questions: { direction: choice, }
jev-trader
One AI trade decision every Monad block. Jev on Kuru MON-USDC.

Every project here really calls Jev in its source · refreshed daily
questions: { direction: choice, }
One AI trade decision every Monad block. Jev on Kuru MON-USDC.
questions: { requested: boolean, issued: boolean, route: choice, // +1 }
A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.
questions: { intent: choice, is_urgent: boolean, frustration: score, }
Evidence-backed use cases, patterns, prompts, and starter code for TypeSafe Jev — a System One model for fast, typed, confidence-aware decisions in software.
questions: { department: choice, return_reason: choice, requested_resolution: choice, // +2 }
tiny Jev-like model built on top of Qwen2.5-0.5B you can train and run on your MacBook
questions: { correctness: boolean, security: boolean, reliability: boolean, // +2 }
A staged code-review workflow and local dashboard built with TypeSafe Jev.
questions: { action: choice, done: boolean, risk: boolean, }
把 Computer Use 的「下一步点哪里」交给 Jev(TypeSafe System One):Jev 从界面文字候选中选元素、动作、完成度与风险,Codex Computer Use 负责读取界面与执行,本地策略门槛拦截敏感操作。只传文字,不传截图。
Write your own criteria, options and score levels in the playground, paste some text, and watch Jev decide. 15 free runs a day.
questions: { direction: choice, }
One AI trade decision every Monad block. Jev on Kuru MON-USDC.
questions: { requested: boolean, issued: boolean, route: choice, // +1 }
A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.
questions: { intent: choice, is_urgent: boolean, frustration: score, }
Evidence-backed use cases, patterns, prompts, and starter code for TypeSafe Jev — a System One model for fast, typed, confidence-aware decisions in software.
questions: { department: choice, return_reason: choice, requested_resolution: choice, // +2 }
tiny Jev-like model built on top of Qwen2.5-0.5B you can train and run on your MacBook
questions: { correctness: boolean, security: boolean, reliability: boolean, // +2 }
A staged code-review workflow and local dashboard built with TypeSafe Jev.
questions: { action: choice, done: boolean, risk: boolean, }
把 Computer Use 的「下一步点哪里」交给 Jev(TypeSafe System One):Jev 从界面文字候选中选元素、动作、完成度与风险,Codex Computer Use 负责读取界面与执行,本地策略门槛拦截敏感操作。只传文字,不传截图。
questions: { refund: boolean, spam: boolean, }
Turn any open model into a classifier/jev endpoint
questions: { next_action: boolean, danger: score, }
A TypeSafe/Jev agent that plays Super Mario Bros. from structured emulator state.
questions: { window: choice, source_reddit: boolean, plain: boolean, }
Search the web with TypeSafe's Jev: source selection, query understanding and relevance ranking. Built with Search1API.
questions: { positive: boolean, }
Drop-in TypeSafeClient replacement backed by LLM APIs
questions: { billing: boolean, }
The official Python library for the TypeSafe API
questions: { intent: boolean, target: boolean, site: boolean, // +5 }
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.
questions: { severity: score, needs_tool: boolean, }
A lightweight Jev-powered router for models, tools, and subagents
questions: { destructive: boolean, exfiltration: boolean, beyond_scope: boolean, // +1 }
TypeSafe Jev as a decision layer for the Pi coding agent: a measured tool-call gate plus jev_ask for typed, calibrated answers
questions: { urgency: score, }
A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.
questions: { queue: choice, escalate: boolean, urgency: score, // +1 }
A small open decision model: state + typed questions -> calibrated probabilities. A Jev / System One re-creation on Qwen3.5.
questions: { risk: score, }
Camera-only autonomous drone in MuJoCo with a small judgment model (TypeSafe Jev) in the loop at 2.5Hz
questions: { stale: choice, }
Bounded TypeSafe Jev workflows for coding agents.
questions: { intent: choice, needs_reasoning: score, }
The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.
questions: { relevant: boolean, }
Classify first. Read selectively. A portable agent plugin and MCP tool for batch text classification.
questions: { urgent: boolean, }
Ruby client for decision models such as Typesafe Jev
questions: { ok: boolean, }
Chrome extension: vibe-check your X posts with TypeSafe's Jev before you hit Post
questions: { sentiment_spectrum: score, catalyst_impact: score, }
An on-demand crypto market intelligence and decision-support terminal powered by TypeSafe AI's System One model (Jev).
questions: { refund: boolean, }
This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
questions: { department: choice, urgent: boolean, frustration: score, }
OpenDecision is an open-source semantic decision engine like typesafe's jev.
questions: { intent: choice, reuse_cache: boolean, needs_subagent: boolean, // +2 }
Connect TypeSafe Jev to Grok Bot as a cheap decision layer - usage gates, skill template, examples
questions: { refund: boolean, team: choice, }
ACP and MCP adapter that bridges TypeSafe Jev with any LLM — computer use and typed decisions alongside Codex, Claude, Grok, and OpenCode.
questions: { next_reference: choice, }
A spatial reference explorer for creators. Local Jev query choices, metadata highlights and source-linked collections.
questions: { problem: score, customer: score, demand: score, // +5 }
Describe your startup idea. Jev decides: kill it, fix it or ship it.
questions: { ok: boolean, }
MCP server that puts TypeSafe Jev on the coding loop in Cursor, Codex, and any MCP client
questions: { r0_missing: boolean, r0_instruction: boolean, }
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
questions: { is_billing: boolean, category: choice, }
Semantic tool routing and typed System One decisions for the Pi coding agent using TypeSafe Jev
questions: { stuck: boolean, destructive: boolean, }
TypeSafe AI の System One モデル Jev を MoonBit から触るためのプレイグラウンド。
questions: { injection: boolean, hidden: boolean, exfiltration: boolean, // +3 }
Agent-ergonomic CLI for TypeSafe's Jev: fast calibrated judgments (pick, rate, check, rank, triage, guard) from the shell
questions: { intent: boolean, target: boolean, site: boolean, // +5 }
English full-duplex voice control for macOS with OpenAI Realtime, native Accessibility, and Jev.
questions: { questions: boolean, }
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.
questions: { binary: boolean, rating: score, }
Replicating Jev with a local LLM
questions: { conflict: boolean, }
Community TypeSafe AI playground: 110 use cases, games, dilemmas and model challenges, with editable prompts, A/B comparisons and a mobile-friendly UI.
questions: { s0: boolean, s1: boolean, }
Lint rules written in plain English. Oxlint finds the code, TypeSafe Jev answers the question.
questions: { color: choice, }
Open-source macOS AI computer use and native GUI automation on Apple silicon. Jev + OmniParser CoreML + Apple Vision OCR. Bring your own OpenRouter, Vercel AI Gateway, or TypesafeAI token.
questions: { does_pass: boolean, }
Using Jev as an evaluator.
questions: { value: choice, surprising: boolean, funny: boolean, // +4 }
YouTube transkriptlerini anlamına göre keşfedin. Türkçe arayüz, Jev analizi, altyazı dışa aktarma ve Vercel kurulum rehberi.
questions: { movement: choice, start_jump: boolean, ceiling_hop: boolean, // +1 }
A uv-managed Python prototype that plays NES Super Mario Bros. (level 1-1 by default).
questions: { action: choice, in_danger: boolean, threat: score, }
Experiments in driving real-time games with TypeSafe Jev: a fast
questions: { amount_disclosed: boolean, }
A browsable directory of what Jev can do — 50 runnable
questions: { directed: boolean, kind: choice, }
Auto mode for every coding agent, built on Jev: risk-scores every tool call with session context (deny / ask / allow), flags prompt injection in results, checks skills and plugins. Claude Code, Codex, Copilot, Gemini, Cursor, pi, OpenCode, ACP.
questions: { is_urgent: boolean, department: choice, frustration: score, }
Jev decision layer for agents: MCP server, embeddable DecisionModel library, and an escalate-only Claude Code plugin (TypeSafe AI's Jev)
questions: { team: choice, human_requested: boolean, refund_requested: boolean, // +3 }
Interactive experiments with TypeSafe Jev, from support routing to 3D driving simulations with real AI decisions and visible sensor inputs.
questions: { skill: choice, }
Jev-assisted file retrieval and request caching for faster Pi workflows
questions: { route: choice, }
Jev-powered Instagram, TikTok, and LinkedIn research: typed routing, real browser evidence, streamed post cards, video capture, and cited socai reports.
questions: { noul: boolean, }
typesafe's jev as a "fuzzy linter". give your code an ocular patdown.
questions: { lane_action: choice, speed_action: choice, hazard: score, // +1 }
2D autonomous car simulation in the browser, driven by TypeSafe's Jev decision model
questions: { route: choice, urgent: boolean, severity: score, }
Nemotron Diffusion Decision Lab
questions: { claims_done: boolean, claims_verified: boolean, verification_applies: boolean, // +1 }
Claude Code Stop hook that blocks an unverified done: reads the transcript for evidence, asks Jev once, fails open on everything else
questions: { route: choice, toolFree: boolean, }
Jev-native AI security harness for autonomous research, multi-agent swarms, persistent hunt boards, and long-running agent workflows. CLI-first, open source, and built for authorized security research.
questions: { intent: boolean, }
TypeSafe Jev as the pi coding agent's quiet decision layer
questions: { intent: choice, rage_bait: boolean, synthetic: boolean, // +1 }
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。
questions: { actionable: boolean, priority: choice, value: score, }
Open-source Jev log triage for OpenTelemetry. Score the signal before expensive LLM analysis.
questions: { is_bug: boolean, team: choice, urgency: score, }
Claude Code / Codex / pi plugin that hands agent steps needing no text output to Jev (TypeSafe's judgment model) — measured p50 ~230 ms and ~$0.02 per 1,000 judgments, with typed escalation back to the LLM
questions: { topic: choice, }
Evidence-backed use cases, patterns, and guidance for building with Jev, TypeSafe AI's System One model. Every claim is labeled and sourced.
questions: { category: choice, urgency: score, isPersonal: boolean, }
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.
questions: { unambiguous_match: boolean, }
Policy-bounded Jev target selection for resilient Playwright workflows
questions: { call_t1: boolean, }
Verbatim Jev-scored context reduction for omp, over TypeSafe or OpenRouter
questions: { intent: choice, isUrgent: boolean, }
Flue agent routing with TypeSafe Jev through Cloudflare AI Gateway
questions: { a: boolean, b: boolean, }
Inspired by TypeSafe Ai, Ask a local LLM typed questions, get calibrated probabilities instead of text. Structured output without generation or parsing. MLX / Apple Silicon.
questions: { billing: boolean, urgency: score, }
A small async LangGraph workflow that sends a mocked email to TypeSafe's Jev model,
questions: { context_needed: choice, }
Pi coding-agent extension: TypeSafe Jev checks for tool calls, tool outputs and replies (prompt injection, approvals, secret scrubbing, task pinning)
questions: { beauty: boolean, cat: choice, }
grep for what code does, not what it's called. Semantic code search powered by TypeSafe Jev.
questions: { irreversible: boolean, goal_done: boolean, }
AskJev — Jev autopilot for any website + guard on irreversible clicks (TypeSafe System One, not Claude)
questions: { partial: boolean, score: boolean, }
A fast browser agent: Jev picks each action from what is on the page, an LLM reads and plans, and every claim in an answer cites a quote from the page.
questions: { urgent: boolean, }
Connect JEV to MCP clients and compare its judgments against general-purpose LLMs using shared datasets and measurable accuracy.
questions: { category: choice, tech: boolean, ai_written: boolean, }
Chrome extension that labels every post on X (Substance · Humor · Chit-chat · Promo · Junk · AI-written) with TypeSafe Jev, and hides the ones you don't want.
questions: { q1: boolean, }
A small, extensible decision-to-action harness for TypeSafe Jev
questions: { is_spam: boolean, }
Run a JSON Schema through TypeSafe's Jev API, and get JSON back.
questions: { instructions: boolean, }
TypeSafe Jev routing for Oh My Pi, with an opt-in checkpoint orchestrator and editable XDG configuration. Requires Bun = 1.3.14 and OMP = 18.2.3.
questions: { odd: boolean, }
Check whether a number is odd, using a System One model, with a calibrated probability.
questions: { throttle: choice, yaw: choice, pitch: choice, // +3 }
This demo uses Jev from TypeSafe AI to autonomously fly a drone in a random city from point A to point B, avoiding obstacles along the way. A trip costs $0.01.
questions: { unsolicited_promotion: boolean, profile_bait: boolean, scam_or_phishing: boolean, // +5 }
Minimal grammY Telegram anti-spam bot powered by TypeSafe Jev
questions: { operation: choice, }
Jev for Chrome: drives the tab you are looking at with TypeSafe Jev, a sub-second decision model. Community port of browser-use/jev-ultrafast, not affiliated with TypeSafe.
questions: { about: boolean, keep: choice, }
TypeSafe System One / Jev community directory — GitHub projects & posts around typed decisions (typesafe.ai)
questions: { is_spam: boolean, folder: choice, suspicion: score, }
Jev Explained
questions: { connected: boolean, }
Jev DSH 决策引擎|面向 Agent Harness 的结构化决策插件。原生支持 DeepSeek Harness,通过 iPolloWork 支持 OpenCode、Codex Harness。
questions: { operation: choice, click_target: choice, goal_reached: boolean, // +1 }
Fast, bounded browser agents powered by Jev and agent-browser — typed actions, research, classification, and safe orchestration.
questions: { department: boolean, frustration: boolean, }
Ruby client for typesafe.ai
questions: { delivery: boolean, department: choice, urgency: score, }
Adapt local language models into Jev-compatible structured decision engines with Choice, Score, and Noul outputs powered by prefill-only binary inference.
questions: { done: boolean, }
A chatbot from typed Jev decisions: hierarchical speculative decoding over System One probabilities.
questions: { is_impossible: boolean, }
Jev-powered decision layer for DeepSeek Harness
questions: { is_urgent: boolean, frustration: score, }
Claude Code plugin that scores review findings, debug hypotheses and design options with TypeSafe's Jev — calibrated probabilities instead of one more opinion.
questions: { is_urgent: boolean, }
Agent-facing TypeSafe Jev (System One) for the DSH Web GUI. The model itself
questions: { routine: boolean, }
SQL with natural-language predicates, powered by TypeSafe's Jev. Filter, rank, classify and score rows by meaning — batched, cached and cost-guarded.
questions: { automated: boolean, }
A small Chrome extension that marks or collapses likely AI-written replies on X, powered by Jev.
questions: { done: boolean, blocked: boolean, }
jev-browse is an unofficial project and isn't affiliated with TypeSafe or Vercel.
questions: { intent: boolean, target: boolean, site: boolean, // +5 }
Türkçe ve İngilizce doğal konuşmayla Windows 10/11 bilgisayar kontrolü: OpenAI Realtime, local Whisper, Jev, UI Automation ve Playwright.
