go gateway that exposes TypeSafe's Jev model through the Model Context Protocol.

High-performance verbatim context compaction for coding agents (Claude, Codex, Antigravity, Gemini, OpenCode)

Reproducible benchmark for TypeSafe AI's Jev on agent tool-call risk classification: accuracy, latency, and whether the confidence score is worth routing on.

Persistent governance for AI agents — turn Jev judgments into replayable relation state with R2R.

MCP server exposing TypeSafe's Jev typed-decision model over the TypeSafe API or OpenRouter

Portable agent skill: TypeSafe Jev as a cheap code-review classifier (HTTP + optional jev-review MCP)

Typed-judgment model (TypeSafe Jev) driving task-level decisions on a simulated xArm7: reliability measurements, failure map, sensor-freshness gate

A Claude Code hook that asks whether the decision you are writing needs a model at all. Includes a measured 149-row comparison of TypeSafe Jev against Claude Haiku 4.5.

Let Jev, TypeSafe's ~100ms decision model, drive your browser. A plug-and-play skill for Claude Code and Codex.

⚡ DataJev LLM → Analyze Jev → Continue / Switch / Verify / Stop System-1 control for System-2 data agents

FINS demo: a UiPath coded agent for AML alert triage where every decision is made by TypeSafe's Jev model (Noul/Score/Choice) instead of an LLM

DeepSeek Harness (DSH) 执行前安全阀门:bash/pwsh 真正执行前先经静态规则 + TypeSafe Jev 语义判定,破坏性操作按 允许/修正/拦截/上报人工 四态处置,含额度降级与审计日志。

Jev decision visualisation and debugging panel for coding agents. MCP server + local web timeline, confidence alerts and trace export.

Open-source Jev skills for Claude Code, Codex, Cursor, and Grok. TypeSafe System One: choice, noul, score. Proceed, ask, or stop.

Open-source Jev harness for TypeSafe, OpenJev, Ollama, vLLM, LM Studio, and llama.cpp. Typed decisions, calibration, verification, abstention, and CI gates.

Jev-powered skill router & security auditor for any AI agent — request analysis, skill choice, prompt-injection scan

Semantic assertions for pytest: test what your LLM app's output means, judged by TypeSafe's Jev.

Evidence-first TypeScript lab for advisory Jev skill routing

Fork of wuyoscar/jev-skill v0.2.0 adapted to call a local keyless Laya decision API by default (no cost); OpenRouter/TypeSafe routes unchanged

Calibrated Jev ranking before lossless context condensation

Calibrated Jev ranking before lossless context condensation

Mandatory Jev-based routing for Herdr-managed agent spawns

Open-source developer harness and runtime safety toolkit for AI coding agents powered by TypeSafe AI / Jev

MCP server for TypeSafe Jev via OpenRouter — typed decisions (noul, choice, score), not chat

Browser automation where TypeSafe's Jev model picks each step. Attaches to an existing Chrome via CDP and runs alongside Playwright MCP. Not affiliated with TypeSafe.

Jev picks what, code owns how - a System One Factorio agent driven by TypeSafe's Jev on FLE

DIY Jev fast decision layer for Agent - 10x faster, 10x cheaper

Lossless LLM session compaction for Claude Code, Codex and ZCode — Jev keep/drop decisions plus a Chinese-optimized lossless policy. No paraphrasing, no hallucinated summaries; 9/9 HANDOVER-FREE on a private benchmark.

Multi-agent healthcare pipeline using Google ADK, stdio MCP tools, and TypeSafe Jev safety gates for instant emergency triage and clinical draft QC.

Jev plays a slot machine until the money runs out. The local version of jevslots.live.

一个不停在做决定的小镇：每个居民每刻的判断都是一次 Jev（TypeSafe System One）调用，概率、犹豫和「哪些决定只是抛硬币」都看得见 · A town where every decision is a Jev call

Review selected Figma copy with typed Jev criteria and exact TextNode citations.

Route bounded decisions through Jev and hand open-ended work to Mistral.

Policy firewall for MCP tool calls with one-time human approvals and JSONL audit.

Routes prompts to the right Claude tier (Haiku/Sonnet/Opus) using TypeSafe's Jev model

A Rust MCP server for TypeSafe AI Jev structured decisions

TypeSafe Jev System One semantic tool routing and typed decisions for DeepSeek Harness (DSH)

An LSP server whose ambient pass runs the rules a repository states in .jev/rules/*.json: each candidate line is sent to Jev, a classifier that answers one typed question with a value and a probability, never prose.

AgentJev-0.6B - a fast 'System One' decision model for AI Agents: feed it any unstructured state (diffs, traces, logs) and structured questions, get calibrated probability distributions back in one ~50ms forward pass. Zero output-token decoding.

Experimental consent-gated Jev routing and public-passage reranking for Pi

Cursor plugin that routes subagents with TypeSafe Jev and exposes Choice, Score, and Noul as MCP tools.

Jev-powered model and reasoning-effort router for Codex in DeepSeek Harness

Spam protection for WordPress comments, reviews and Contact Form 7 using the Jev decision model (independent, unaffiliated)

Horse racing simulator with real-time AI prediction. The TypeSafe Jev model is used to predict race changes in under a second.

A Paseo provider that uses TypeSafe Jev to route each Codex turn.

Jev-powered decision layer for coding agents. Analyze code and diffs, assess bugs, security, risk, and breaking changes, and return structured decisions for automated continue, fix, retry, or human-review workflows.

Open MCP server to run TypeSafe Jev (System One) packs locally — Choice / Noul / Score for Cursor & agents

Claude Code plugin: swaps LLM-summarized /compact for Jev's yes/no calls — nothing kept is ever rewritten, ~20–50x cheaper than routing it through an LLM.

Resume↔JD apply-gate cost eval: TypeSafe Jev vs Claude/Grok/GPT tiers (10 real JDs)

Jev-powered context compaction plugin for opencode: prune stale tool calls and results before every request, keep the rest verbatim.

A Jev practice catalog and local-first Agent skill router: map recurring logs to reusable decisions, tools, and workflows.

Paste a suspicious text message. Get a straight answer and the reasons behind it.

MCP server that lets Claude Code and Claude Desktop drive the jev-ultrafast browser agent in your real Chrome, with a domain-bound safeguard

Distil a prompt into a small, fast, calibrated classifier. Typed decisions (choice/score/noul) with calibrated probabilities from a local LLM teacher, served at /v1/systemone.

Claude Code plugin: asks TypeSafe Jev which installed skill fits each prompt and logs the answer (shadow-first). A working reference for the skill-suggestion cookbook on Claude Code — the README records why it is unlikely to help a strong model as a router.

Jev4JobHunter — AI job application plugin with TypeSafe Jev for job matching. Screen BOSS Zhipin jobs, apply and follow up with Codex / Claude Code. 用 Jev 筛岗位，让 Agent 完成投递与跟进。

Portable Jev skills for intent, completion, routing, Camofox browser loops and shadow context relevance.

Fail-open Jev workflow routing plugin for Codex

JEV for quilt as understood output: cellular-first decision substrate — typed cells, hook-and-drop deltas, bookkeeper WAL, last-mile projection decoupled

MCP server exposing TypeSafe AI's Jev decision model to Claude (stdio, two tools: jev_evaluate, jev_route)

Memory plugin for DeepSeek Harness: every memory read/write is a typed judgement by TypeSafe Jev (choice/noul).

Jev by TypeSafe AI — the free guide: where to get it, how to use it, use cases, and an honest comparison with Claude, GPT and Gemini. By Unnati Tripathi (@aiwithunnati).

Semantic MCP middleware that intercepts AI-agent tool calls and combines deterministic policy with TypeSafe Jev risk judgments before actions reach upstream MCP servers.

Same maze, same rules, N decision backends. A zero-key, zero-dependency arena that measures Jev / LLM / local decision models on speed, cost, calibration error (ECE) and invalid-output rate.

Prior-authorization triage POC using TypeSafe AI's Jev (System-1 model) — payer-side utilization management, synthetic PHI-free data, audit-logged decisions.

An all-in-one Jev plugin for Codex. Bringing automatic reasoning-effort routing, context filtering, and workflow assistance to macOS, Windows, and Linux. Under active development.

MCP server for Jev AI (jev-ai.pro): classification, scoring, yes/no checks, action assessment, batched decisions and saved judges.

将你的jev变成mcp插件，接入任意agent(Claude,codex,Cherry Studio)。辅助llm决策层。Turns your jev into an MCP plugin, helping LLM make decisions.

latest top 100 showcases for jev (keep updating) from x / github / latest sources

EconPaper Architect is an architect skill tailored for economic academic papers (journal submissions, dissertations, working papers, and policy research). This version incorporates enhanced calibration decision-making via Jev/RLCD: enabling the system to not only provide conclusions but also honestl

Jev 意图雷达 — 用 TypeSafe SystemOne(Jev) 读懂消息背后的意图、情绪与风险

Astra planner and JEV controller for Minecraft, with native recording, tested routes, and run verification.

VexJoy AI Agent with Jev Intelligent Routing - /do routes plain-English requests to the right specialist agent and gates the work with reviews, tests, and a learning loop.

Guardrails for Pi built on pi-typesafe that steer the agent instead of interrupting you: Jev judges irreversible and off-task tool calls, detects stuck loops, checks unverified done claims, flags slop

Discriminative Monte Carlo Tree Search using TypeSafe Jev System One Primitives and Gemini

Probabilistic AI decisions as composable backend primitives — typed judgments (noul/score/choice), deterministic thresholds, and explainable workflows. Powered by TypeSafe's Jev, provider-agnostic.

⚡ Universal System-1 AI Runtime & Dual-Brain Gateway. Sub-15ms calibrated decisions (noul, choice, score) for agents. Drop-in OpenAI proxy that slashes 80% token costs. Make decisions, not strings.

TypeSafe AI System One (Jev) task plugin for QuantumNous/new-api — native /v1/systemone, synchronous evaluation, token billing

Home Assistant Assist conversation agent powered by TypeSafe's Jev (System One) model

Rust CLI powered by Jev from TypeSafe.ai that ranks agent skills for the next step using live session context. Includes Claude Code hooks, structured JSON, abstention, and local feedback. Requires a TypeSafe API key.

Mini benchmark of TypeSafe's jev-1.13 structured decision model (OpenRouter Decisions API) on labeled support-triage: noul/choice/score, consistency, cost, lessons learned

Resolve git merge conflicts by enumeration and judgment: code enumerates every valid resolution, a TypeSafe System One model picks, code gates the pick.

What Jev answers when the only options are true and false. 3,539 statements put to TypeSafe's System One model, one subject swapped at a time — open dataset, runner and every raw response.

Guardrail + model router for LLM gateways on TypeSafe's Jev (System One model), with an independent accuracy/calibration/latency evaluation. Stdlib Python.

Bounded semantic routing with Jev and Poise. Rust, single-server, alpha.

Minesweeper played by TypeSafe's Jev System One model: one P(mine) per hidden cell per move, code owns the policy.

Snake auto-played by TypeSafe's Jev System One model: one typed decision call per tick, code owns legality and safety.

Ticket-Routing im Kundenservice mit dem Entscheidungsmodell Jev von typesafe.ai

Jev-style model routing powered by kev — a tiny local System One model classifies every request and picks the right LLM. 100% local, 100% free.

Paper-trading dashboard for crypto perpetuals routed through Jev (TypeSafe System One model), inspired by public Jev-trader builds. Simulation only, no real order execution.

Static auditor for code that uses Jev / TypeSafe System One models as a security guardrail. Type-safe is not the same as correct.

Jev(TypeSafe AI System One Model) 스터디 — 타입화된 결정·RLCD·confidence-gated routing을 한국어 노트와 TypeScript 목업으로 정리

Typed System One decisions, ranking, verification, and an opt-in Hermes tool gate using TypeSafe Jev.

Automatic model routing for Pi using TypeSafe's Jev through Vercel AI Gateway

Cost-aware LLM router that picks the cheapest model capable of handling a query, using TypeSafe's Jev for fast classification instead of an LLM call.

A verification layer for AI evaluations. Checks the instrument, not just the score: data, scorer, runs, numbers, claims, and itself.

Open-source, local Jev alternative: a System One decision layer with provably calibrated confidence (ECE 0.170→0.071). Typed decisions, runs offline, no API key, no waitlist.

Production TypeSafe Jev (System One) use-case harnesses with confidence-gated decision logic

Pokemon Red on PyBoy: code owns the route and the arithmetic, Jev picks at branches in about 100 ms, calibration measured instead of assumed

Independent calibration test of TypeSafe's Jev on a task it cannot have seen: 900 rule-generated support tickets (choice / score / boolean) plus 3 public benchmarks via Vercel AI Gateway. Raw responses, ECE with noise floor, temperature refit, per-type sign of miscalibration. Reproducible for ~$0.06

Worked examples for TypeSafe's Jev System One decision model, runnable today through OpenRouter

Benchmark TypeSafe Jev against any OpenRouter model on your own labelled classification data: accuracy, calibration, latency, cost

A Clash Royale bot with no trained policy: Jev (TypeSafe System One) makes every decision from the live game state

Never confidently wrong: a TLA+-verified consensus kernel around TypeSafe's Jev, run through 1,680 chaos-tested pharmacy decisions with zero wrong verdicts. Film, code, and every captured call.

Typed-judgment admission control at the traffic edge: three-layer prompt-injection and abuse filter for nginx/OpenResty, powered by TypeSafe Jev. Fail-open, cached, hot-reloadable.

Offline-first experiments for abstention and open-world routing with Jev.

Educational demo: score simulated token launches GEM/RUG via a mocked TypeSafe Jev decision model. Shadow/active router, no real trades.

Pi extension that uses Jev task classification (via OpenRouter) to route each run to explicitly configured models with fail-open policy. Public Preview.