questions: { department: choice, frustration: score, is_urgent: boolean, }
DSH bundle that registers jev_ask for TypeSafe Jev noul, choice, and score answers.
questions: { instructions: boolean, }
Runtime constraints for the pi coding agent: checks every side-effecting tool call against what you said, before it runs. Powered by TypeSafe Jev.
questions: { urgent: boolean, }
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.
questions: { what: choice, }
Operator lab for TypeSafe Jev. Chess Arena, closed-schema booths, Stockfish HUD for review only.
questions: { t: boolean, }
Your feed, your rules, in plain English. A browser extension that filters X, YouTube, Reddit, LinkedIn and Hacker News with topics you write yourself. Bring your own Jev key.
questions: { model: choice, effort: choice, is_followup: boolean, }
Local proxy that picks the Claude model and effort per message using TypeSafe Jev. Routes subagents, leaves your cached main chat alone.
questions: { needs_skill: boolean, }
Claude Code mod that routes decisions to TypeSafe's Jev model: ranks installed skills per prompt, and answers the agent's own this-or-that questions when confident.
questions: { confidentiality: choice, }
JEV Document Classification enables the rapid and cost-effective classification of text-based documents using AI, leveraging TypeSafe's "System One" model.
questions: { comparison: choice, }
Jev powered OpenCode compaction
questions: { blocking: boolean, }
Input moderation for Mastra agents on TypeSafe Jev — one file
questions: { department: choice, }
Measure when to use Jev and other models on your data, then route accordingly.
questions: { content_type: choice, }
Fast structured Android control loops with TypeSafe Jev and Mobile MCP
questions: { is_command: boolean, complete: boolean, }
Draw on a tldraw canvas with your voice and a pointing finger. Jev (TypeSafe System One) decides action, target and place in ~350 ms per spoken word.
questions: { department: choice, frustration: score, is_urgent: boolean, }
Jev-compatible System 开源Jev
questions: { requires_uncertainty_notice: boolean, response_depth: score, }
A polished OpenAI + TypeSafe Jev terminal interface for answers with transparent decision reports
questions: { verdict: choice, should: boolean, doom: score, // +1 }
We ask Jev, TypeSafe AI's System One model, whether AI should kill us all. Every ten minutes. Using the actual headlines.
questions: { difficulty: score, needs_reasoning: boolean, stakes: score, // +5 }
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.
questions: { category: choice, reached_assertion: boolean, missing_context: boolean, }
Open-source Codex plugin for TypeSafe Jev decision consultation, failure diagnosis, and evidence-based completion review
questions: { is_toxic: boolean, is_profane: boolean, severity: score, // +2 }
Fast, drop-in profanity and toxicity screener for Node.js, powered by TypeSafe AI Jev. Catches leetspeak, character spacing, and romanized profanity across languages including Kannada, Telugu, Tamil, Hindi, and Bengali. ~50-500ms latency.
questions: { complexity: score, needsPlanning: boolean, }
Throwaway Jev demo: route coding tasks to Grok Build or Codex Astra
questions: { ping: boolean, }
Codex plugin: Jev-guided dieting of bulky tool results
questions: { task_completion: score, instruction_following: boolean, grounded_in_evidence: boolean, // +5 }
Affordable for parallel online agent evals and observability. Powered by JEV.
questions: { is_billing: boolean, }
Build versioned judgment functions on TypeSafe's Jev once, then call the same published version from your backend over HTTP and from coding agents over MCP. The vendor key stays on your machine.
questions: { complete: boolean, }
Open-source native computer use for macOS and Windows: TypeSafe Jev, local OCR, and selective planning.
questions: { wants_refund: boolean, intent: choice, }
Runtime authorization and guardrails for AI-agent tool calls with deterministic policy and TypeSafe Jev via OpenRouter.
questions: { operation: choice, }
Manipulate images via chat, uses Jev like model to classify prompt
questions: { destructive: boolean, exfiltration: boolean, privilege: boolean, // +4 }
Open auto mode for AI agents — a calibrated tool-call firewall powered by TypeSafe Jev. Ships as a Claude Code hook
questions: { enabled: boolean, color: choice, progress: score, }
Local JEV-style decisions with DiffusionGemma on Apple Silicon, with benchmarks and coding-agent examples.
questions: { category: choice, bug_severity: score, has_repro_steps: boolean, // +2 }
MCP server and agent skill for the TypeSafe AI System One API (Jev): decompose a judgment into Choice / Score / Noul questions, lint them, measure on labelled data, and put calibrated thresholds in code
questions: { action: choice, }
Jev and Microsandbox explore alternate game futures with a reusable TypeScript learning harness
questions: { content_type: choice, already_known: boolean, insight_density: score, }
Know before you click. A Chrome extension that reads articles and YouTube videos ahead of you and says read, skim, save, or skip — with a confidence, tuned to your goals. Open source, MV3, powered by Jev.
questions: { completion: choice, }
One grounded Jev/Playwright core: typed SDK, persistent CLI, and MCP server with native browser operations and deterministic assertions.
questions: { relevant: boolean, category: choice, }
PiJev: a terminal coding agent with Jev in the loop — Jev ranks the repository's files before the first call, picks skills and triages failures; your coding model writes the code. Built on Pi.
questions: { hallucination_sensitive: boolean, }
Type-safe model router. Jev (System One) banks each request to a typed catalog route.
questions: { ping: boolean, }
Yunus Pi is a heavily customized harness experience built on top of a forked Pi harness (pi.dev). It uses patches, extensions, skills, and custom provider configs to customize the overall experience. It uses advanced machine learning, Jev, Cactus Needle 3 and similar technologies.
questions: { criteria: boolean, }
Jev-powered Chrome extension that categorizes X posts and classifies replies in context.
questions: { claims_success: boolean, }
Find the AI agent runs that broke because their environment did: missing keys, tools, files, permissions, network, or context. Powered by TypeSafe Jev.
questions: { label: choice, }
Owned, deterministic classifier for checking whether agent claims are supported by evidence, with optional Jev comparison through Cloudflare AI Gateway.
questions: { irreversible: boolean, }
Pydantic AI capabilities made stronger with Jev: small runnable demos, one file each
questions: { composition: choice, legibility: boolean, }
Image-native typed decisions with shared visual encoding and Qwen3-VL
questions: { is_urgent: boolean, severity: score, }
Shadow-mode validation harness for a pre-execution firewall on AI agent tool calls (TypeSafe/Jev). Real run, findings in report.md.
questions: { action: choice, asset: choice, condition_operator: choice, }
Reference prototype exploring agentic commerce: TypeSafe/Jev → Axiom → Argent → Silverscript on Kaspa.
questions: { tier: choice, is_greeting: boolean, }
Jev (TypeSafe) model router on the Vercel AI Gateway
questions: { line: choice, pace: choice, overtake: boolean, // +1 }
Uses jev to control race cars on a virtual track
questions: { severity: score, area: choice, }
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.
questions: { destructive: boolean, secrets: boolean, }
Jev-powered Judgment layer for Claude Code. Stops paying reasoning prices for if-statements: a PreToolUse hook scores every tool call against a YAML policy you own — allow / deny in ~100 ms, no LLM in the loop. TypeSafe Jev now, local models next. Dry-run by default, calibration table published.
questions: { is_exquisite_and_dynamic: boolean, animation_verdict: choice, primary_deficiency: choice, }
Real-time quality gate and Art Director Warden for Claude Code powered by TypeSafe Jev 1.13 non-autoregressive decision model
questions: { person_name: boolean, email_or_phone: boolean, postal_address: boolean, // +5 }
CLI that finds PII in text with TypeSafe Jev: presence, sensitivity, and located spans
questions: { is_regulation: boolean, mentions_deadline: boolean, mentions_fines: boolean, // +5 }
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.
questions: { topic: choice, requests_credentials: boolean, sender_identity_mismatch: boolean, // +4 }
Experiments on TypeSafe Jev (System One decision model) via OpenRouter: repeatability, perturbation, and LLM baseline comparison
questions: { needs_rewrite: boolean, visual: choice, }
Pi extension: clearer replies via Jev review + optional rewrite/visuals
questions: { states_application_instruction: boolean, }
Upwork job classification example
questions: { a: boolean, b: boolean, }
A Chrome extension that brings TypeSafe's Jev to X.com to analyze posts as you browse
questions: { is_urgent: boolean, department: choice, }
Opencode plugin using Jev (system one model) as part of software development process. Not affiliated with Opencode team.
questions: { file_removal: score, credential_theft: score, data_exfiltration: score, // +5 }
Static shell script analysis with Jev.
questions: { kind: choice, relationship: choice, review_priority: score, }
面向开发者的 Jev / TypeSafe 精选:说明每个项目里 Jev 负责哪一步、先读哪段源码、需要什么依赖,以及哪些结论还没有运行验证。
questions: { uses: boolean, }
Configurable GitHub submission review and PR classification with TypeSafe Jev. No text-generation model.
questions: { ok: boolean, }
Unofficial CLI for the TypeSafe System One API (Jev) — designed for AI agents and anything that can execute a process.
questions: { alive: boolean, }
Jev, TypeSafe's System One classifier, as a tool inside Claude Code, Codex, Pi, and OpenCode: typed classify, check, score, rank, and ask, plus one-command setup.
questions: { urgent: boolean, severity: score, }
Node client for decision models such as Typesafe Jev
questions: { outOfScope: boolean, contradictsPrevious: boolean, shouldFlag: boolean, }
Every tool call your agent makes, checked before it runs. A Claude Code plugin that uses TypeSafe AI's Jev to verify each pending tool call against the session plan, then allows it, asks you, or blocks it. Proof of concept
questions: { scope_alignment: score, touches_state: boolean, breaks_contracts: boolean, // +2 }
Fast semantic code search & diff sanity auditor for AI coding assistants (Antigravity, Cursor, Claude Code) powered by TypeSafe System One.
questions: { failure_domain: choice, customer_impact: score, systemic_outage: boolean, }
A garage full of tiny experiments for building critical systems with System One & Jev 🔧🧠⚡
questions: { succeeded: boolean, }
CLI for TypeSafe AI's Jev evaluation model — typed questions in, structured JSON answers out
questions: { action: choice, close_intent: boolean, intentional_control: boolean, // +1 }
Jev-based local-first gesture and gaze media-control agent with guarded page-close intent.
questions: { edit: choice, contract: choice, caller: choice, // +2 }
Semantic code review with Jev, plain-English rules and Agent Skills.
questions: { next_move: choice, }
Chakravyuha — a polar ring-maze where every move is a Jev (TypeSafe System One) decision. A fun experiment: the model picks each move, the walk grades it green or red, and the history page asks whether its confidence score can be trusted. BYOK, no build step.
questions: { same_intent: boolean, }
Skip expensive LLM calls when TypeSafe Jev says same intent. OpenAI-compatible local cache proxy — npx @kushalicious/jevcache
questions: { instructions: boolean, }
Smart, dynamic AI filtering for X and YouTube feeds using Jev
questions: { needs_vision: boolean, needs_tools: boolean, }
Pick the best AI model and reasoning effort for any task in ~1s. Plugin for Claude Code, Claude Desktop and Codex, powered by TypeSafe's Jev decision model and live OpenRouter pricing. Balance intelligence, speed and cost, or choose your priority.
questions: { eligible: boolean, }
AI gateway that validates before it executes: Lead plans, JEV validates, Worker generates. Local-first control plane, 359-provider catalog.
questions: { intent: choice, urgent: boolean, frustration: score, }
n8n community node for TypeSafe Jev structured AI decisions
questions: { disposition: choice, risk: score, data_exfil_risk: boolean, // +2 }
Agent tool/MCP call gate — allow / ask_human / deny via TypeSafe Jev
questions: { should_review: boolean, risk: choice, route: choice, // +1 }
GitHub Action that uses Jev (TypeSafe AI via Vercel AI Gateway) to cheaply triage pull requests before expensive LLM/human review
questions: { fraud: choice, }
Use Jev with Kimi K3 for hard classification
questions: { is_project: boolean, substance: score, }
Open-source projects that provably call Jev, TypeSafe AI's System One model. Every entry links to the line of code that proves it. Refreshed daily.
questions: { impact: score, }
TypeSafe AI (jev) 시범 사용 프로젝트
questions: { q: boolean, }
jevkit for JavaScript/TypeScript: static linter and shared record format for building on TypeSafe's Jev (System One) model. Unofficial.
questions: { action: choice, }
Voice and text browser control with Jev, Chrome MV3 and a local AI Gateway bridge
questions: { intent: choice, connection: choice, supported: boolean, }
A small detective escape room built with TypeSafe Jev, React, and Express.
questions: { category: choice, bug_severity: score, wants_refund: boolean, // +1 }
Jev Playground
questions: { is_urgent: boolean, needs_human: boolean, is_financial: boolean, }
Compare GPT generated language with JEV structured Noul decisions on the same input.
questions: { condition: choice, }
Plain-English pull request checks powered by Jev. One condition, a minimum confidence, one check.
questions: { q: boolean, }
Jev-powered context compaction for Pi. Keep critical instructions and tool history, prune the noise, and fall back gracefully.
questions: { answered: boolean, }
list of projects that use typesafe's jev
questions: { risky: boolean, submit_after_typing: boolean, }
Trying automation on web browser via jev from typesafe
questions: { relevance: choice, }
Codex code-search plugin using Jev relevance filtering with auditable token metrics
questions: { billing: boolean, urgent: boolean, team: choice, // +1 }
Jev-like model inference engine + Jev-compatible API
questions: { refund: boolean, }
Complete browser tasks with Ego Lite and actively call Jev for semantic target selection, filtering, ranking, classification and text evidence judgments.
result = post_json("https://api.typesafe.ai/v1/systemone", os.environ["TYPESAFE_API_KEY"], body)i. am. speed.
export const SYSTEM_ONE_URL = 'https://api.typesafe.ai/v1/systemone';
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.
"adaptation": "Native Noul replaced with binary Yes/No Choice; state/question unchanged",
Semantic ifs from open models, on a 3090 at home. Independent; not affiliated with Jev or TypeSafe.
Agent skills for building with TypeSafe's System One API
A curated list of public projects, integrations, and discussions built on Jev — TypeSafe AI's System One model for typed decisions.
from typesafe_sdk import AsyncTypeSafeClient, RetryPolicy
Software factory foreman based on TypeSafe's Jev model
A curated list of official resources and community projects for TypeSafe, System One models, and Jev.
A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.
const url = `${opts.baseUrl ?? 'https://api.typesafe.ai'}/v1/systemone`Tax document page classifier built on Jev decisions. 100% strict accuracy across 261 IRS forms, ~$0.001 per page.
url: 'https://api.typesafe.ai/v1/systemone',
▶ Watch the demo — Jev opens Uber, enters a route from San Francisco Airport to the Golden Gate Bridge, and reaches payment selection. The recorded task timer shows about 21 second
-- jev.api_url default 'https://api.typesafe.ai/v1/systemone' (proxies, mocks, tests)
Ask your Postgres tables questions in plain language. A PostgreSQL extension powered by TypeSafe's Jev.