Jev-first quiz automation with reasoning-model fallback, CSV/Excel import, confidence routing, and a Streamlit UI.

Jev-powered security screening and cost-aware routing for OpenAI, Anthropic, and OpenRouter LLMs.

Bounded, typed tool execution for Astra plans and Jev decision gates.

Measuring a decision model's moral judgements: constant latency regardless of difficulty, sensitivity to framing, and what that means — data, code and paper

Smart paste: copy a whole resume, paste into a job application, and Jev (TypeSafe) routes only the relevant pieces into the right fields.

Zero-shot spam filtering with TypeSafe Jev Noul questions, compared with TF-IDF baselines

Jev decides, Grok Bot executes, humans control irreversible actions. A decision router for Grok Bot built on TypeSafe AI's Jev.

Jev demo: forced Choice vs Choice+IDK vs Noul sufficiency gate (label-order swap)

Jev-powered routing for OMP and Pi: complex planning and review, focused cheaper workers.

Evidence-gated registry of Jev question packs — curated questions, golden cases and measured evidence for Jev-compatible decision endpoints

Personal T3 Code fork with an opt-in Jev model-routing trial. Based on pingdotgg/t3code.

Validation harness for Jev's Choice, Score and Noul primitives on OpenRouter's Decisions API — 282 recorded responses, reproducible offline

Twelve field tests for TypeSafe's Jev model: calibration, guardrails, résumé screening, interview rubrics and its failure modes. Bring your own API key.

Native Node-RED nodes for versioned Jev decisions, review routing and provenance.

Pi extension: per-turn Jev reasoning-effort routing, downgrade-only with user-baseline safeguards.

Decide which code-migration sites can be safely auto-rewritten, using Jev's calibrated probability entropy. AST matching, triage, auto-rewrite, self-calibration.

Pandu, is mini Jev model, inspired by Jev. Tiny policy models for fast, local, uncertainty-aware decisions in closed-loop AI environments.

Jev as a channel message router | Jev频道消息路由

SAAM · JEV Decision Demo — drone FPV, três pilotos, Vercel AI Gateway

Using jev to filter out articles from RSS feed that clog it up.

A local lab for seeing what TypeSafe's Jev judgment model does on realistic business cases: typed answers, probabilities, policy in code, receipts.

Confidence-gated incident routing with TypeSafe Jev

Dynamic per-turn model router on free OpenCode Zen + Go models (fork of gargpratyush/jev-router)

Pi extension: TypeSafe Jev routes among checked models without becoming a chat model.

Benchmark harness evaluating TypeSafe's Jev model on six public safety benchmarks against Shieldstral-1.0-3B and top SOTA guard models

A calibration arena for TypeSafe Jev: reliability, Brier/ECE, and confidence-gated risk-coverage on analytically-known random worlds.

How good is Jev? TypeSafe Jev vs an LLM on the same intent-routing task.

Natural-language speculation gates for speculative programmatic tool calling (spec-ptc), judged by TypeSafe Jev

An mini node orchestrator that uses Jev to handle routing to different LLMs based on difficulty.

Put Jev's three headline claims on trial on your own GPU. One command, a 0.5B local model: measures constrained-scoring speedup, structural type safety, and the confidence calibration nobody has published evidence for. Runs on a 6GB laptop card.

Benchmark: TypeSafe Jev vs traditional LLM on support-ticket routing accuracy, latency, and cost

BYOK playground for TypeSafe Jev (System One): Choice, Score, Noul examples for production gates.

Perfume recommendation chatbot powered by TypeSafe Jev's typed decisions (no generated text) over FragDB-format fragrance data

Test harness + benchmark for TypeSafe's Jev decision model (noul/choice/score) via OpenRouter's Decisions API

Independent playground for TypeSafe AI Jev decision models: typed decisions, support-ticket routing, reproducible evaluations, and a local browser demo.

Browser Cookie Clicker loop driven by Jev via Vercel AI Gateway

An adversarial evaluation of TypeSafe's jev decision model: nine experiments and 28 predictions fixed before any data was collected. 123,805 requests, $12.69.

Local, privacy-first dashboard for Jev Router classification and model-routing history

Does ORDER BY over a Jev probability put rows in a defensible order? Independent ranking, calibration and invariant measurements of TypeSafe AI's Jev: passes six pre-registered gates on 360 labeled rows, fails four of six on graded product relevance.

This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.

Interactive experiments with TypeSafe Jev, from support routing to 3D driving simulations with real AI decisions and visible sensor inputs.

情緒測謊器：嘴上說「好」，心裡真的好嗎？用 TypeSafe Jev（System One 模型）透過 OpenRouter 即時判斷，並與一般 LLM 對照

🔥🔥 Papers, open reproductions and independent evaluations behind System One models and Jev.

Open-source alternative to TypeSafe's Jev: a System One style model layer that gives typed, calibrated decisions from any open-weights LLM in one forward pass (HF + vLLM), with honest benchmarks

Use Jev (TypeSafe's System One model) as a calibrated reranker: one call, up to 30 documents, a probability per document. Apache-2.0.

Open-source Jev-style System One decision model. Gemma 3 270M with a scoring head — fast, calibrated decisions in a single forward pass. No text generation. Inspired by TypeSafe.ai's Jev.

Open-weights System One models (text, images, audio) and the harness that trains and measures them: LoRA plus a pointer readout head, code-labeled data, calibration on the scoreboard.

Decisions as code on System One models: typed questions, thresholds with hysteresis, nested decisions, journal, calibration

Runnable samples for Jev, TypeSafe AI's System One model. Send state and questions carrying their own answer options, then branch on the typed value that comes back.

Can a System One model play arcade games? TypeSafe's Jev plays Tetris, Snake and 2048 — benchmarked against random and heuristic baselines.

Does a System One model actually beat keyword matching? A reproducible benchmark on catching disguised duplicate thesis titles. 24 cases, real production baseline, raw data and charts included.

Stress test of TypeSafe AI's jev-1.13 System One model: limits, vagueness, calibration, adversarial, new patterns, LLM bake-off

Zero-shot benchmark of TypeSafe Jev 1.13 (decision model) vs open-weight non-generative models PrismNLI-0.4B and Laya: frozen protocol, raw predictions, calibration, latency, report

Free English RAG benchmark for TypeSafe Jev 1.13 — frozen candidate pools, calibration, paired bootstrap CIs, $0 runs. Compared with OpenJev and NVIDIA cross-encoders.

playing with jev-latest evaluation model

Reproducible benchmark evaluating TypeSafe AI's Jev (System One paradigm) on Brazil's ENEM 2025 standardized exam. Evaluates typed decision-making, domain-specific accuracy, and RLCD uncertainty calibration against open LLM baselines with an interactive GitHub Pages dashboard.

Open System One models: typed decisions with calibrated probabilities, trainable on your own data. No text generation.

Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground

Probability-aware evaluation for typed decision models: calibration, selective risk, latency, and reproducible benchmarks.

OpenJev: Open-source alternative to TypeSafe Jev. Typed probabilistic decision API (Choice, Noul, Score) powered by open LLMs & constrained logprob calibration.

Stop guessing confidence thresholds: calibrate, threshold, and drift-check typed decision models (TypeSafe Jev) against an LLM teacher.

An open training and inference stack for Jev-style decision models. Train models to score dynamic candidate branches from a shared prefix, with support for high-cardinality choice, calibration, and fast batched inference.

Nushell module for the TypeSafe System One API: typed decisions with calibrated probabilities

Benchmarks and a playground for TypeSafe's Jev (System One) model: chess, and who-is-the-player-talking-to for speech-to-text game NPCs

A word-level language model whose output layer is Jev: n-gram drafter, Noul chunk verification, bits-per-token eval

离线可用的本地类型化决策：4 核 CPU 单题 15.6ms。Local & offline Jev / System One inference on CPU — ONNX + INT8, no torch at runtime. 支持 laya / kev / PlayJev

Unofficial TypeSafe Jev showcase — System One decisions, not chat.

Local Jev-compatible evaluation server: POST /v1/systemone with typed noul/choice/score, open weights, no waitlist

Chess moves, evaluations, persona opponents, and game classification with TypeSafe AI System One

Experiments on Jev’s probability calibration, uncertainty reporting, and forecast probability preservation.

Jev-compatible /v1/systemone server reading typed decisions from LLM logits, benchmarked against TypeSafe's Jev on the same items via JevBench

Curated directory of real-world tools, interactive video teardowns, empirical benchmarks, and fast System One decision models.

Jev vs GPT-4.1 as synthetic survey respondents on Twin-2K-500. How you ask mattered more than which model you used.

Jev (TypeSafe System One) decision tools + live verification benchmark for DeepSeek Harness: jev_decision (choice/score/noul) and jev_verify, honest by design.

Rank or pick from more candidates than Jev can see in one call. The documented limit is 255 options; the real one is ~32,768 tokens. Naive chunk-merging throws away 83% of reranking's value -- measured on BEIR scifact, with controls.

A calibration audit of TypeSafe's Jev: does a decision model's stated confidence mean what it claims? 8,000 judgments against human annotations, $0.05.

Does TypeSafe's Jev keep its accuracy and calibration on Russian? Independent RU vs EN audit (ECE, reliability diagrams, paired bootstrap) on parallel human-labelled data.

How many decisions can a model make in a minute, and what do they cost? Jev, a System One decision model, raced against six LLMs on the same Snake boards.

Semantic video scene search: embeddings retrieve, Jev decides. Measured on MSR-VTT — +9 pts R@1, and it can say 'nothing here matches'.

Does Jev's confidence mean what it says? Calibrating Jev (TypeSafe System One) with Platt scaling and isotonic regression.

Can you beat Jev at Gomoku, Go or chess? Play TypeSafe's System One decision model on Cloudflare Pages, with every API call shown, a hall of fame and replays.

Pre-registered benchmark: can a 2B local model (Gemma 4 E2B) answer web questions without making things up when a decision model (TypeSafe Jev) makes every call? SearXNG for search, MemPalace for verbatim memory, seven arms including open local judges. Spec and thresholds fixed before any run.

Option-ready retrieval for decision models on the CloudBTL landing layer

Historical paper-trading simulator for evaluating TypeSafe AI JEV decisions

Scripts and raw results for a first hands-on look at Jev, TypeSafe AI's System One decision model: calibration, latency, edge cases, and a plain-LLM baseline.

Position paper: the Hidden-Markov and fuzzy primitives missing from TypeSafe AI's Jev and System-One decision models. Two lemmas, one principle (Deferred Crispification), one architecture (BSF-S1).

Open, auditable reproduction of TypeSafe Jev: a 2B probabilistic decision model benchmarked across six public suites with weights, code, and receipts.

Evaluating TypeSafe's Jev on Michael Mauboussin's 50-question decision calibration test

JevKit is an open-source decision infrastructure that helps developers integrate Jev into their applications, define structured decision tasks, evaluate model performance, and build reliable fallback policies.

Evaluate typed AI decisions on labeled French-language cases.

Speed and accuracy benchmark: TypeSafe's Jev API vs the local Laya MLX typed-decision model on synthetic tasks

Independent API-only calibration audit of TypeSafe AI's Jev decision model

Benchmarking Jev on Japanese Medical Licensing Examination questions: accuracy, calibration, latency, image dependency, and exam-level reconstruction.

TypeSafe Jev predicts a synthetic 32-team tournament in round fan-out: calibrated Brier vs Elo/seed/oracle plus Monte Carlo champion odds.

Made the horizontal open-source model for Jev with RLCD, and it surpasses all the Jev benchmarks

TypeSafe's Jev vs gpt-5.4-mini and gpt-5.6-luna on four public classification sets: cases, per-item answers, scoring, charts

Jev System One AI & RLCD Reproduction Engine: Sub-70ms Calibrated Decisions with SmolLM-135M and 0 Output Tokens

Blind human labelling app for the Jev crash-narrative calibration reference set (private: contains redacted CRIS narratives)

Measure accuracy and calibration of Jev (TypeSafe AI's decision model) on public datasets: 12 business-like tasks, 7 experiments, one Python file.

Benchmark of TypeSafe Jev (System One decision model) for systematic review title/abstract screening vs GLM/Sonnet on Cohen_2006 gold standard

A forward-only experiment: Jev (TypeSafe System One) making one-second trading judgments on bitbank, logged for calibration analysis.

A local demo comparing Jev and LLM judges for answer evaluation, with native Noul and Score outputs.

Measures how well TypeSafe's RLCD-Jev model spots real secret credentials in file snippets

Pluggable decision-model training and benchmarking framework

Typed decisions from frozen local LLMs, with reproducible evaluation and experimental residual-head training.

Pretrained base LMs are already calibrated on option-logit readouts; instruct tuning breaks it. Measured on Qwen2.5 0.5B/1.5B/7B, MMLU/ARC/HellaSwag.

Independent research notes toward an open Jev-like decision model: public facts, API contract, training and eval plan.

OpenJevPro: Production-grade typed probabilistic decision API (Choice, Noul, Score) powered by open LLMs & constrained logprob calibration.

Tax document page classifier built on Jev decisions. 100% strict accuracy across 261 IRS forms, ~$0.001 per page.

A family of System One-style models fine-tuned from Qwen3.5, designed for one-pass typed decisions with calibrated probabilities.

JevBench v1 - a benchmark for Jev-class typed decision models: smart, cheap, fast, reliable, open.

Open replica of TypeSafe's Jev: typed calibrated decisions in one forward pass, on Gemma 4 E2B / Gemma 3 270M (Modal)

openvons (open-Jev): 有限選択肢に確率で答える判断層 — テキスト / 画像 / 日本語音声コマンド

Independent, reproducible benchmark: a decision model (jev), eight constrained LLMs, and deterministic baselines on typed decisions - accuracy, calibration, latency, cost, failure modes

Jev-style calibrated decision model (Choice/Score/Noul) on Qwen3.5-0.8B

A small open decision model: state + typed questions -> calibrated probabilities. A Jev / System One re-creation on Qwen3.5.