A curated, source-backed list of projects built with Jev, TypeSafe AI's System One model for typed decisions.
import { choice, score } from "@typesafe-ai/sdk";Route to the cheapest model in claude code for your task using jev-router
"jev (TypeSafe stepper)": ("typesafe_sdk", "quackd[jev]"),One CLI for all your robots. Connect them, command them, and let them work together, each with an LLM for a brain, Jev for cheaper steps. Microduck, Open Duck Mini, LeRobot, XLeRobot, AlohaMini, ToddlerBot or any ROS base. Claude, OpenAI, Gemini, Grok, or local via Ollama or vLLM. Simulator, .duck safety contracts, MCP, memory between runs, flocks.
typesafe: {endpoint:'https://api.typesafe.ai/v1/systemone',keyName:'TYPESAFE_API_KEY',model:'jev-latest',modelPattern:/^jev-[a-z0-9.-]{1,80}$/},5–10x faster browser operations: Jev clicks, Codex thinks and verifies. Built at EZCollegeApp.
"/v1/systemone",
Jev-compatible API endpoint based on open models (prefill-only)
? "https://api.typesafe.ai/v1/systemone"
Self-hosted, versioned skills library for AI agents. MCP, scoped clients, and optional Jev recommendations.
export const JEV_API_ENDPOINT = "https://api.typesafe.ai/v1/systemone";
Local-first MCP plugin for continuous software-quality review by AI coding agents, powered by Jev.
export const DEFAULT_BASE_URL = "https://api.typesafe.ai";
The official TypeScript/JavaScript library for the TypeSafe API
"description": "Qwen3.5-0.8B-Base fine-tuned on frames labelled by ten per-game search programs to play ten browser games from 448 px screenshots, reading a pro
A source-backed Jev project directory with a reusable Jev-only GitHub review workflow.
from typesafe_sdk import AsyncTypeSafeClient, Choice, Noul, Score
Build calibrated AI classifiers from human feedback using Jev and GEPA.
baseUrl = 'https://api.typesafe.ai/v1',
Semantic code linting with Jev
import { TypeSafeClient } from "@typesafe-ai/sdk";Browser use using Typesafe's Jev model
parser = argparse.ArgumentParser(description="Local visual Choice/Noul/Score judgments")
An educational Jev-like visual inference experiment on Apple Silicon: shared context, direct candidate scoring, and local visual demos.
"""Jev-compatible HTTP API: POST /v1/systemone and GET /v1/models.
Open, Jev-compatible System One decision server on DiffusionGemma
export const TYPESAFE_ENDPOINT = "https://api.typesafe.ai/v1/systemone";
WXT browser extension: Jev-powered page clutter removal with reusable template rules.
? "> 💡 **如何快速复核**:如果项目中已接入 Jev / TypeSafe 决策机制(例如 Dart、Go、Rust、Java、Python、TS/JS 等多语言 SDK,或 OpenRouter decisions、`/v1/systemone` 调用),欢迎直接在本 Issue 中回复补充包含决策调用的*
Awesome Jev: source-backed open-source ecosystem radar, plain-language project discovery, and automatic GitHub sync
@app.post("/v1/systemone", response_model=SystemOneResponse)A self-hosted drop-in replacement for TypeSafe's jev, powered by GliFormer.
import { choice, noul, score } from "@typesafe-ai/sdk";Fast, cheap, typed judgments from TypeSafe's Jev model, as MCP tools.
"name": "jev",
A skill for writing and improving programs that call Jev, TypeSafe's System One model
if r.URL.Path != "/v1/systemone" || r.Header.Get("Authorization") != "Bearer k" {mcp connector to give your AI agent direct access to typesafe ai's jev model
export const SYSTEM_ONE_URL = 'https://api.typesafe.ai/v1/systemone';
Claude Code plugin: trim long Bash output with TypeSafe Jev before the model sees it
const res = await fetch("https://api.typesafe.ai/v1/systemone", {A playable Three.js driving simulator with Jev-powered autopilot
typesafe: { host: "api.typesafe.ai" },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
res = await fetch('https://api.typesafe.ai/v1/systemone', {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
import { TypeSafeClient, choice, noul, type ChoiceCriteria, type EntryType } from "@typesafe-ai/sdk";🇺🇸 English · 🇧🇷 Leia em português
A curated list of awesome Jev / TypeSafe System One applications, libraries, and resources.
"jev": j_val,
Calibrated 151M Non-Autoregressive Decision Engine beating TypeSafe Jev & Laya on LocalLLaMA/typed-decisions (77.10% acc, 0.0636 Brier, 0.0144 ECE)
"https://api.typesafe.ai/v1/systemone"
Pre-alpha PostgreSQL extension for TypeSafe AI (Jev) categorical classification
Jev takes a state plus a set of typed questions (Choice, Score, Noul) and returns typed answers with calibrated probabilities in one request, no text generation
A community directory of projects built on Jev, TypeSafe AI's System One model.
apiBase: 'https://api.typesafe.ai',
Detect youtube sponsor segment with live audio and transcript powered by Jev
🔥🔥 Papers, open reproductions and independent evaluations behind System One models and Jev.
return False, f"could not reach api.typesafe.ai ({e.__class__.__name__}); check your internet connection"Put a live Jev (TypeSafe) meter on any video: every sentence scored, rendered as a 16:9 edit
//! port, empty or root path only. Canonical origins append `/v1/systemone`
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.
"""One small, strict client for TypeSafe Jev (POST /v1/systemone).
Jev-powered model routing, memory, compaction, skill selection, computer and browser use for Hermes agents (also Claude Code and Codex)
import { TypeSafeClient } from "@typesafe-ai/sdk";Fish-style zsh history autosuggestions ranked by Jev (TypeSafe)
v = sub.add_parser("serve", help="HTTP server with the model loaded once (POST /score, /v1/systemone)")Open Jev implementation with custom finetuning
// Docs: https://docs.typesafe.ai/api (POST /v1/systemone, Noul questions)
🧹 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.
// mock-jev: a local stand-in for TypeSafe's `POST /v1/systemone`, for driving the router
A local LLM gateway for coding agents. When your agent is about to decide which tool to call,
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Curated Jev resources and runnable examples for typed AI decisions.
baseUrl: process.env.JEV_BASE_URL || 'https://api.typesafe.ai/v1/systemone',
Portable, Jev-guided context compaction for coding agents.
import { createLiveTypeSafeClient, type TypeSafePort } from "../semantic/typesafe-client.js";CLI that picks Cursor, Claude Code, Codex, or OpenCode + model/effort for a task, then launches it. Powered by Jev and Herdr
import { TypeSafeClient, type EntryType, type Questions } from "@typesafe-ai/sdk";A tool calling chat bot built with Jev and no LLM.
"name": "Jev",
Jev-style parallel constrained decisions for any MLX model on Apple Silicon. Typed, schema-valid JSON in one forward pass.
from typesafe_sdk import AsyncTypeSafeClient, TypeSafeError
Typesafe.ai System One Model Jev navigating a Neo4j graph by using a classifier over neighbouring relationships
const res = await fetch(`${options.baseURL ?? 'https://api.typesafe.ai'}/v1/systemone`, {Route HTTP requests by meaning. A semantic router for Hono powered by Jev.
ENDPOINT = 'https://api.typesafe.ai/v1/systemone'
Use Jev to make art!
url: "https://api.typesafe.ai/v1/systemone",
Jev picks which of your rules apply to each prompt, so Claude only sees the ones that matter.
base_url: str = "https://api.typesafe.ai",
A Discord moderation bot built with Python and TypeSafe AI (Jev System One). It filters spam and scam links in real time, escalates offenses automatically, and lets moderators prof
var request = URLRequest(url: URL(string: "https://api.typesafe.ai/v1/systemone")!)
Say it, and your Mac does it. A computer-use harness on Jev that reads the screen through Accessibility. Fast, no vision 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.
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Skill for Hermes, and other agents, to ask typesafe's jev
API_URL = "https://api.typesafe.ai/v1/systemone"
Control Ableton Live with one short sentence (Japanese / English). Summon with ⌘⇧Space, type or dictate, done.
url, default_model, prefix = "https://api.typesafe.ai/v1/systemone", "jev-latest", "TYPESAFE"
A Jev powered LinkedIn recruiting agent. Watch it browse relevant profiles, save links, and review evidence against your hiring brief.
const res = await fetch("https://api.typesafe.ai/v1/systemone", {Typed decisions with TypeSafe's Jev, the first System One model
import { TypeSafeClient } from "@typesafe-ai/sdk";Live Jev trader on Hyperliquid
Self::Typesafe => "https://api.typesafe.ai/v1/systemone",
Semantic grep: find code by describing what you're looking for, powered by Jev.
"jev": j_val,
Non-autoregressive decision engine on ModernBERT (151M) with calibrated uncertainty (RLCD), TypeSafe AI Jev benchmark audit, and in-browser WebGPU playground
endpoint: "https://api.typesafe.ai/v1/systemone".into(),
Classify Git commit diffs and messages with Jev. Bug fixes, security fixes/CWEs, and change types.
return self.async_create_entry(title="Jev", data={CONF_API_KEY: api_key})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.
import { choice, TypeSafeClient, type Usage } from "@typesafe-ai/sdk";Codebase search powered by Jev from @typesafe-ai
base_url: str = "https://api.typesafe.ai",
Read-only trading journal and review harness: Jev typed judgments, agent integration, and a reproducible finance benchmark. No orders, no advice.
const validUrl=url.protocol==='http:' && url.hostname==='127.0.0.1' && /^\d+$/.test(url.port) && url.pathname==='/v1/systemone' && !url.username && !url.passwor
TypeSafe Jev action selection inside Codex Computer Use
self.http.get("https://api.typesafe.ai/v1/models")Talk to your Mac. Local whisper.cpp + one Jev (TypeSafe) call per command + macOS automation.
"joshmn/typesafe-sdk": {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。
export const API_URL = process.env.JEV_API_URL || "https://api.typesafe.ai/v1/systemone";
Browser automation where an LLM plans and Jev (Typesafe System One) decides. Library, CLI and MCP server.
# baseUrl: https://api.typesafe.ai
A linter for the things a linter could never check: whether a function does
@app.post("/v1/systemone", response_model=DecisionResponse)Turn any off-the-shelf LLM into a Jev -like decision layer
"text": "**Live Jev findings — 2026-09-18**\n\n89 live calls against `\nhttps://\napi.typesafe.ai/v1/systemone`, model `jev-1.13.0`. Raw data in `data/probe.jso
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
* Serves the web app in docs/ and relays POST /v1/systemone to TypeSafe, adding the key from
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 your browser.
"""回傳一個已設定好 key 的 TypeSafeClient;拿不到 key 就直接退出、說清楚為什麼。
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。
import { createGateway, experimental_evaluate as evaluate, type Experimental_EvaluationQuestion as EvaluationQuestion } from "ai";Experimental browser agent powered by FX, Jev, and Vercel AI Gateway. Bring your own API key to read pages and automate browser tasks.
import { TypeSafeClient, choice } from "@typesafe-ai/sdk";Snake auto-played by TypeSafe's Jev model: one System One choice per tick, legal moves and facts generated in code
The transport: one POST to `/v1/systemone` per call.
TypeSafe Jev for OTP: reply to Jev from a GenServer and pattern match on its answer
TypeSafeClient,
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.
jev_raw=label['jev'], jev_reported=label['jev_reported'])
Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results
API_URL = "https://api.typesafe.ai/v1/systemone"
TypeSafe Jev controls original StarCraft shareware through keyboard and mouse with recorded action probabilities.
* - api.typesafe.ai (commercial Jev, "System One")
⚡ 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
const json = await postJson(fetchImpl, "https://api.typesafe.ai/v1/systemone", key, jevRequest(batch, model));
Jev vs Gemini 3.8 Flash: labelling 1,000 app reviews, 4.1× faster and 7× cheaper
keywords = ["jev", "typesafe-jev", "open-source-jev", "jev-alternative", "system-one", "system-one-model", "llm", "classification", "structured-decisions", "typ
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
const ENDPOINT: &str = "https://api.typesafe.ai/v1/systemone";
Rust linter powered by configurable Jev rules, with a VS Code extension.
baseURL: "https://api.typesafe.ai",
原版 Pi Coding Agent 插件:按时机配置规则,并自带风险检查、输出脱敏、重复失败和缺少验证提醒。
from typesafe_sdk import TypeSafeError
The invalidation layer for AI memory. Every fact gets a lease; new evidence ends it. Built on TypeSafe Jev.
static constexpr const char *SYSTEMONE_PATH = "/v1/systemone";
DuckDB extension: typed Jev answers as real SQL types
for k, name in [("noul", "Noul (yes/no)"), ("score", "Score (rubric level)"), ("choice", "Choice")]:Open replica of TypeSafe's Jev: typed calibrated decisions in one forward pass, on Gemma 4 E2B / Gemma 3 270M (Modal)
DEFAULT_BASE_URL = "https://api.typesafe.ai"
Retrieve by relevance, not resemblance: filter an AI assistant's memories with TypeSafe's Jev
TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone"
Trading bot with the all new TypeSafe AI's first system one model named as Jev
Grill-me with Jev optional each turn
"typesafe": Backend("typesafe", "https://api.typesafe.ai/v1/systemone", "jev-latest", "TYPESAFE_API_KEY"),grep, but the pattern is a description. Filters lines by meaning with TypeSafe's Jev decision model: ~200 ms and a thousandth of a cent per line.
export const JEV_PATH = "/v1/systemone";
Chrome extension that labels every post you scroll past on X with typed Jev judgments and a live cost counter
from typesafe_sdk import Choice, TypeSafeClient
Probability-aware evaluation for typed decision models: calibration, selective risk, latency, and reproducible benchmarks.
endpoint: "https://api.typesafe.ai/v1/systemone".to_string(),
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
logging.getLogger("typesafe_sdk").setLevel(logging.WARNING)MCP server for TypeSafe Jev: typed classify, score, check, match and screen for any agent, with confidence on every answer
keywords: ['Jev', 'TypeSafe AI', 'System One model', 'Jev SDK', 'Jev tools', 'Jev agents', 'open-source AI'],
A verified, community-maintained catalog of 433 open-source projects built with Jev.
"mechanism": "Pinned code builds state from the method, URL, headers and a truncated textual body, then asks one Noul question per route in a single call. The f
看看 Jev 能做什么:用中英文讲清热门应用、工作原理和各自优缺点。Explore Jev apps with plain-language examples, explanations, and comparisons.
import { type Questions, TypeSafeClient } from "@typesafe-ai/sdk";Command-line tool for TypeSafe's Jev AI model
GROUPS = ('jev', 'llm')Jev vs GPT-6 Astra vs GPT-4.1 mini: direct Cartesian control of an xArm7 in MuJoCo.
id: "jev", name: "Jev (TypeSafe AI)",
Monitoring & Safety layer for all your agents. Open Source CLI & Skills for Claude Code, Codex, Cursor, Jev and your preferred agents.
endpoint = "https://api.typesafe.ai/v1/systemone"
A claude code plugin for jev
"typesafe": ("https://api.typesafe.ai/v1/systemone", "jev-latest", "TYPESAFE"),Fine-grained robot control with Jev, physics previews, and configurable LIBERO tasks.
const response = await fetch("https://api.typesafe.ai/v1/systemone", {Configurable semantic linting powered by Jev, with file-level NOUL judgments and a magic-strings plugin.
/// Defaults to `https://api.typesafe.ai`. Path prefixes are preserved when the
Typed TypeSafe AI clients for Rust, with async and blocking backends and observable retries.
import { experimental_evaluate, generateObject, type Experimental_EvaluationQuestion } from "ai";Everyday Stocks Status with Jev
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
An agent skill to discover TypeSafe Jev opportunities, design typed questions, and learn from recent community experiments.
Evidence-backed index of real-world Jev (TypeSafe AI System One) use cases: repos, patterns, benchmarks, and measured results
# ---------------------------------------------------------------- TypeSafe Jev 互換 (POST /v1/systemone)
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
"jev",
⚡ Sub-100ms cognitive reflexes for autonomous coding agents. Powered by TypeSafe AI's Jev & get-fable.
id: i ? 'deepseek' : 'jev',
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。
import { choice } from '@typesafe-ai/sdk';Interactive TypeScript coding CLI powered by Jev typed decisions and constrained AST generation.
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
An experimental JEV-powered framework for forecasting short-term stock price direction from structured market data.
from typesafe_sdk import ChoiceAnswer, JSONContent, NoulAnswer, ScoreAnswer, SystemOneResponse
Python 3.14. Get an API key from console.typesafe.ai and put it in .env:
DEFAULT_BASE_URL = "https://api.typesafe.ai"
Stop guessing confidence thresholds: calibrate, threshold, and drift-check typed decision models (TypeSafe Jev) against an LLM teacher.
"https://api.typesafe.ai/v1/systemone", data=body,
PoC: TypeSafe Jev as the reviewer for Hermes Agent smart command approvals. 8.7x faster, 4.4x fewer prompts, measured on 153 real commands. Approvals only.
.feels() on anything — the AI if statement as a real, typed method. Jev + BAML.
const r=await fetch('https://api.typesafe.ai/v1/systemone',{AI Music (MIDI) generator powered by Jev
"base_url": "", # default https://api.typesafe.ai
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.
_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Typed, confidence-aware agent skill routing with TypeSafe Jev.
TYPESAFE_BASE_URL = "https://api.typesafe.ai"
Typed System One decisions, ranking, verification, and an opt-in Hermes tool gate using TypeSafe Jev.
SYSTEMONE_URL = "https://api.typesafe.ai/v1/systemone"
Classify your inbox with Jev (TypeSafe's System One model) — tag, move, flag, and notify, all config-driven.
DefaultBaseURL = "https://api.typesafe.ai"
Go SDK for the TypeSafe AI API — typed questions in, probability distributions out.
// SystemOne asks questions about a state via POST /v1/systemone.
unofficial go sdk for typesafe ai
'provider': provider, 'base_url': 'https://ai-gateway.vercel.sh/typesafe' if vercel else 'https://api.typesafe.ai',
Linux, macOS ve Windows için kaynaklı ikinci beyin. Claude Code, Codex ve Antigravity adaptörleri; yerel Markdown kasa, ayrı hafıza incelemesi, isteğe bağlı Mem0/Jev.
* `POST /v1/systemone` の応答のうち、判定に必要な部分だけを検証する。
Zod validates the shape. Jev validates the meaning.
defaultAPIURL = "https://api.typesafe.ai/v1/systemone"
Semantic SQL for Postgres, powered by Jev
import { createGateway, experimental_evaluate as evaluate } from "ai";Automatic model routing for Pi using TypeSafe's Jev through Vercel AI Gateway
const result = (await postJson("https://api.typesafe.ai/v1/systemone", key, body)) as {Fast browser agent for ego lite. One TypeSafe request per step; an agent or Jev picks the move.
MODEL = os.environ.get("JEV_MODEL", "jev-latest")Rebuild a site's internal link map in seconds with Jev, race Claude Opus 5 on the same queue, and let a deep model rewrite the rubric from the disagreements.
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
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.
TypeSafeClient,
Observable browser stealth game: Jev makes typed guard judgments while deterministic code owns the world.
TRACKED_PACKAGES = ["httpx", "numpy", "pydantic", "PyYAML", "typer", "typesafe-sdk"]
Reproducible benchmark for measuring Jev reranking quality, latency, and cost in RAG
export const ENDPOINT = 'https://api.typesafe.ai/v1/systemone';
Filter any live Twitch chat with Jev: a bring-your-own-key Chrome extension
import { experimental_evaluate as evaluate } from 'ai';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.
from typesafe_sdk import Noul, RetryPolicy, TypeSafeClient
Use Jev (TypeSafe's System One model) as a calibrated reranker: one call, up to 30 documents, a probability per document. Apache-2.0.
-X POST https://api.typesafe.ai/v1/systemone \
Agent-first Haskell DSL for TypeSafe's Jev judgment model: typed packets, inferred types, answers under the same labels
import { choice, noul, score, type ChoiceResponse, type NoulResponse, type ScoreResponse } from "@typesafe-ai/sdk";Content artifact for a Buivo post about System One models. Working name, pending final brand sign-off.
"typesafe": Backend("typesafe", "https://api.typesafe.ai/v1/systemone", "jev-latest", "TYPESAFE_API_KEY"),sort by meaning: order lines along a plain-English dimension, from pairwise comparisons judged by TypeSafe's Jev model
// "~typesafe/jev-latest" always points to the newest Jev. The tilde matters:
Practical, tested recipes for TypeSafe's Jev decision model on OpenRouter: support triage, database indexing, file organizing, tagging, taxonomies, dedupe, PII detection, extraction, search re-ranking and a browser agent.
DEFAULT_URL = "https://api.typesafe.ai/v1/systemone"
Typed semantic decisions for Unix pipelines and CI, powered by TypeSafe AI Jev.
typesafeBaseUrl: "https://api.typesafe.ai/v1",
Checks risky shell and file commands before your agent runs them.
"endpoint": "https://api.typesafe.ai/v1/systemone",
Small dependency-free CLI for TypeSafe Jev
base_url="https://api.typesafe.ai", retry=RetryPolicy(max_retries=1),
TypeSafe AI Jev judgments for Agent Zero, with typed tools and probability cards.
A curated list of tools, integrations, and experiments built on Jev, TypeSafe AI's System One model for fast, typed decisions.
const { raw, ms } = await post('https://api.typesafe.ai/v1/systemone', ts, buildPayload(model, text, prev, chapter));Jev reads a whole novel in seconds. Every passage becomes a row of colour.
import { choice, noul, TypeSafeClient, type EntryType } from "@typesafe-ai/sdk";1v1 Jev quickscope arena — Three.js + TypeSafe System One
Public examples of Jev used for robot control, 3D modeling and adjacent control tasks, with sources and archived media
* TypeSafe-compatible /v1/systemone (native typed interface).
JevBench v1 - a benchmark for Jev-class typed decision models: smart, cheap, fast, reliable, open.
source: "jev" | "local";
Reusable machine-learning primitives for Jev — PCA, MCMC, text diffusion, neural cellular automata, and a task harness that picks the right tool.
export const SYSTEM_ONE_URL = "https://api.typesafe.ai/v1/systemone";
Pi extension: verbatim context compaction with TypeSafe Jev decisions
from typesafe_sdk import Choice, RetryPolicy, TypeSafeClient
Reproducible early-access evaluation of Jev on Korean understanding and medical text, with runtime and cost evidence
baseURL: URL = URL(string: "https://api.typesafe.ai")!,
An independent, type-safe Swift SDK for TypeSafe Jev, with async/await, batching, retries, and SPM support.
import typesafe_sdk
High-speed recursive AI Elo tournament engine powered by Jev and Swiss matchmaking
export const DECISIONS_URL = 'https://api.typesafe.ai/v1/systemone'
Talk to your camera, and Japanese variety-show captions and manga effects appear on their own, matched to what you are saying.
response = await this.fetcher("https://api.typesafe.ai/v1/systemone", {Check Pi code edits against repository Markdown rules with TypeSafe Jev
/// Retrying is safe for this API: <c>POST /v1/systemone</c> is a stateless evaluation call, and a
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.
from typesafe_sdk import AsyncTypeSafeClient, Choice, RetryPolicy, TypeSafeError
A small, fast prose linter: ruff-style rule codes for writing, backed by TypeSafe's Jev model
val DefaultBaseUrl: Uri = Uri(scheme = "https", host = "api.typesafe.ai")
Scala SDK for Jev. No effect system bundled.
export const TYPESAFE_BASE = process.env.TYPESAFE_API_BASE || "https://api.typesafe.ai";
Jev play Tetris in real-time against other AI models
DEFAULT_BASE_URL = "https://api.typesafe.ai"
pre-commit hook: one Jev call judges whether your commit message matches the diff, plus debug leftovers, scope creep, and a secret belt
export const ENDPOINT = "https://api.typesafe.ai/v1/systemone";
A word-level language model whose output layer is Jev: n-gram drafter, Noul chunk verification, bits-per-token eval
MODEL = "typesafe/jev-1.13"
Semantic GitHub PR labels using Jev's typed decisions, with conceptual scope instead of line counts
} from "@typesafe-ai/sdk";
Hybrid coding harness: System 2 writes, System 1 (Jev) runs reflexes.
public static let defaultBaseURL = "https://api.typesafe.ai"
Unofficial Swift library for the TypeSafe API
import { TypeSafeClient } from "@typesafe-ai/sdk";Neon Function proxy for the Neon AI Gateway with TypeSafe Jev routing.
self.model = os.environ.get("JEV_MODEL", "typesafe-ai/jev")A coding agent that filters every tool result through Jev before the model sees it, with an A/B harness measuring pass@1 and cost against the unfiltered control
import { experimental_evaluate as evaluate } from 'ai';Calibrated alignment verifier for LLM responses and agent plans — powered by Jev
var request = HttpRequest.newBuilder(URI.create("https://api.typesafe.ai/v1/systemone"))Jev from plain Java 25. No framework, no dependencies, one HTTP call.
SYSTEM_ONE_PATH = "/v1/systemone"
daf-jev: composable Python toolkit for TypeSafe's Jev (System One) decision API — question builders, confidence gates, evaluator, calibration, CLI, MCP server, agent skill
model: undefined, // undefined = advocaat default (jev-latest / typesafe-ai/jev)
Turn your AGENTS.md preferences into a fast, Jev-powered AI linter.
export const SYSTEM_ONE_URL = 'https://api.typesafe.ai/v1/systemone'
Jev-scored context compaction for OpenAI Codex CLI — scores every tool call before compaction and restores critical tool outputs verbatim after it
for name,url,key in [('openrouter','https://openrouter.ai/api/v1/models',auth['OPENROUTER_KEY']),('typesafe','https://api.typesafe.ai/v1/models',auth['TYPESAFE_Comparing Jev, Gemini Flash, and Claude Fable on Python code review rules: cost, speed, accuracy, and consistency. Includes results, charts, and reproducible experiments.
import { choice, noul, TypeSafeClient } from "@typesafe-ai/sdk";Voice-driven semantic auto-advance for Slidev, powered by Cloudflare Agents and TypeSafe AI Jev
assert.equal(captured.model, '~typesafe/jev-latest');
Self-hosted AI email classifier for Gmail powered by Jev. Create custom labels, organize your inbox, and filter spam with confidence and cost controls.
TYPESAFE_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
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.
// api.typesafe.ai allows no localhost CORS origins (and keys belong server-side).
A show-and-tell capability study for Jev, TypeSafe's System One decision model.
try{const response=await fetch('https://api.typesafe.ai/v1/systemone',{method:'POST',signal:controller.signal,headers:{'content-type':'application/json','authorA browser-native Doom agent experiment with structured spatial state, composable AI controls, live decision telemetry, and a Chocolate Doom WebAssembly runtime.
const response = await fetch('https://api.typesafe.ai/v1/systemone', {Helping JEV speak <3
const API_URL: &str = "https://api.typesafe.ai/v1/systemone";
Fast semantic code search powered by Jev. Find the relevant files, line ranges, and snippets
"--provider", choices=["jev", "haiku", "anthropic"], required=True
Experimental Jev permission gate for Claude Code via OpenRouter, with reproducible latency and cost benchmarks
import { choice, noul, score, TypeSafeClient } from "@typesafe-ai/sdk";DiffJury — TypeSafe Jev PR risk router + code review coach
import { score, TypeSafeClient } from "@typesafe-ai/sdk";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.
const response=await fetch('https://api.typesafe.ai/v1/systemone',{method:'POST',headers:{Authorization:`Bearer ${c.JEV_API_KEY}`,'Content-Type':'application/jsA small programming language for LLM workflows, powered by Jev.
return (env.get("TYPESAFE_BASE_URL") or "https://api.typesafe.ai").rstrip("/")if you're experimenting with jev it will be easier from here
import { choice, TypeSafeClient } from '@typesafe-ai/sdk';English Português (Brasil)
--endpoint URL default https://api.typesafe.ai/v1/systemone
Ask Jev typed questions from the shell: noul, choice, and score answers as numbers, not prose
"jev": jev[k], "llm": llm[k], "label": None}
Does a TypeSafe Jev rerank beat embedding search? Graded relevance eval (9,831 pairs, 164 zh/en queries) over the Agent Skills Hub catalog, with the judge-circularity bias measured.
process.env.TYPESAFE_BASE_URL ?? "https://api.typesafe.ai",
Browser automation with Jev (TypeSafe) as decision model
for u in "https://docs.typesafe.ai/llms.txt" "https://evals.typesafe.ai/" "https://openrouter.ai/typesafe/jev-1.13"; do
Agent skill: design judgment-assisted systems with TypeSafe Jev (System One). Maps Choice/Score/Noul onto decision theory, reranking, and routing. Composition algebra, question design, validation gates. MIT.
Thin httpx wrapper around POST https://api.typesafe.ai/v1/systemone.