A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.

mini-Jev: what a Jev-style typed-decision interface looks like on a frozen Qwen3-4B — read the option letter's logits instead of generating JSON. Preregistered experiment, results, teaching bench.

Dohnuts builds small multimodal models for direct decisions. -> System One model

Empirical experiments and API research for TypeSafe's Jev System One model trained using RLCD

Jev-class System One model blueprint — built from open components (50M encoder + parallel decision heads, Needle3 distillation, RLCD path)

Turn any open model into a classifier/jev endpoint

The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.

Jev-compatible API endpoint based on open models (prefill-only)

EmbodiedJev: MuJoCo robot decision workbench with MiniCPM5-2B, Jev and compatible model APIs

A decision cache for TypeSafe Jev-class models — memoize decisions so repeats are free, deterministic, and shareable. One 2 MB binary.

Jev-style parallel constrained decisions for any MLX model on Apple Silicon. Typed, schema-valid JSON in one forward pass.

Data extraction for systematic reviews, quoted from the papers. Ask a trial report and its supplements your extraction form or a RoB 2, ROBINS-I, QUADAS-2 or TIDieR template; Jev points at the lines, every answer is a verbatim quote with its page, you check it and export the table. Files stay in you

Awesome list of Jev use cases. Compared with GPT Models (LLMs) across on cost and speed.

A Swift package for typed decisions from language models (probabilities, choices, and scores), with support for local MLX models and the TypeSafe Jev API.

Jev Resume Disqualifier: Sub-25ms automated resume knockout engine powered by TypeSafe Jev System One decision intelligence. Eliminates 80% of unqualified applicants with deterministic date math & EEOC-safe rejection notices.

Catch breaking API behavior hidden in OpenAPI prose with deterministic checks and TypeSafe JEV System One semantic review.

Researching how Jev can accelerate tasks that rely on LLM decision-making.

A pi extension that exposes TypeSafe (Jev, System One) judgments as five pi tools, so a model can make narrow semantic judgments while your code and your users keep control of thresholds, weights, and actions.

Open models, libraries, tools, and applications for Jev and System One decisions.

Browser decision playground and reproducible experiments on memory, uncertainty, and Doom control

Turn any LLM into a Jev-style decision model: typed decisions, real probabilities, no training.

Mock Jev API decisions with MSW for deterministic tests without real API calls or credits.

Typed Jev decision primitives for Reachy Mini applications.

Jev System One Black-Box Study - Complete Reproducibility Bundle

Jev (laya-mlx typed decisions) guided long-context compression for faster Qwen3.8 prefill on Apple Silicon MLX

Deterministic generational wave, linguistic origin, and gender distribution for names using TypeSafe JEV System One

Reproducible Jev and GPT-4o mini classification experiments, findings, and explanatory report.

Architecture and implementation specification for a GLiNER2-based decision service with a Jev-compatible interface for Choice, Score, and Noul.

Open-source paper hedge fund. Jev decides. Public tape of holdings, buys, and losses.

Interactive workspace for comparing baseball roster acquisitions — positional coverage, playing-time transfers, and reproducible scenario analysis, demoed on five 2026 Red Sox storylines.

Does a typed-judgment model rerank better than a cross-encoder? Jev, Voyage, GPT-4.1-mini, GPT-5.6-luna and Laya over identical shortlists on two Finnish legal corpora.

Clasificador de comandos de shell de una sola pasada (solo lectura / reversible / destructivo), inspirado en Jev

Minimal Python starter for TypeSafe Jev typed decisions — UIbuckets

Local bilingual probability decisions from context, questions, and candidate answers. Independent research preview inspired by TypeSafe Jev.

Where does a decision model's generalisation come from? RLCD on Qwen3.5-4B, held-out sets grouped by training-data coverage, JevBench and three external suites.

Rust reimplementation of Laya, a sub-35ms non-autoregressive typed-decision engine (ModernBERT encoder + RLCD-trained decision head), built from scratch on candle.

A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.

Trading bot with the all new TypeSafe AI's first system one model named as Jev

TypeSafe System One / Jev community directory — GitHub projects & posts around typed decisions (typesafe.ai)

Control your Mac by voice. Speech → Jev (TypeSafe AI System One model) typed decisions → macOS actions. Menu-bar Swift app.

Runnable demos of TypeSafe's System One model (Jev) — parallel Noul judgments and a Choice-based citation/claim checker

A curated list of Jev guides, official documentation, and community projects for AI practitioners, product managers, and builders.

An automated trader using SystemOne model - TypesafeAI Jev

JAST is an experimental SAST (static application security testing) desktop app that uses TypeSafe AI's Jev System One model.

Can a System One model steer music? Jev picks the plan (enums only); code renders sheet, audio and MIDI.

Next.js UI showing off TypeSafe's System One model (Jev) — parallel Noul judgments and a Choice-based citation checker, deployable to Vercel

JevGeni — a fly brain at the claw machine. Tech demo for Jev (typesafe.ai) + Whisper v3 Turbo (Groq). Voice only.

a demo of Typesafe's Jev a System One Model for structured decsion making

Verified, screenshot-rich awesome list of projects built on Jev — TypeSafe AI's System One model for typed decisions

Xtags: a Chrome extension that labels each post in an X timeline with what it is trying to get from you — inducement, provocation, promotion, machine-generated, persuasion, entertainment, information — drawn as a tag plus a probability right after the timestamp. A side panel reports session counts (

One AI trade decision every Monad block. Jev on Kuru MON-USDC.

Search the web with TypeSafe's Jev: source selection, query understanding and relevance ranking. Built with Search1API.

Browser use using Typesafe's Jev model

An educational Jev-like visual inference experiment on Apple Silicon: shared context, direct candidate scoring, and local visual demos.

Control a real browser by voice. Jev (TypeSafe System One) decides intent + target in ~300 ms per spoken word; Playwright acts — often before you finish the sentence.

Fish-style zsh history autosuggestions ranked by Jev (TypeSafe)

Live Jev trader on Hyperliquid

Jev 模型介绍与实测：通过 Choice / Score / Noul 将自然语言转为带类型的判断与概率，用于分类、评分和路由；支持与 DeepSeek 等模型对比评论打标、速度与结果，含 CSV/Excel 导入、原速回放与离线报告。

Talk to your Mac. Local whisper.cpp + one Jev (TypeSafe) call per command + macOS automation.

Can a model design a dashboard? A console whose whole design system is generated at runtime by Jev from a one-sentence brief.

1v1 Jev quickscope arena — Three.js + TypeSafe System One

macOS computer use driven by Jev (TypeSafe System One) as the decision maker

Run Jev-like decisions in your browser with the Prompt API.

AI as a PowerShell decision primitive: describe what you need, let Jev rank the right file.