TypeSafe Jev (System One) decision tools for Hermes Agent: jev_check / jev_route / jev_score / jev_evaluate
endpoint: "https://api.typesafe.ai/v1/systemone".to_string(),
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).
import type { Questions } from "@typesafe-ai/sdk";Decision harness for TypeSafe Jev — confidence gates, shadow mode, recipes, and evals. Claude CLI 48.9s → Jev 1.3s on the same row-filter job.
reply = requests.post("https://api.typesafe.ai/v1/systemone", json=request,Jev plays Generation 3 Pokémon via Showdown and a real FireRed ROM.
const res = await fetch("https://api.typesafe.ai/v1/systemone", {22 Jev models, one ball: a 3D football match where every player is its own Jev (TypeSafe AI System One) decision. Watch, or take over the number 9.
const baseUrl = options?.baseUrl ?? process.env.TYPESAFE_API_BASE ?? "https://api.typesafe.ai/v1";
Local-first test selector using Jev judgments to determine which tests are affected by a code change
DefaultBaseURL = "https://api.typesafe.ai"
Go client for TypeSafe's System One API and its model Jev: typed judgments and calibrated probabilities instead of generated text
self.send(Method::POST, "/v1/systemone", Some(body), options, |raw| {Independent async and blocking Rust SDK for the TypeSafe AI System One API
from typesafe_sdk import Choice, TypeSafeClient
Aside agents decide with TypeSafe Jev (System One: Choice/Score/Noul). Not a Cua binding — Jev is the model, Aside is the browser runtime.
else env("TYPESAFE_ENDPOINT") or "https://api.typesafe.ai/v1/systemone"Jev-powered relevance filtering and reranking for RAG in Python.
This is a thin pass-through for ``POST /v1/systemone``. The request body
Agent Skill: send closed coding-agent judgments to TypeSafe Jev
public static let defaultBaseURL = URL(string: "https://api.typesafe.ai")!
Swift SDK for TypeSafe AI
* rooted at `https://api.typesafe.ai` and authed with the bearer token.
A Scala 3 / ZIO library for TypeSafe AI's
import { choice, score, TypeSafeClient } from "@typesafe-ai/sdk";A small local demo where a Mermaid flowchart contains the route rules, Jev supplies typed judgments, and JavaScript follows the matching branches.
A curated projects built with Jev, TypeSafe's System One model.
(Text::new("JEV"), TextFont { font_size: FontSize::Px(16.0), ..default() }, TextColor(ACCENT)),Midi Jambox with Jev
TYPESAFE = os.environ.get("TYPESAFE_BASE_URL", "https://api.typesafe.ai").rstrip("/")Can we run something like Jev on a 3090 at home?
const ENDPOINT = process.env.TYPESAFE_ENDPOINT ?? 'https://api.typesafe.ai/v1/systemone'
Jev cannot generate a single note. Given a piano and the right questions, it improvises anyway.
export const SYSTEM_ONE_URL = 'https://api.typesafe.ai/v1/systemone';
Codex plugin: verbatim Jev-guided context restoration around session compaction. Port of tamaratran/fast-jev-compaction to Codex lifecycle hooks.
import type { Fetch, Questions, SystemOneResult } from "@typesafe-ai/sdk";Semantic schemas over TypeSafe's Jev — validate the state locally, then project typed answers.
from typesafe_sdk import Choice, Noul, RetryPolicy, TypeSafeClient
Playing Pokemon Red using TypeSafe Jev
import { TypeSafeClient } from "@typesafe-ai/sdk"k8s awareness with jev
from .schema import Choice, Noul, Question, Score, question_from_dict
An optimized inference engine to turn LLMs into Jev-like machines: optimized for quick, lightweight, and accurate decision-making, classification, and scoring
# "JEV" is also Japanese encephalitis virus, and "typesafe" is a common word.
A curated list of projects, integrations, and resources for Jev, TypeSafe AI's System One model.
DEFAULT_API_URL = "https://api.typesafe.ai/v1/systemone"
Community TypeSafe AI playground: 110 use cases, games, dilemmas and model challenges, with editable prompts, A/B comparisons and a mobile-friendly UI.
@default_base_url "https://api.typesafe.ai"
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.
from typesafe_sdk import AsyncTypeSafeClient, Choice, RetryPolicy
TypeSafe's Jev model plays Vampire Survivors on Steam: BepInEx plugin + Python brain + live decision dashboard. Native Linux only.
: (vercelGateway ? GatewayProtocol.DEFAULT_BASE_URL : "https://api.typesafe.ai");
Idiomatic Java SDK for TypeSafe AI Jev System One decision engine
} else if r.URL.Host != "api.typesafe.ai" {macOS computer use driven by Jev (TypeSafe System One) as the decision maker
TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone"
Open-source LLM router that uses TypeSafe's Jev to pick a model, on top of LiteLLM
export const JEV_URL = process.env.CANNY_JEV_URL ?? "https://api.typesafe.ai/v1/systemone";
Stops AI coding agents from claiming work is done without evidence. Deterministic hooks decide, TypeSafe's Jev advises. Append-only ledger, zero runtime dependencies.
return { kind: "connection", message, retryable: true, hint: "Check network access to api.typesafe.ai." };MCP server exposing TypeSafe Jev as typed, calibrated judgment tools: classify, score, check, batched ask. Ships as a Claude Code plugin.
import type { ChoiceResponse, EntryType, NoulResponse, Question, Usage } from "@typesafe-ai/sdk";Semantic test matchers for Vitest and Jest, powered by TypeSafe's Jev model. Write expectations in plain English, get calibrated probabilities back.
const API_URL: &str = "https://api.typesafe.ai/v1/systemone";
Reimagined window switcher for macOS using frontier artificial intelligence. Predicted by TypeSafe's Jev model
req=urllib.request.Request('https://api.typesafe.ai/v1/systemone',data=body,headers={'Authorization':'Bearer '+key,'Content-Type':'application/json','Cache-ContIndependent Jev 1.13.0 behavior study: report, controlled prompt experiments, raw results, and offline verification.
"app": "jev",
Turning an LLM model into a Jev like System.
Explore real-world use cases and projects built with TypeSafe AI's Jev: content moderation, AI agents, model routing, and semantic search. Curated by SeeAPI.
help = "API root [default: https://api.typesafe.ai]"
Interact with "Jev" model from TypeSafe AI
'description' => __( 'TypeSafe API base URL (default https://api.typesafe.ai/v1).', 'ai-provider-for-jev' ),
Connect WordPress to TypeSafe's Jev System One model for structured decisions (choice, score, noul).
defaultBaseURL = "https://api.typesafe.ai"
Community Go SDK for TypeSafe AI Jev / System One
API_URL = "https://api.typesafe.ai/v1/systemone"
Ask a yes/no question of every function in a codebase. Ranked answers in seconds, for cents. Grep whose pattern is a question, powered by TypeSafe Jev.
endpoint = "https://api.typesafe.ai/v1/systemone"
Zero-shot English goals on a sim Franka. Jev chains hardcoded primitives.
const val DEFAULT_BASE_URL: String = "https://api.typesafe.ai"
JevNoiseGate filters unwanted notifications and SMS on Android. Rather than matching keywords, an LLM decides what's noise — and only what it explicitly flags is blocked. Verification codes are matched on-device and never uploaded; anything uncertain passes through.
baseUrl = "https://api.typesafe.ai",
YouTube sponsor skipper that reads the captions and decides at watch time: a probability heatmap on the seek bar, no crowd database
export const MODEL = 'typesafe/jev-1.13';
Chess, Connect Four, and a decision model. Play Jev or watch Jev play itself.
Things built with Jev (TypeSafe), plus patterns, documented limits, and unbuilt ideas
"""OpenRouter Decisions API transport for Jev (not TypeSafe /v1/systemone)."""
LlamaIndex reranker + router powered by TypeSafe Jev — typed scores/choices, cheaper than LLM-as-judge.
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
使用 TypeSafe Jev 审查 Skill 与 MCP 可疑行为 | Review Agent Skills and MCP code with Jev, static evidence, and explicit coverage gaps
if self.path != "/v1/system_one":
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.
import { choice, noul, score, TypeSafeClient } from "@typesafe-ai/sdk";TypeSafe AI'ın karar modeli Jev ile basit, tip güvenli bir örnek. Aynı görevi Claude Opus 5 ile yapan bir karşılaştırma scripti de içerir.
"model": "typesafe/jev-1.13",
SLO-aware LLM inference router with Jev decisions, live queue metrics, counterfactual evaluation, and reproducible latency/cost benchmarks
from typesafe_sdk import AsyncTypeSafeClient
TypeSafe Jev demonstration for new analyzation — experimenting with Jev for fast analysis of news and tickers
// request example for POST /v1/systemone (api.md:153), and its example
A Go client for the TypeSafe System One API — typed judgments and probabilities, zero dependencies outside the standard library.
process.env.TYPESAFE_ENDPOINT ?? "https://api.typesafe.ai/v1/systemone";
Reward-hack radar for coding agents: structural denies + TypeSafe Jev System One sidecar for Claude Code & Cursor hooks
from typesafe_sdk import Choice, Noul, TypeSafeClient
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.
Wild things people are building with TypeSafe AI's Jev
A curated list of awesome Jev / TypeSafe System One applications, libraries, and resources - curated by APA (AIPersona Academy)
"""System One / "Jev"-style scorer.
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.
import { noul, TypeSafeClient, type NoulResponse } from "@typesafe-ai/sdk";Plugin for oh-my-pi that uses Typesafe Jev API to classify tool calls as safe/unsafe/ask
self.url = "https://api.typesafe.ai/v1/systemone"
⚡ DOOM-JEV: Autonomous ViZDoom Agent
import { choice, noul, TypeSafeClient } from '@typesafe-ai/sdk';An autonomous agent that plays Clash Royale on macOS through the native
} from "@typesafe-ai/sdk";
A CLI that checks natural-language engineering rules against the current Git
"typesafe": "https://api.typesafe.ai/v1/systemone",
A typed Python framework for controlling Android over ADB with Jev.
endpoint: "https://api.typesafe.ai/v1/systemone",
Fast Rust CLI for TypeSafe Jev: typed decisions, offline linting before you pay
* TypeSafe's native API — POST https://api.typesafe.ai/v1/systemone, key
Fast, cheap judgment for AI coding agents: semantic search, focused reads and list picking in ~2s. CLI + MCP server on TypeSafe Jev. Benchmarked on SWE-bench.
API_URL = "https://api.typesafe.ai/v1/systemone"
A chatbot built on a model that cannot generate text (TypeSafe AI's Jev, driven autoregressively)
_TOOLSET = "jev"
Jev Decisions Plugin for Hermes (and other AI Agents): tool risk reviews, human approval recommendations, evidence checks, and a local decision journal.
API_HOST = "api.typesafe.ai"
Pure Jev that can "type" and drive towards task completion.
'base_url' => env('TYPESAFE_BASE_URL', 'https://api.typesafe.ai'),Unofficial Laravel integration for TypeSafe Jev AI with typed responses, async requests, scoped dependency injection, and testing fakes.
import { experimental_evaluate as evaluate } from 'ai';Semantic MCP firewall powered by Jev — screens every tool call, tool result, and tool description with calibrated System One verification. 94% block recall, 0 false positives, ~$0.00002/check.
DefaultBaseURL = "https://api.typesafe.ai/v1/systemone"
High-speed, cross-agent safety gate plugin for Claude Code, Codex CLI, and Antigravity.
export const DEFAULT_ENDPOINT = 'https://api.typesafe.ai/v1/systemone';
Unofficial TypeSafe Jev showcase — System One decisions, not chat.
API = "https://api.typesafe.ai/v1/systemone"
TypeSafe's Jev is a decision model: it takes state and typed questions and returns calibrated
/// Sends `state` and `questions` to `POST /v1/systemone` with client defaults. Returns decoded answers.
Rust SDK for the TypeSafe AI API
DefaultBaseURL = "https://api.typesafe.ai"
unofficial go SDK for typesafe AI, with typed answers, retries, and context support
export const API_URL = "https://api.typesafe.ai/v1/systemone";
A browser form for building requests to TypeSafe's Jev: pick a template, fill in the blanks, copy the request. No JSON, no install, runs locally.
import type { EntryType, NoulQuestion as SdkNoulQuestion, Usage } from '@typesafe-ai/sdk';Claude Code plugin that scores how well you prompt a coding agent, and shows whether your habits are improving. Runs on TypeSafe's Jev model. Zero added latency.
DEFAULT_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
I kept watching coding agents burn context on decisions that aren't hard - triage 400 tickets, tag 600 files, route to one of six teams. jev-mode moves those verdicts to a typed-judgment model. I A/B'd it: 78% fewer tokens, 16x less work-attributable input, accuracy 96.1% vs 93.7%. Python, no deps, MIT.
import { choice, noul } from '@typesafe-ai/sdk';FUn little experiment with Typesafe AI Jev Model playing chess against stockfish :)
* Typed question specs in the wire shape of `POST /v1/systemone` (PLAN.md §2.2).
Play Slay the Spire 2 with Jev (TypeSafe System One).
from typesafe_sdk import TypeSafeError
Make room for useful evidence. Inspectable context selection for RAG, with Jev reranking and open benchmark studies.
API_URL = "https://api.typesafe.ai/v1/systemone"
TypeSafe'in Jev karar modeli gerçek bir online 2048 sitesinde oynuyor — hamle başına tek API çağrısı, tek anahtar.
return {"url": "https://api.typesafe.ai/v1/systemone", "key": os.getenv("TYPESAFE_API_KEY", ""), "model": os.getenv("TYPESAFE_MODEL", "jev-latest")}EmbodiedJev: MuJoCo robot decision workbench with MiniCPM5-2B, Jev and compatible model APIs
// POST /v1/systemone {model, state, questions} -> {model, answers, usage}TypeSafe AI System One (Jev) task plugin for QuantumNous/new-api — native /v1/systemone, synchronous evaluation, token billing
DefaultBaseURL = "https://api.typesafe.ai"
Go client for TypeSafe AI's System One API (Jev), with optional Langfuse instrumentation
typesafe: { name: 'TypeSafe', url: 'https://api.typesafe.ai/v1/systemone', model: 'jev-1.13.0' },A teleprompter of talking points that checks each one off as you cover it, using TypeSafe's Jev Score questions
URL = "https://api.typesafe.ai/v1/systemone"
Text generation with jev: one typed question per word
POST https://api.typesafe.ai/v1/systemone
Eight minimal working examples of TypeSafe's Jev (a System One model) applied to mechanical and electrical engineering: CAD/CAE/CAM routing, FEM result triage, DFM screening, BOM alignment, hallucination-proof extraction. Zero dependencies.
// Probability is the Noul answer: how likely Jev thinks the positive is.
Blind security benchmarks for Jev, TypeSafe's System One model: prompt injection and vulnerable code detection, built on jev-go
"jev" => { input_per_mtok: 0.042, output_per_mtok: 0.0 },Community Rails integration for TypeSafe AI's System One API, built on the
request = Request('https://api.typesafe.ai/v1/systemone',Copy and paste this into your coding agent:
TYPESAFE_BASE_URL Jev API root (default https://api.typesafe.ai)
Effect-based safety gate for AI coding agents' shell commands (OpenCode, Antigravity): fast structural rules, then TypeSafe's Jev or a chat model judges what a command does. Certified with Jev at zero dangerous commands allowed.
`Request is what the app POSTs to https://api.typesafe.ai/v1/systemone\n` +
Screen a folder of CVs with the TypeSafe Jev decision model: typed judgments, an editable policy, free re-scoring.
/** TypeSafe's public /v1/systemone API. Thread safe; reuse a client across requests. */
Unofficial Java SDK for TypeSafe Jev and Vercel AI Gateway, with Spring Boot and WebClient support
export { choice, noul, score } from "@typesafe-ai/sdk";Typed, policy-driven decision workflows on top of TypeSafe AI Jev: confidence routing, fallbacks, evaluation, and RAG patterns for TypeScript apps.
_systemOneUri = _pipeline.Resolve("/v1/systemone");.NET SDK for the TypeSafe AI platform
TypeSafeClient,
Select Git changes for staging with a plain-language description.
//! `serde` shapes for `POST /v1/systemone` — no HTTP calls yet.
Jev-routed client for NEAR AI Cloud inference and IronClaw agents.
/** Defaults to `~typesafe/jev-latest`. */
Fork of tamaratran/fast-jev-compaction: Jev via OpenRouter with zero data retention (zdr, data_collection: deny)
typesafe:Object.freeze({id:'typesafe',label:'TypeSafe',endpoint:'https://api.typesafe.ai/v1/systemone',modelsEndpoint:'https://api.typesafe.ai/v1/models',envKeyAI life-and-civilization simulation: TypeSafe Jev makes every decision (typed, probabilistic, auditable); LLMs plan — OpenAI-compatible APIs, local models (Ollama, LM Studio), Claude Code, Codex.
const API_URL = "https://api.typesafe.ai/v1/systemone";
A Chrome extension that covers distracting YouTube videos with Jev. Show anyway whenever you want.
import { choice, TypeSafeClient } from '@typesafe-ai/sdk';100 AI NPCs live in a tiny town. Jev chooses the next action; the world writes the story.
from typesafe_sdk import Choice, Noul, Question, Score
A thin shim between Pydantic and Jev.
from typesafe_sdk import AsyncTypeSafeClient, Choice
Backtest Jev (TypeSafe) as a BUY/SELL/HOLD trader on NQ L10 order-book data
assert cfg.name == "typesafe" and cfg.base_url.startswith("https://api.typesafe.ai"), cfgAwesome Collection of apps built with Jev - a System One model
export const SYSTEM_ONE_URL = "https://api.typesafe.ai/v1/systemone";
Fast JEV compaction extension for pi
const TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone";
A small Jev-powered bridge to Chrome through the Chrome DevTools Protocol.
const ENDPOINT = "https://api.typesafe.ai/v1/systemone";
Reversible context pruning for Pi, powered by TypeSafe Jev. Keep useful context without deleting session history.
pub const DEFAULT_API_URL: &str = "https://api.typesafe.ai";
Rust-aware code review for Claude Code and coding agents, powered by TypeSafe Jev
import { APIError, AuthenticationError, TypeSafeClient, choice, noul, score } from "@typesafe-ai/sdk";Audit your git diff against YAML coding-standards packs using TypeSafe's Jev model, from a CLI or your AI agent's command/skill.
'typesafe': ('https://api.typesafe.ai/v1/systemone', 'jev-1.13.0')}Experimental semantic line search with TypeSafe Jev via OpenRouter. Python CLI with no runtime dependencies.
API_HOST = "api.typesafe.ai"
A maleCNS fly-brain connectome fights a language model in mk.js — spiking simulation, dopamine learning, and the controls that say what each side contributes
"adaptation": "Native Noul replaced with binary Yes/No Choice; state/question unchanged",
Run SemIf (Jev-style semantic-if decisions) on a CPU — no GPU. Reads typed option probabilities straight from an open model in one forward pass, plus a web UI.
from typesafe_sdk import Choice, Noul, Score, TypeSafeClient, TypeSafeAPIError
Discriminative Monte Carlo Tree Search using TypeSafe Jev System One Primitives and Gemini
from typesafe_sdk import Choice, Noul
Tell Claude Code which installed skill a session needs, using Jev (TypeSafe AI) for the decision and skills.sh for discovery.
SYSTEM_ONE_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
⚡ Ultra-fast, low-cost intelligent task classifier and 3-tier routing engine powered by TypeSafe Jev (System One)
// a same-origin path that the host forwards untouched to api.typesafe.ai — a
Check whether each cited paper supports the sentence citing it. Claude proves the quote, TypeSafe's Jev scores it, a human decides.
TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone"
MCP server: screen PubMed titles/abstracts against a query or clinical question with TypeSafe Jev
#define JEV_DEFAULT_URL "https://api.typesafe.ai/v1/systemone"
SQLite extension that calls TypeSafe Jev (or tensai serve) from SQL
const ORIGIN = "https://api.typesafe.ai";
Codex 可恢复委派:Capsule → Jev 选路 → Policy Guard(仅 ALLOW/DENY)→ Root 验收。自动委派默认关闭。Recoverable Codex delegation via Jev + Policy Guard; Root keeps acceptance.
export const JEV_ENDPOINT = 'https://api.typesafe.ai/v1/systemone';
Not every coding task needs your best model. Experimental Jev-powered model routing for Claude Code — V3 prototype runs today, V4 routes at the task boundary.
with patch('jevseek.models.OpenAI') as ds, patch('jevseek.models.TypeSafeClient') as jev:A local coding workspace pairing Jev action routing with DeepSeek argument generation. Native tools, persistent sessions, React desktop, and documented research.
transport: 'typesafe', endpoint: 'https://api.typesafe.ai/v1/systemone',
Browser automation CLI for AI agents, powered by the Jev model's millisecond decisions and near-zero inference costs
// except in the Authorization header of a request to api.typesafe.ai.
Chrome extension that triages Gmail with TypeSafe's Jev model: category, priority, spam % and reply % on every email.
public const DEFAULT_BASE_URL = 'https://api.typesafe.ai/v1';
PHP SDK for TypeSafe's Jev: send text and typed questions, get typed answers with calibrated confidence. PHP 8.1+, works with any PSR-18 client, Laravel 8–13.
Calls the real ``https://api.typesafe.ai/v1/systemone`` endpoint. The
Evidence-driven frontend QA built on Jev Ultrafast and Browser Harness, with a synthetic todo demo.
import { choice, noul, type Questions, type SystemOneRequest, type SystemOneResult } from "@typesafe-ai/sdk";A step-through logic interpreter for natural-language facts and rules, unified with Jev
import { experimental_evaluate as evaluate } from 'ai';Jev-backed tool approval gate and tool-list pruning for the Vercel AI SDK
const TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone";
Cache-neutral context trimming for the pi coding agent, powered by TypeSafe Jev: long tool output cut to verbatim key lines before it enters context, with lossless recall. Measured, with pre-registered benchmarks.
d, wall, srv = post("api.typesafe.ai", "/v1/systemone", os.environ["TYPESAFE_API_KEY"], {"model": "jev-1.13.0", "state": state, "questions": questions})An independent benchmark of TypeSafe's Jev, a model that does not write text. You send it some content and a list of typed questions (yes/no, pick one option, rate on a scale) and
import { choice, TypeSafeClient } from "@typesafeai/sdk";Automated database migration safety reviewer powered by TypeSafe AI (Jev System One model)
A curated list of what people built with Jev
jev_model: str = "jev-latest"
Route among multiple LLMs and multi-model provider keys without leaking secrets.
use jev_sdk::{Choice, Noul, NoulCriteria, Question, Score, TypeSafeClient};An agent-facing command line for Jev,
public static final String DEFAULT_BASE_URL = "https://api.typesafe.ai";
Community Java client for the TypeSafe System One API (unofficial)
baseUrl: "https://api.typesafe.ai/v1/systemone",
Verbatim context pruning for the pi coding agent, scored by TypeSafe Jev: stale tool calls and results are dropped or truncated, everything kept stays verbatim.
DEFAULT_BASE_URL = "https://api.typesafe.ai"
A VGI worker exposing TypeSafe System One questions (choice, noul, score) to DuckDB/SQL as LATERAL-joinable table functions
import { choice, type EntryType, TypeSafeClient } from "@typesafe-ai/sdk";JevArena — two Jev agents duel in click-only browser games (Browser Use + TypeSafe Jev)
import { experimental_evaluate as evaluate } from 'ai';Recursive Jev choice over a taxonomy. Select from more than 255 options without breaking TypeSafe Jev's choice cap.
SystemOneResult,
Run Laya, the open-source Jev-compatible System-1 decision model, from Node.js / TypeScript via ONNX Runtime
API_URL = "https://api.typesafe.ai/v1/systemone"
Fast CVSS scoring from vulnerability descriptions using Typesafe Jev
Real mode: uses the official ``typesafe_sdk`` (``pip install jev-triage[jev]``),
Triage for deep-research agents. Score N search results in one parallel TypeSafe Jev call, so the frontier model only reads what is worth reading.
export const JEV_MODEL = '~typesafe/jev-latest'
星露谷农场小助手:Jev 自主游玩、dsh 插件、独立 CLI 与 SMAPI Mod
endpoint: options.endpoint ?? "https://api.typesafe.ai/v1/systemone",
Typed, confidence-aware AI decisions for TypeScript and Python with Jev, OpenRouter, safe fallbacks, and per-call cost tracking.
System-architecture skill for TypeSafe AI Jev/System One — find fuzzy semantic judgment and turn it into small Choice/Score/Noul primitives.
api.typesafe.ai; the CLI, the verifier and the lab harness all go through it.
Jev (TypeSafe) exploratory thread: claim audit, live demos, and runnable code
import { experimental_evaluate as evaluate } from 'ai';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.
/// TypeSafe Jev (`POST /v1/systemone`). Only transcript text and group
Private Mac voice diary: local Parakeet transcription, Jev sorting, Notion library
export const DEFAULT_BASE_URL = "https://api.typesafe.ai";
A Jev based context curator for pi
baseUrl: "https://api.typesafe.ai/v1",
Cut Claude Code's skill manifest by ~75% with TypeSafe Jev. Scores every installed skill for relevance and hides the rest via skillOverrides — 12,750 → 3,185 tokens on a 217-skill install, for $0.0009 a session.
DEFAULT_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Catch breaking API behavior hidden in OpenAPI prose with deterministic checks and TypeSafe JEV System One semantic review.
DEFAULT_MODEL = 'jev-latest'
Asks Jev whether a Redmine issue's tracker fits, while you fill in the form
from typesafe_sdk import Choice, Noul, NoulCriteria
atlas-jev is a local memory store. You give it text. An OpenRouter chat model extracts memories worth keeping, and those memories are stored on disk in LanceDB. You can search them
const response = await fetch('https://api.typesafe.ai/v1/systemone', {method:'POST', headers:{Authorization:`Bearer ${s.apiKey}`, 'Content-Type':'application/jsA live tone labeler for Bluesky posts and drafts, using TypeSafe's Jev API.
const curlCmd = `curl -i -X POST https://api.typesafe.ai/v1/systemone \\
Autonomous System-One Triage Engine & Benchmark powered by TypeSafe AI (Jev). 75ms inference, $0 output tokens, and RLCD epistemic safety gates.
// 1. TYPESAFE_API_KEY -> POST https://api.typesafe.ai/v1/systemone (first party)
Bev: the slowest classifier in the world, at Jev prices. npx bev-ai
from typesafe_sdk import Choice, Noul, RetryPolicy, Score, TypeSafeClient
Routes human review attention: green/yellow/red for a diff and who should look. It doesn't review the code. Built on TypeSafe.
export const SYSTEM_ONE_URL = "https://api.typesafe.ai/v1/systemone";
Fast compaction for Pi: Jev-scored verbatim eviction of stale tool history, with LLM summarisation of the evicted transcript as the fallback.
* POST https://api.typesafe.ai/v1/systemone
Multi-axis writing quality checker powered by TypeSafe AI's Jev model. Separate named checks, each with its own verdict and confidence.
{ value: "jev-latest", label: "jev-latest" },shadcn-style reusable components and blocks for using TypeSafe AI.
DEFAULT_BASE_URL = "https://api.typesafe.ai"
Pokemon Red on PyBoy: code owns the route and the arithmetic, Jev picks at branches in about 100 ms, calibration measured instead of assumed
const up = await fetch(upstream.replace(/\/+$/, "") + "/v1/systemone", {Neovim: ask the buffer a question, get a quickfix list. Treesitter splits functions, Jev scores each one, probabilities land as virtual text
API = "https://api.typesafe.ai/v1/systemone"
Claude Code Stop hook that checks an AI assistant's claims against what it actually read this session, using TypeSafe's Jev as the judge
const TYPESAFE_API_URL = 'https://api.typesafe.ai/v1/systemone';
Privacy-first Chrome extension that semantically blocks native ads, sponsored feed cards, and video ads using TypeSafe Jev
import { choice, TypeSafeClient, type JsonValue } from "@typesafe-ai/sdk";Experimental multi-horizon BTC signal generator using TypeSafe Jev probabilities and Binance market data.
from typesafe_sdk import Choice, Noul, Score
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
const API_ENDPOINT = process.env.TYPESAFE_ENDPOINT || "https://api.typesafe.ai/v1/systemone";
Universal Model Context Protocol (MCP) Server for TypeSafe Jev (System One) semantic code search and validation.
.parse(models.data.find((item) => item.id === "typesafe-ai/jev"));
Lint JavaScript and TypeScript against plain-English project conventions with Jev.
MODEL = "~typesafe/jev-latest"
Cross-domain check on MIND news: a zero-shot Jev headline prior is worth ~500 labelled articles, adds +0.069 ρ as features, and lifts a Thompson-sampling cold start by 25%.
export const SYSTEM_ONE_URL = "https://api.typesafe.ai/v1/systemone";
Verbatim context compaction for pi, powered by the TypeSafe Jev model.
server = mcp.get("mcpServers", {}).get("jev", {})Codex Plugin with typed Jev judgments for risk review, evidence checks, context screening, and reranking.
JEV_URL = "https://api.typesafe.ai/v1/systemone"
Benchmark TypeSafe Jev against any OpenRouter model on your own labelled classification data: accuracy, calibration, latency, cost
JEV_URL = "https://api.typesafe.ai/v1/systemone"
TypeSafe Jev plays Super Mario Bros from a text description of emulator RAM
import { choice, score } from "@typesafe-ai/sdk";Keeps OpenCode on a cheap sticky model for warm cache; Jev escalates hard turns to stronger subagents.
pub const DEFAULT_BASE_URL: &str = "https://api.typesafe.ai";
Async-first Rust SDK for the TypeSafe AI API
DEFAULT_BASE_URL: Final = "https://api.typesafe.ai"
Async Python client for TypeSafe Jev. Typed questions in, probabilities and choices out, no prose to parse.
import { experimental_evaluate as evaluate } from 'ai';A Magic Jev (8) Ball for pull requests.
host_permissions: ["https://api.typesafe.ai/*"],
Organize bookmarks with your own semantic rules using Jev.