Jev (TypeSafe System One) × ASReview SYNERGY abstract screening demo — Choice/Noul vs gold labels

Spring Boot starter for TypeSafe AI's Jev — typed Choice/Score/Noul decisions in your Spring MVC app, no text parsing required.

TypeSafe Jev System One powered Gomoku arena

Jev System One powered Chinese chess arena

A practical Jev playground for typed, probabilistic decisions across fraud, sales, and patent screening.

Non-blocking, provenance-checked Jev decisions for Bevy ECS.

Turn typed Jev review findings into exact, undoable Premiere timeline markers.

Native Unreal Engine 5.8 StateTree tasks for finite, revision-guarded Jev decisions.

Live Jev support-ticket judgment demo using Choice, Noul and Score primitives.

Demos que enseñan en qué se diferencia Jev (el modelo System One de TypeSafe AI) de un LLM normal

Tiny demo of TypeSafe System One / Jev: unstructured state in → typed probabilistic decisions out (noul, choice, score). Mock by default; live API optional.

beta project di use-computer su google chrome mediante l'uso di Jerv, riducendo notevolmente la latenza e i costi per token

Processing arena where little robots hunt treasure, with TypeSafe's Jev as their brain

🐠 A multiplayer fish game where every AI decision is a TypeSafe Jev (System One) call — flee, hunt, roam, with live confidence bars. Node + WebSocket + Three.js.

Floating animal emoji finder with a search bar in the middle. Search in plain English ("birds", "animals that fly") using Jev AI, with a built-in search as fallback. Click any emoji to copy it.

Control your own Chrome by voice. Jev (TypeSafe System One) decides intent + target from typed probabilities in ~300 ms per spoken word; the extension acts before you finish the sentence. MV3 port of moritzkremb/jev-voice-browser.

Playground for TypeSafe AI's Jev: typed judgments (noul / choice / score) with probabilities

🧹 Fun project: a Chrome extension that asks a tiny AI decision model (TypeSafe Jev) "is this DOM element an ad?" and pops it off the page. BYOK, no backend, not a real ad blocker.

Snake auto-played by TypeSafe's Jev model: one System One choice per tick, legal moves and facts generated in code

字面理解、计数不可靠、日期比较、多级间接、无关细节大 state、对抗内容、指令与 criteria 矛盾、结构性不变量、生成。官方建议"拆成原子问题在代码里组合"。

同一审核 rubric、8 个 Choice × 每条件重复 15 次。TypeSafe raw agree 90.8%（8 题有 2 题翻转，但 conflicts=0 —— 翻转只发生在「具体标签 ↔ uncertain」之间）。加一条 abstention 规则（用 probabilities 要求 top probability ≥ 0.60，否则 uncertain 转人工）后一致率升到 99.2%，automatic 74.2%，不增加模型调用。对照：Haiku t=0 100%、Opus 4.8 reasoning 92.5%、gpt-5.4-mini t=0 99.2%。官方声

官方明说 confidence 是从 probabilities 分布算出的统计量，分布越集中越确定；Noul 不带 confidence；官方明说"你没有被锁死在我们的定义上"；阈值应"从保守值开始、在你自己数据上测"。

*"Coding harnesses like claude, codex, cursor have shipped some kind of way to classify dangerous actions… Up until now, this classifier step has been locked away in the closed source parts of the harness. Now that a cheap and performant classifier model exists, we can take the same pattern and adop

TypeSafe 新增 Team 页 + 导航新增 Enterprise 入口（产品化/商业化信号）

Vercel 官方 changelog 宣布 Jev 上架 AI Gateway

llms.txt 全站 111 页；本地原有 30 页，diff 后发现 cookbooks/ 下 18 篇配方（含可跑代码、真实数据集、实测数字）。逐篇拉取并加 type: official-cookbook frontmatter。

npx -y skills@latest add typesafe-ai/skills -s typesafe-ai -g -a '*' --copy -y → 安装到 ~/.agents/skills/typesafe-ai/（单文件 SKILL.md，149 行 / 10 KB，覆盖 79 个 agent）。安全评估：Gen=Safe、Socket=0 alerts、Snyk=Low Risk。唯一失败项是 Eve（不支持全局安装，无影响）。

本轮 diff 未发现新增页（30 篇 + 18 cookbook 已齐）；说明采集器的 diff 逻辑正确。

端点 POST https://api.typesafe.ai/v1/systemone；jev-1.13.0，别名 jev-latest/jev-preview；64k/请求、state+最长问题 32k；限流 250k tok/s、1200 req/min 且动态调整；仅文本输入；Choice≤255、Score 2–10 档；不 fine-tune、所有账号共用同一套权重；不用客户数据训练；英语最准。

preview 端点 /preview/evaluation → 稳定版 POST /v1/systemone；prompts 数组 → questions map；responses 数组 → answers map；字段改名 probability→noul、chosen→choice、expectation→score；choice 概率由数组变 map；score 概率为 v1 新增；认证不变。

A curated list of public projects, integrations, and discussions built on Jev — TypeSafe AI's System One model for typed decisions.

Evidence-backed use cases, patterns, prompts, and starter code for TypeSafe Jev — a System One model for fast, typed, confidence-aware decisions in software.

A curated, source-backed list of projects built with Jev, TypeSafe AI's System One model for typed decisions.

A community directory of projects built on Jev, TypeSafe AI's System One model.

Everyone now talks about the architecture that's not auto regressive and does lightning fast probability prediction with a json schema. I worked on this literally one year back in March 2025, published an arxiv paper, pushed the model to huggingface along with the pypi pack

Hello HN! We're Dillon and Francesco from Cua. We were wondering how many computer use tasks actually need a full general purpose LLM (e.g. gpt-6-astra, claude-opus-5 etc.) to think through all their decisions and steps. Some tasks require thinking about a plan, exploring di

Evidence-backed use cases, patterns, and guidance for building with Jev, TypeSafe AI's System One model. Every claim is labeled and sourced.

The Jev benchmark you've all been waiting for: Will Jev pull the lever in the trolley problem? Don't think too much about it :) Place whatever you'd like on each side of the tracks, and GPU (my startup's AI system, whee!) will have Jev judge the result. As a b

Hi everyone. TypeSafe released Jev last week, and it pushed me to build agent-chaperone. It is a screening layer for AI agent tool calls and tool results. It screens risky, off-task, or secret-leaking actions before they run, and prompt injections or other suspicious instructions

A curated projects built with Jev, TypeSafe's System One model.

SemanticSpace is an experiment around Jev, TypeSafe AI’s new model. It uses a Cartesian plane defined by arbitrary phrases for each axis, to map prompts onto the resulting 2D semantic space. You can edit the prompts and axes to visualize virtually any 2D relationship.

I built Odyssey, a browser based journey from Earth to lunar orbit. It uses Jev from TypeSafe AI to choose between navigation actions. You can watch each decision and the probabilities assigned to the available options as the flight progresses. The simulation provides the traje

Full disclosure, it was coded with AI, I don't claim otherwise. But I wanted to test out tool calls and iterative problem solving using Jev and needed a simple library/framework/harness to do that. SOKIT (System One Knowledge, Instructions and Tools) is the result

A crawler-maintained directory of projects built on Jev, TypeSafe AI's System One model. Daily GitHub + npm sweep, human-merged.