// Minimal client for POST /v1/systemone. Works in the extension worker and in Node.
Chrome extension that hides AI-generated posts on X and LinkedIn. Scored by TypeSafe Jev. Reddit and YouTube next.
// POST https://api.typesafe.ai/v1/systemone
Map a codebase into units and let Jev (TypeSafe AI) hand an AI coding agent the ten files that matter for a task
Requires TYPESAFE_API_KEY and: pip install typesafe-sdk
Fake autoregressive language model powered by TypeSafe Jev
USING (VALUES ('API_URL', 'https://api.typesafe.ai/v1/systemone'),Ask your Db2 for i tables questions. A Db2 for i SQL SDK powered by TypeSafe's Jev.
let resp = ureq::post("https://api.typesafe.ai/v1/systemone")Sub-second Git pre-commit & pre-push semantic reflex gate powered by TypeSafe AI Jev
let response = match ureq::post("https://api.typesafe.ai/v1/systemone")Zero-hallucination open-source repo and crate scout powered by TypeSafe AI Jev System One scoring
assert!(sent.starts_with("POST /v1/systemone HTTP/1.1"), "{sent}");AI defect code suggestions for Non-Conformance Reports, powered by TypeSafe AI's Jev model
#[arg(long, default_value = "https://api.typesafe.ai/v1/systemone")]
Structured code review for GitHub and Gitea Actions, powered by TypeSafe Jev and written in Rust.
from typesafe_sdk import SystemOneResponse
Lints AI-generated code for slop using Jev, a System One model that makes fast structured decisions instead of generating text.
* Falls back to `POST {baseURL}/v1/systemone` with the same wire questionsDrop-in decision/routing layer powered by TypeSafe Jev (System One) — typed Choice/Noul/Score routes with production safety gates.
MODEL = "typesafe/jev-1.13"
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
const BASE_URL = "https://api.typesafe.ai";
Test bench for TypeSafe's Jev
DefaultBaseURL = "https://api.typesafe.ai"
Unofficial Go client for TypeSafe's System One API and its model, Jev.
typesafe = env("TYPESAFE_BASE_URL", "https://api.typesafe.ai").rstrip("/")Jev (TypeSafe) vs Claude Haiku 4.5 on 2 000 phishing emails: accuracy, calibration, latency, cost. Reproducible benchmark.
/// Blocking `POST /v1/systemone`.
Rust client for the TypeSafe AI System One API: send a state plus named,
import { TypeSafeClient, TypeSafeDecisionModel } from "@effect/ai-typesafe";Route-declared SEO graph and audit toolkit for TanStack Start: sitemap/robots, React head, JSON-LD, Vite coverage gate, live audit, and Jev-backed link decisions.
from typesafe_sdk import Choice, TypeSafeClient
Runnable demos of TypeSafe's System One model (Jev) — parallel Noul judgments and a Choice-based citation/claim checker
const res = await fetch("https://api.typesafe.ai/v1/systemone", {Chrome MV3 extension: one-click tab grouping with two engines — fixed rules (Jev/TypeSafe System One) or any OpenAI-compatible LLM that invents its own group names. Includes built-in API error log viewer.
ENDPOINT = 'https://api.typesafe.ai/v1/systemone'
Working Memory Jev · Passage
result = post_json("https://api.typesafe.ai/v1/systemone", os.environ["TYPESAFE_API_KEY"], body)⚡ Ultrafast browser agent with dynamic, indexed action spaces. Zurich → London on Google Flights in 7.1s.
export const DEFAULT_BASE_URL = "https://api.typesafe.ai/v1/systemone";
Per-prompt capability router for coding agents: resolves installed skills, MCP servers, agents and commands against your prompt via TypeSafe Jev, and measures whether the injection actually helps.
'/v1/systemone',
PHP & Laravel SDK for TypeSafe AI's JEV Model series
MODEL = "typesafe/jev-1.13"
A safety boundary for AI-assisted Home Assistant decisions, with explicit policy checks and deterministic state verification.
TYPESAFE_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Browser use for coding agents, 3-5x faster than browser-use. MCP server + CLI; TypeSafe Jev decides every step in ~300 ms.
Endpoint: POST https://openrouter.ai/api/alpha/decisions (model ~typesafe/jev-latest).
Jev notes: fourteen decisions I ran through it
"url": "https://api.typesafe.ai/v1/systemone",
这是在本机运行的 API 客户端,推理由云端 Jev 执行,不需要显卡。Jev 适合分类、判断和评分,返回选项、概率及分数;它不生成聊天回复或代码。
model: str = "~typesafe/jev-latest",
Directory Search with OpenRouter Decisions
const { TypeSafeClient, choice, noul, score } = await import("@typesafe-ai/sdk");Adaptive multi-model AI orchestration runtime using Jev for cost-aware routing, confidence-based escalation, tool selection, and model execution
@url = "https://api.typesafe.ai/v1/systemone"
Probabilistic control flow for Ruby — chance, pick, and rate, powered by TypeSafe's Jev
API = "https://api.typesafe.ai/v1/systemone"
Скилл для агентов Letta: суждения по критериям через TypeSafe System One (Jev)
jevModel: process.env.JEV_MODEL ?? "typesafe/jev-1.13",
Semantic firewall for LLM agents: tool calls gated by TypeSafe Jev (System One decision model via OpenRouter) + deterministic policy. PoC with corpus, stability eval, baseline, results.
url: `${process.env.OXLINT_JEV_BASE_URL ?? DEFAULT_BASE_URL}/v1/systemone`,Digest your skills into oxlint rules powered by jev
import { noul } from "@typesafe-ai/sdk";Uses typeful jev, zero sync to pull and sync large repositories for issue triage
URL = "https://api.typesafe.ai/v1/systemone"
@typesafeai 's Jev controls the 2 hands and each finger to play the piano in real-time. Jev only "sees" what we see and plays this from the "note waterfall". It uses @browser_use 's jev-ultrafast and some decision scheduling to make this happen in real-time. Sound on 🔈🔉🔊
import { experimental_evaluate as evaluate } from 'ai';Jev-filtered always-on speech input harness (mic → STT → Jev → text feed)
* POST /v1/systemone Jev at TypeSafe, which refuses requests from browser pages
Jev, TypeSafe's System One model, plays chess against any OpenRouter LLM, Stockfish and you. One-page web app with live moves, Jev's move probabilities, saved games and win rates.
baseURL: URL = URL(string: "https://api.typesafe.ai/v1/systemone")!,
Control your Mac by voice. Speech → Jev (TypeSafe AI System One model) typed decisions → macOS actions. Menu-bar Swift app.
join(or(env.TYPESAFE_BASE_URL, 'https://api.typesafe.ai'), '/v1/systemone'),
Typed decisions in Claude Code: adds $.jev over TypeSafe's Jev, through OpenRouter, Vercel AI Gateway, Cloudflare Workers AI, LiteLLM or the TypeSafe API.
import { TypeSafeClient, TypeSafeDecisionModel } from "@effect/ai-typesafe";A demonstration of the Jev System 1 model in Effect, matching vulnerabilities to their underlying CWEs
* Service worker: the only place that holds the API key and talks to api.typesafe.ai.
Chrome extension that reads every cookie banner and popup like a person and clicks the honest button. Judged by TypeSafe's Jev. BYOK, no backend.
API_URL = "https://api.typesafe.ai/v1/systemone"
NYC 311 complaint heatmaps with TypeSafe JEV: reproducible pipeline, live research results, and interactive geographic visualizations.
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Capability-aware context-pruning installer, bounded Jev assessment engine, and experimental harness request-projection adapters (experimental, not live-host tested)
"jev" => Some(Self::Jev),
Argent + Jev
import { TypeSafeClient } from "@typesafe-ai/sdk";Local evaluation workbench for TypeSafe Jev
DEFAULT_MODEL = os.environ.get("JEV_MODEL", "typesafe/jev-1.13")Jev for Hermes: cheap intent gates + verbatim tool compaction on OpenRouter
j = row.get("jev")open-Jev LM arm: Qwen2.5-0.5B + LoRA reproducing a hosted decision model's judgment at 92.9% on hand-labelled gold - trained overnight on a 6-vCPU CPU-only host, $0/call. Paper, corpora, harnesses, receipts.
export const SYSTEM_ONE_URL = 'https://api.typesafe.ai/v1/systemone';
Jev-guided verbatim supplemental compaction for Codex sessions
* SDK's `experimental_evaluate`, not the chat-completions endpoints.
What your last session knew, scored against what this one is doing. MCP server: a per-project ledger written as things happen, recalled per task with TypeSafe's Jev evaluation model via Vercel AI Gateway.
"""Native HTTP client for Experiential /v1/systemone.
A gate for your agent's expensive steps, powered by TypeSafe Jev (System One). Offline-first, OpenRouter or direct, MIT.
DefaultBaseURL = "https://api.typesafe.ai"
Go SDK for TypeSafe AI.
import type { TypeSafeClient } from '@typesafe-ai/sdk';Context compaction and safety gating for AI agents via TypeSafe Jev: keeps messages verbatim, no summarization. OpenAI, Anthropic, LangChain, CLI, MCP.
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Jevaluate: evaluate before you trust. Field notes, runnable scripts and an agent skill for TypeSafe Jev: gated evals, a browser loop, a product walk with DeepSeek vision, a UI text judge and a first-click tree test. Co-authored with Claude Fable 5.1.
const r = await fetch("https://api.typesafe.ai/v1/systemone", { method: "POST", headers: { Authorization: `Bearer ${KEY}`, "Content-Type": "application/json" },Almond-fastloop: Almond's browser computer-use rig (Chrome DevTools + TypeSafe Jev), and the Browser Use Olympics benchmark it is measured on.
from typesafe_sdk import Choice, TypeSafeClient
Turning the Jev classifier model into an autoregressive next token predictor
DEFAULT_MODEL = "~typesafe/jev-latest"
Classify C/C++ snippets via TypeSafe Jev through OpenRouter.
('HTTP API', 'Send `state`, `model`, and typed `questions` to `POST https://api.typesafe.ai/v1/systemone`. Check the current schema before integrating.', 'httpsA curated collection of TypeSafe Jev projects, examples, tutorials, and demos from GitHub, the web, X, and YouTube. Organized by use case, with concise summaries and original sources. Available in English, Chinese, Japanese, and Spanish.
"model": "jev-1.13.0 (aka jev-latest), released 2026-09-15",
📡 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
export const MODELS = { chat: 'google/gemini-3.7-flash', decision: 'typesafe/jev-1.13' } as const;A repository for jev-expirements
from typesafe_sdk import Choice, Noul, TypeSafeClient
Jev (TypeSafe System One) vs Claude Opus 5 driving a simulated robot arm in MuJoCo
typesafe: { key: "TYPESAFE_API_KEY", model: "jev-latest", endpoint: "https://api.typesafe.ai/v1/systemone" },Local tool-routing classifier for coding agents, with a gateway, MCP integrations, and decision logs.
"url": f"http://{args.host}:{args.port}/v1/systemone",Supersimple way to serve LLMs as a Jev-like endpoint
let md = `# Results\n\nGenerated by \`node eval.js\` on ${new Date().toISOString().slice(0, 10)} with \`${process.env.JEV_MODEL ?? 'typesafe/jev-1.13'}\`.\n\n`;Experiment: using TypeSafe Jev as a chatbot by choosing replies one letter or word at a time
"""FastAPI server exposing Jev-compatible POST /v1/systemone."""
Toy local System One–style decision API (Jev-shaped). Not affiliated with TypeSafe.
/// Calls <c>POST /v1/systemone</c> on the TypeSafe API over a pooled <see cref="HttpClient"/> from
A .NET 10 and React 19 application for fast, structured AI-powered ticket triage using TypeSafe Jev.
printf ' 官方直连 key(api.typesafe.ai)。留空跳过,之后可 export TYPESAFE_API_KEY。\n'
A CLI for the TypeSafe Jev System One decision model — defaulting to the TypeSafe direct API (api.typesafe.ai), with OpenRouter Decisions as a switchable alternative — plus a pi ex
if event != 'jev':
An experiment in fast, probabilistic decisions. Jev chooses actions; Python handles
const defaultModel = "typesafe/jev-1.13";
Stop burning LLM calls on classification. Route bugs, triage failures, and gate PRs in 200ms for $0.00002. OpenClaw plugin for TypeSafe Jev structured decisions.
if want := "https://api.typesafe.ai/v1/systemone"; call.URL != want {Go SDK for TypeSafe AI — classification and rating primitives over text and JSON
const DefaultBaseURL = "https://api.typesafe.ai/v1"
Unofficial Go SDK for TypeSafe AI's Jev API
ENDPOINT = os.environ.get("TYPESAFE_API_BASE", "https://api.typesafe.ai") + "/v1/systemone"Agent skill that spots bounded-judgment steps, tries a typed decision model (TypeSafe's Jev) first, and documents every attempt
if not model or model == "jev-latest":
Ultra-fast browser automation using TypeSafe Jev via Panerelay and OpenRouter.
`,e+=" a b c d e f g h",e}perft(e){let t=this._moves({legal:!1}),n=0,i=this._turn;for(let r=0,a=t.length;r<a;r++)this._makeMove(t[r]),this._isKingAttChess moves, evaluations, persona opponents, and game classification with TypeSafe AI System One
response = client.post('https://api.typesafe.ai/v1/systemone', json=payload, timeout=min(20, remaining))Experimental Jev game agent: RAM, emulator lookahead, checkpoint search and verified recordings. Bring your own ROM and BizHawk.
public const string Endpoint = "https://api.typesafe.ai/v1/systemone";
Flow Launcher predictive file search with Jev intent reranking. Type natural language like 'the pdf I just downloaded' and get the right file.
const API_URL = "https://api.typesafe.ai/v1/systemone";
Jev plays browser table tennis in real time: structured telemetry, typed decisions, ordinary Chrome inputs, and auditable evidence.
const typesafe = configFromEnv({ TYPESAFE_API_KEY: 'ts', JEVC_MODEL: 'jev-1.13', JEVC_BASE_URL: 'https://proxy.example/v1/systemone' });Pi extension suite powered by Jev: selective context compaction and model routing
ENDPOINTS = {'typesafe': 'https://api.typesafe.ai/v1/systemone',Análise crítica e plano de aplicação do Jev em decisões estruturadas
const val ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Computer use with TypeSafe Jev: control your PC, browser, games and Android phone with a prompt
assert!(headers.starts_with("post /v1/systemone "));Twitch/Discord moderation rules in plain English, powered by Jev and Gemini
ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Jev x NetHack: bounded runner, research code, and completed recording releases
.post(Uri.parse('https://api.typesafe.ai/v1/systemone'),Run Flutter integration tests using natural language with TypeSafe.ai's Jev
const TYPESAFE_URL = 'https://api.typesafe.ai/v1/systemone';
Jev learns to play flappy-bird game with physics based context and without it
The API is a single endpoint (``POST /v1/systemone``), so we talk to it with
Home Assistant Assist conversation agent powered by TypeSafe's Jev (System One) model
export const DEFAULT_MODEL = 'typesafe/jev-1.13';
Claude Code mod: Jev-scored context pruning through OpenRouter. Verbatim compaction, an optional gate on oversized tool outputs, tests and evals.
pub const DEFAULT_BASE_URL: &str = "https://api.typesafe.ai";
Unofficial typed async Rust client for the TypeSafe System One API
public static final String DEFAULT_BASE_URL = "https://api.typesafe.ai";
A Java client for TypeSafe's System One API and its Jev models: send some state and a set of
const BASE_URL = process.env.TYPESAFE_BASE_URL || "https://api.typesafe.ai/v1";
Drive the ego lite browser with Jev (TypeSafe System One): one indexed element table in, one operation + target out, single process. ~2x faster than a per-step LLM loop in our measurements.