Projects built on Jev (TypeSafe AI's System One model), curated by Jev itself.

108 条声明对照：Jev 的校准并不独特（含作者自我修正）

cellcog.ai 追踪页 自称分层记录 *"claims / concedes / measured / found, dated"* → 与本库锚页设计意图一致，值得长期对照

在两个带标签数据集（Banking77 与 Web of Science）上独立测量 Jev 校准，协议在出结果前冻结，原始 JSONL 与图表已提交。原话：*"no routing parameter transferred between the two datasets"* —— 最优阈值、两模型精度差的符号、以及路由是否划算，全都变了。诚实标注：Web of Science 的标签来自出版物元数据，部分误差是标签歧义。

无 API key、无账号的零样本分类 HTTP 服务；提供 openapi.json(OpenAPI 3.1) 与 llms.txt；附带可安装的 agent skill（*"paste it into any coding agent… npx skills add"*）

6 个问题的准确率/Brier/分桶可靠度：Brier 0.036–0.149；高置信桶（0.9–1.0）多为 100%（egress 15/15、outside_repo 14/14、prod 10/10、secrets 10/10）；但 destructive 在 0.8–0.9 桶是 0%（3 个样本全错），仓库自认有一个问题不达其 0.85 门槛。仓库默认以 observe（影子模式）发版，原话"不该凭 README 说分类器好就开强制，自己跑"。

三个分类任务上对比"每题一个直接 Jev 问题" vs "12–14 个打分维度 + 本地拟合权重"；5,477 条测试行、3,410 万输入 token、共 $1.43。日语 NLI 上分解 0.9076 vs 直接问 0.8373，但分解把约 25× 更多"困难的良性样本"误判为攻击，四次修复尝试全部失败。

把 Jev 接进 DSH，注册原生工具 jev_decide（走 ctx.tools.register + DSH 强制 JSON Schema 子集，即 MCP 工具的注册路径），零依赖、不 import 任何 @deepseek-ai 包；两种传输（原生 TypeSafe API / Vercel AI Gateway）。

A curated list of projects, SDKs, and write-ups built on Jev, TypeSafe AI's System One model for typed decisions.

New：InfoWorld（2026-09-17） —— 企业媒体视角，用例清单：*"which tool to invoke, which action to take next, whether a request should be approved, when a task…

把 Jev 描述为 *"a small and customizable System One decision model"*，并明确 *"Jev can't reason or write explanations; anything heavier gets split into separate questions and recombined in code"*。

*"Your AI reports 0.95 confidence. That is not automatically a 95% chance of being right."*，并讨论"把阈值设在人仍会复核的位置"——与本库铁律 + 阈值方法论一致，且他是 AI 教育知名账号 → 概念正在被正确传播

X：@heyDhavall 的简洁概括（*"why make software wait for an LLM to generate paragraphs when it really just needs decisions?"*）

*"got Jev to review my PRs. ~200x cheaper than Claude and it answers in half a second, 6 real PRs… $0.00007 each. 1,000 PRs = 7 cents vs ~$14.50 on Opus 5"*；粘贴一个 diff → 一次调用 → 14 个类型化检查以概率返回（硬编码密钥、SQL 注入…）

创始人第二段"原始初衷"（比第一段更锋利）：Diogo Almeida 经 Pat McGuinness Substack 转引

*"Teach your coding agent to try Jev before it writes another regex, and to write down what happened."* 它让 coding agent 在发现某步骤是有界判断（classify/tag/triage/size/rank/route/filter/verify/match/gate）时先试 Jev，再把这次尝试（无论是否采纳）记录到一个 lab 目录供下个项目复用。支持 Claude Code / Codex / Cursor / Gemini CLI / OpenCode / Pi / He

把我们此前零散收集的生态补成一张完整的图，结构为「官方资源 / 客户端与集成 / agent 与开发者工具 / 浏览器 agent / 游戏机器人与交互 demo / 评测与独立研究 / 展示与实战记录」。最后复核 2026-09-17，并明确声明与 TypeSafe 无隶属关系。

四条精准告诫（已写入 IO 契约 §S8） —— Wavect 独立评测：

litellm/types/proxy/guardrails/guardrail_hooks/typesafe.py 实现了 compaction guardrail：*"A completed tool exchange is dropped when Jev scores the probability that it is still needed below this value. Defaults to 0.2."*

独立第三方与我们的术语纪律收敛：HarnessRouter（2026-09-20）

*"A server implementing the TypeSafe/Jev HTTP API with Qwen3.6-35B-A3B on SGLang."* 单容器单 B200；SGLang 0.5.19 Rust 前端 + radix caching + breakable prefill CUDA graphs；可一键部署 Modal（unauthenticated=True）拿到公网端点。工程细节值得抄：API 与推理同生共死（推理挂了 API 也退出，让 Modal 换容器，而不是留一个 HTTPS 活着但后端已死的进程）；预热时故意请求一个未使用 token 的概率以绕开

第 9 份独立评测：@juanmacias《Testing TypeSafe's Jev - Legal Corpus》

① Noul 的 0.5 不等于"中等"，意味模型分不出来；② Score 不是测量，不要在档位间插值（1.0 可能是"全在第 1 档"或"一半 0 一半 2"）；③ 批量打包 13 问 = 便宜 12.2×、快 10×（测试用 53,777 字符长文档；重复测试未见批量效应）；④ criteria 里放"像真输入的例子"有效：同一 Safari bug，纯档位 score 1.30 @ conf 0.54 → 加相关例子 1.07 @ 0.90，加不相关例子几乎无变化；⑤ 生产规模实测：1,018 篇摘要分类 24 主题共 $0.08、中位 256 ms/篇；⑥ 护栏影子测试：含糊 shel

40 次调用全成功、10/10 分类正确；median 0.643–0.674 s；$0.000025–0.000027/call；confidence 在 medium 档明显更低（0.57–0.67 vs 1.0）——目前唯一独立观测到的校准行为。保留意见：官方 benchmark 里 Jev 76.0% 未明显超过 Luna 76.1% / DS v4 Flash 76.8%。

fx 默认 auto 模式的 safety reviewer 原跑 GPT Luna，换 Jev 后 p95 快 18× 且更准；"coming to Vercel AI Gateway and likely new default"；同司 @fazxes 称 ~5–18× 更快且更准。

闭环信号：Archer 那篇文章上了 HN —— Jev's Architecture Unmasked（item 49766351，1pt）

A curated list of awesome Jev / TypeSafe System One applications, libraries, and resources.

Curated Jev resources and runnable examples for typed AI decisions.

JEV HUB · X 上关于 TypeSafe AI「系统一模型」Jev 的长文与演示视频聚合（保留原链与作者）｜ 谁是专家 出品

A curated list of awesome Jev / TypeSafe System One applications, libraries, and resources - curated by APA (AIPersona Academy)

Jev is all the rage right now and this directory lists all things Jev! Docs, SDKs, and the full tool map one click away.

A provenance-first, machine-readable directory of the TypeSafe Jev ecosystem

@typesafeai 在发布日 11:17am 发布后，5:43pm 被 CEO 报告被盗，5:54pm 确认钓鱼，11:49pm 夺回（"JEV LIVES"）。

The system one Harness for system one models

OpenDecision is an open-source semantic decision engine like typesafe's jev.

Classify your inbox with Jev (TypeSafe's System One model) — tag, move, flag, and notify, all config-driven.

Connect WordPress to TypeSafe's Jev System One model for structured decisions (choice, score, noul).

The same decisions, on CPU. System One model that can run on your Personal Computer.

tell you everything about jev,TypeSafe AI's System One model for typed decisions.

System One Models & Jev documentation. typesafe.ai documentation extracted in .md format for LLMs. Used to train LLMs.

Connect Four played by TypeSafe's Jev System One model: one typed Choice per move, with Jev vs Jev personas and a baseline.

A Github Action for a Code Review Classifier built with the System One model Jev

Testing out System One Models

Using Typesafe.AI to generate diff reviews.

A village of silent AI villagers: every decision goes to a System One model (Jev) instead of a chat LLM, with live Jev-vs-frontier-LLM cost meters.

🐳 A dockerised image of Convaiinnovations Laya System One model. For rapid deployment and scaling

System One Model API for Laya compatible with TypeSafe Jev

tiny Jev-like family of decision models built on top of Qwen3.5 you can train and run on your own

A self-hosted drop-in replacement for TypeSafe's jev, powered by GliFormer.

grep by meaning, across languages. TypeSafe Jev scores every line against a meaning; combine meanings with AND/OR/NOT. 意味で探す grep。日本語で英語を、英語で日本語を検索できる

Adapt local language models into Jev-compatible structured decision engines with Choice, Score, and Noul outputs powered by prefill-only binary inference.

Left-pad strings with TypeSafe AI's Jev. For reasons.

Type-Safe Decoding for Autoregressive LLMs

TypeSafe（Jev / System One）申请 → 确认邮件 → 获批 → 注册 → 建 API Key 全链路工具，纯 HTTP 无浏览器

在 X 的时间线上，给每条帖子标出它想让你干什么。判断来自 Jev，一个只返回概率、不生成文本的模型。

微信（Windows 4.x）旁挂的回复辅助：窗口截图 + 本地离线 OCR 读对方消息 → Jev 判断意图 → 3 条候选一键填入，发送永远手动

TypeSafe Jev (System One) にブラウザ上のマインスイーパーを解かせるデモ

A show-and-tell capability study for Jev, TypeSafe's System One decision model.

A lightweight, native Swift 6 bridge integrating TypeSafe AI's Jev System One decision model into Apple's Foundation Models framework.

A TypeSafe Jev-compatible HTTP server (POST /v1/systemone)

A polished OpenAI + TypeSafe Jev terminal interface for answers with transparent decision reports

System One judgments (noul/choice/score) from any LLM in one prefill — a Rust, Jev-compatible /v1/systemone engine

Compare GPT generated language with JEV structured Noul decisions on the same input.

Can Jev Bayes? No. Testing TypeSafe AI's Jev model against Bayesian-optimal strategies.

Learn Jev — TypeSafe System One typed decisions for software. Personal GitHub Pages reference hub (deck, shorts, sources). Unofficial.

Chess head-to-head bench: TypeSafe Jev vs Laya (System One legal-move decisions)

Resolve a DAG of enumerated decisions with a fast judgment oracle (Jev). Selection over sampling; slop-free within a fixed vocabulary.

Jev plus a decision head that learns from feedback: can a loop name a bias we planted in our own dataset?

Jev 中文介绍：System One、State、Choice、Score、Noul，提供 Markdown、HTML 和 PDF。

Intelligent procedural ambient soundscape generator powered by TypeSafe JEV System One

Six Instagram DMs. One hidden near-term buyer. Try the decision layer and own the handoff.

Jev で「いっぱい→おっぱい」を Noul / Choice / Score で聞く最小デモ

Highlight text, right-click, Ask Jev — TypeSafe Jev answers in a Chrome side panel

Native Entscheidungsmaschine für macOS: kev-0.6b und laya als Core ML in Swift, ohne Python zur Laufzeit, ohne Cloud

Before every NFL snap, a decision-only AI model (TypeSafe Jev) calls run or pass and go/punt/kick on fourth down, graded live against the coach.

Jev primitives: Choice / Score / Noul explainers + examples

Jev (TypeSafe System One) 테스트베드 — 클라우드 API와 로컬 셀프호스팅(jeff/GLiFormer) 양쪽 실행 예제 및 실측 결과

omp extension: a read-tier decision tool backed by TypeSafe System One (Jev) — typed choice/noul/score questions over any state, answered with probabilities and token cost

👩‍🔬 Pilot of the decision model 'jev' from TypeSafe AI

Typed System One decisions with Jev: Choice + Score + Noul composed in code.

Classify large playlists by song language with TypeSafe AI's latest Jev model.

Learning about Jev, Typesafes flagship structured decision model.

Tiny Jev (typesafe) call stub — sample rows + Choice/noul questions

Jev 文本判断工具：Noul、Choice、Score，深色本地网页与命令行，Python 标准库实现。

Local "System One" — typed closed-set decisions on local Qwen/Spark. Drop-in shape for /v1/systemone, no cloud.

Testing flappy bird with SystemOne Jev like model locally

A network profiler usign Jev, educational proof of concept only!

An experiment with semantic code linting using Jev from TypeSafe AI

Noul -> Primitiva para saber si es si o no

The Jev System 1 Oracle — Victorian steampunk Magic 8-Ball powered by TypeSafe AI's Jev model

How jevchess.com asks JEV for a chess move: every legal move as the options of one typed Choice question, plus the hanging-piece check that describes them.

Jev (TypeSafe AI's System One decision model) use-case catalog: real-world builds, cost math, design patterns, and a reality check on vendor claims.

Resume-to-job-description fit classification using TypeSafe AI's Jev model via LangChain

Open, Jev-compatible System One decision server on DiffusionGemma

The open, local take on Jev: typed decisions from an LLM, without generating a single token

A very fast document classifier/splitter using Jev

Run Laya, the open-source Jev-compatible System-1 decision model, from Node.js / TypeScript via ONNX Runtime

OpenThai-SystemOne: open Thai + English System One decision model (0.8B, 256-way slot head, Apache-2.0)

TypeSafe Jev controls original StarCraft shareware through keyboard and mouse with recorded action probabilities.

Typed SEO, AEO and GEO judgments powered by Jev, a System One decision model. Code owns the rules, the model owns the meaning.

Toy local System One–style decision API (Jev-shaped). Not affiliated with TypeSafe.