"""Thin wrapper around TypeSafe AI's official Python SDK (`typesafe-sdk`,
Google ADK vs Microsoft Agent Framework for structured-output agents, with TypeSafe Jev as a vendor-neutral QC gate
const response = await fetch('https://api.typesafe.ai/v1/systemone', {This tool analyzes YouTube video transcripts using three primitive question types from TypeSafe's Jev model:
description: "Request and response contract for POST /v1/systemone.",
A curated list of projects built on Jev, TypeSafe AI's System One model.
Pareto-optimal menu picks on cost, macros, deliciousness, and reviews — with TypeSafe/Jev scoring and a fixed output schema.
"""Thin HTTP client for the TypeSafe /v1/systemone endpoint.
Everything you need to run TypeSafe's Jev with Claude Code: a tool-call guard, tier guard, file search, browser agent, review, belay, compaction and installers.
.post("https://api.typesafe.ai/v1/systemone")DAG creation out of unordered items via Jev
const response = await fetcher("https://api.typesafe.ai/v1/systemone", {Recursive semantic file search using TypeSafe Jev and fzf
const r = await fetch("https://api.typesafe.ai/v1/systemone", {An observable raw-character chat experiment powered entirely by TypeSafe Jev Choice
constructor(apiKey: string, baseUrl = "https://api.typesafe.ai/v1") {Zero-dependency TypeScript client for TypeSafe Jev (System One decision model) — OpenRouter, TypeSafe direct, and Vercel AI Gateway providers
"ai-model-id": "typesafe-ai/jev",
Grade page sections for clarity, writing and on-page SEO. WXT + TypeSafe AI Jev.
TYPESAFE_BASE_URL Default https://api.typesafe.ai
TypeSafe Jev-scored context recovery for Cursor CLI (agent). Capture tool I/O, score keep/drop, re-inject after native compact.
POST /v1/systemone Jev-compatible (TypeSafe's shape): {state, questions, model}convaiinnovations/laya 的本地推理引擎:不训练、不微调,把官方发布的三份权重跑成一个 HTTP 决策服务,Mac(Apple 芯片)上开箱可跑;同时复刻 TypeSafe Jev 的请求/响应格式,按官方接口写的客户端只改一个 base URL 就能打到本地权重,其余代码、类型、校验都不用动。
ap.add_argument("--model", default=os.environ.get("JEV_MODEL", "typesafe/jev-1.13"))Jev-shaped typed-decision model (state + Choice/Score/Noul questions -> calibrated probabilities, one pass) on ModernBERT / DeBERTa / LLaDA-MoE, with measured latency, accuracy, calibration and training cost
api_base: str = "https://api.typesafe.ai/v1",
Turns Jev into a chatbot
Endpoint: POST https://api.typesafe.ai/v1/systemone
Let Jev (TypeSafeAI) solve 2048
import { choice, noul, score, TypeSafeClient } from "@typesafe-ai/sdk";A small Next.js app for experimenting with TypeSafe AI's Jev model (System One)
import type { JsonValue, Questions } from "@typesafe-ai/sdk";A living-world RPG whose NPCs are decided by TypeSafe's Jev judge model; code owns rules, numbers and state.
JEV_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Cost-optimized OpenRouter model router using TypeSafe's Jev, with a live full-catalog scorer instead of a hardcoded model list
TYPESAFE_BASE_URL: Final = "https://api.typesafe.ai"
Home Assistant custom component: Conversation agent with Jev fast-path + Grok fallback
std::string api_url = "https://api.typesafe.ai/v1/systemone";
Natural-language row filtering for MySQL, powered by TypeSafe Jev.
<article class="feature-card sdk-card"><div class="feature-visual" aria-hidden="true"><span class="code-tag"></></span><span class="visual-caption">THE BU
A curated list of Jev / TypeSafe System One projects, SDKs, tutorials, and evaluations. English and 简体中文.
import { TypeSafeClient } from '@typesafe-ai/sdk';Standalone TypeSafe Jev code-review CLI: typed decisions over a local git diff.
API_URL = "https://api.typesafe.ai/v1/systemone"
TypeSafe (Jev) vs DeepSeek-flash: side-by-side speed/token/cost/accuracy comparison across invoice extraction, email classification, and reranking
.unwrap_or_else(|_| "https://api.typesafe.ai/v1/systemone".into()),
A playground for experiments around Jev, TypeSafe's System One model.
#define JEV_DEFAULT_URL "https://api.typesafe.ai/v1/systemone"
Batched natural-language judgments for SQLite, powered by TypeSafe Jev
const API_URL = 'https://api.typesafe.ai/v1/systemone';
Auto permission mode for Command Code: screens every tool call with TypeSafe Jev before it runs, and rejects anything out of scope.
* POST https://api.typesafe.ai/v1/systemone
Jev can't generate text. So I made it talk anyway. A conversational interface built from probabilistic decisions and a deterministic language compiler — no generative LLM.
delivery = { via: "jev" };Jev-based adaptive model routing with structured decisions, persistent feedback, and hybrid retrieval
API_URL = "https://api.typesafe.ai/v1/systemone"
Jev powered code review hook for agents
const JEV_URL = 'https://api.typesafe.ai/v1/systemone';
Jev に判断を任せる自動生成のエレクトロの楽器
Get Jev fast — TypeSafe’s sharp System One for typed decisions, plus kindred models the community is buzzing about.
const Endpoint = "https://api.typesafe.ai/v1/systemone"
A bounded Jev risk check for Claude Code: eight risk axes, one request, one optional reinspection.
const response = await (options.fetch ?? fetch)("https://api.typesafe.ai/v1/systemone", {pi-jev-agent is an experimental extension for the Pi coding agent. It uses TypeSafe Jev to choose the next tool before each language-model step.
import typesafe_sdk as sdk
experiments with system one model jev
// "~typesafe/jev-latest" always points to the newest Jev. The tilde matters:
Throw in a pile of company files and get them classified and organized by department, type, sensitivity, date, counterparty and PII, with an index for AI agents. Powered by TypeSafe's Jev on OpenRouter (17¢ per 1,000 files). Zero-dependency Node CLI + Claude skill + Codex agent.
"typesafe": ("https://api.typesafe.ai/v1/systemone", "jev-latest", "noul", "noul"),A Stop hook that stops your coding agent from stopping too early. Plain-language rules, judged by jev.
import { TypeSafeClient, noul, score } from "@typesafe-ai/sdk";Moderation Guard — TypeSafe Jev demo
const API_URL = "https://api.typesafe.ai/v1/systemone";
Classify notes with Jev and file them into folders by attribute.
baseUrl: "https://api.typesafe.ai/v1/systemone",
Jev-scored context pruning for OpenCode: drops stale tool calls and truncates bulky results on the outgoing request — fail-open, cache-backed, configurable live. Port of fast-jev-compaction to the V2 context hook.
TS_URL = os.environ.get("TS_MCP_TS_URL", "https://api.typesafe.ai/v1/systemone")MCP server exposing TypeSafe (Jev/System One) to the fleet: judge, rerank, systemone
TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone"
Score every file in a pull request with Jev (TypeSafe System One) and decide in code whether it can merge itself. Shadow mode: comments, never merges.
# - TypeSafe native-shaped: POST /v1/systemone, GET /v1/models
Typed decisions from the shell: an unofficial stdlib-Python CLI and Agent Skill for TypeSafe's Jev model, via the TypeSafe API (default) or OpenRouter. Yes/no, choice and ordinal scores with calibrated probabilities, semantic grep and batch mode.
from jev_engine import SystemOneClient, Noul, Choice, Score, SystemOneResult
Jev-Engine: 面向软件工程的 System One 离散决策引擎与完整上下文投影切片管道
const fn = (mod['experimental_evaluate'] ?? mod['evaluate']) as EvaluateFn | undefined;
Busca em arvore (MCTS/PUCT) com avaliacao tipada do TypeSafe Jev e portao humano obrigatorio. A arvore supoe, a sonda mede: marco so e concedido por codigo de saida verde.
jevModel: options.jevModel ?? (process.env.OPENROUTER_JEV_MODEL?.trim() || 'typesafe/jev-1.13'),
Natural-language end-to-end tests for web apps, powered by Jev and Playwright.
| `:base_url` | `TYPESAFE_BASE_URL` | `https://api.typesafe.ai` |
Unofficial Elixir client for TypeSafe's System One API (Jev): typed Noul, Choice and Score judgments over Req
pub const DEFAULT_BASE_URL: &str = "https://api.typesafe.ai";
Unofficial Rust client for TypeSafe's System One API (Jev): typed Noul, Choice and Score questions, async and blocking
import type { SystemOneResult } from "@typesafe-ai/sdk";Jev (TypeSafe AI) PoC through Game of Thrones
API_URL = "https://api.typesafe.ai/v1/systemone"
TypeSafe Jev plays original Civilization II in a browser, with live action probabilities. Experimental full-game harness.
TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone"
使用Jev模型进行决策的量化交易
JEV_URL = "https://api.typesafe.ai/v1/systemone"
Jev (TypeSafe System One) × ASReview SYNERGY abstract screening demo — Choice/Noul vs gold labels
TypeSafe's docs warn that ``jev-latest`` moves and that tuned confidence
jevkit for Python: static linter and shared record format for building on TypeSafe's Jev (System One) model. Unofficial.
if (kind === 'typesafe') return 'https://api.typesafe.ai/v1/systemone';
A browser-first AI poker benchmark. Seat Jev and OpenAI-compatible models at the same no-limit Texas Hold'em table, watch every card and decision as a spectator, and let the tournament run autonomously until one model wins.
DEFAULT_URL = "https://api.typesafe.ai/v1/systemone"
Hermes Agent skill whose north-star gate is judged by Jev (TypeSafe System One): turn an intention into a checkable finish line, generate the run prompt, and let Jev rank what is still unproven.
export function createDecider(endpoint = "https://api.typesafe.ai/v1/systemone"): Decide {Opt-in Auto (Jev) model routing for OpenCode with a configurable model allowlist
TYPESAFE_URL = "https://api.typesafe.ai/v1/systemone"
general Chrome agent — Jev + OpenRouter
model: "~typesafe/jev-latest",
open-sourced jev-flash-router: an MCP server for TypeSafe's new Jev model. AI coding agents waste hundreds of reasoning tokens just deciding which file to edit, which route to pick, or whether a diff breaks tests. Jev evaluates state and outputs calibrated probabilities. Works with Cursor, Windsurf, & Claude Code
const DEFAULT_API_BASE = "https://api.typesafe.ai/v1";
Pi extension that classifies each prompt with TypeSafe's Jev and routes it to the best model you're logged into.
import { experimental_evaluate as evaluate } from "ai";See what Jev thinks about your SaaS website — powered by ReplyNodes web context and Vercel AI Gateway.
const CODE_QUERIES = ['"@typesafe-ai/sdk"', '"typesafe_sdk"', '"api.typesafe.ai"', '"jev-latest"']
Projects built on Jev (TypeSafe AI's System One model), curated by Jev itself.
APIURL = "https://api.typesafe.ai/v1/systemone"
Results page: https://claude.ai/code/artifact/f00ee126-9554-4e2f-b2e7-1fc86c066aa9
const res = await fetch("https://api.typesafe.ai/v1/systemone", {Chrome extension that stamps every X post with a type badge — alpha, shitpost, AI slop, bait — judged by Jev from Typesafe
"http://127.0.0.1:8768/v1/systemone",
Run jev-browser on a fully local JEV-style decision engine (no cloud API). Warm-browser fork, VRAM guard, measured benchmarks, run traces.
model: str = "typesafe:jev-1.13.0"
TypeSafe/Jev router plugin for Hermes Agent — compact tool results, suppress duplicate tools, skip unnecessary main-model calls
import type { ChoiceQuestion, NoulQuestion, Questions, ScoreQuestion, SystemOneResult } from '@typesafe-ai/sdk'Paper trading agents on a live tape, decided every second by TypeSafe's Jev (System One). Electron desktop app.
import { TypeSafeClient, choice, noul } from '@typesafe-ai/sdk';Write Cucumber tests with just the .feature file. No step definitions — Jev (TypeSafe AI) resolves each Gherkin step and Playwright runs it.
URL = "https://api.typesafe.ai/v1/systemone"
Jev (TypeSafe AI) 可复现实测:算术、计数、日期、零幻觉、把握度校准,中英对照
from typesafe_sdk import AsyncTypeSafeClient, RetryPolicy
AI detection in research papers with Jev
import { noul, score, TypeSafeClient } from '@typesafe-ai/sdk';Low-latency audio censorship POC using Jev typed decisions and ffmpeg.
import { type NoulQuestion, noul, TypeSafeClient } from "@typesafe-ai/sdk";Fast deep research for the pi coding agent: reads up to 100 pages in full per round, Jev keeps only the passages that answer your questions.
import { choice, TypeSafeClient, type EntryType } from '@typesafe-ai/sdk';Reproducible benchmark evaluating JEV as a software decision primitive for dependency-update automation under distribution shift.
import { choice, noul, score, TypeSafeClient } from "@typesafe-ai/sdk";Practical guide to using TypeSafe Jev with Herdr and Claude, Codex, Hermes, and browser agents.
import { TypeSafeClient, type TypeSafeClientConfig } from '@typesafe-ai/sdk';Analyze prompts with TypeSafe Jev before GitHub Copilot
this.baseUrl = opts.baseUrl ?? process.env.JEV_BASE_URL ?? "https://api.typesafe.ai/v1";
Cost-aware PR review using TypeSafe Jev decisions before a generative reviewer.
TypeSafeClient,
TypeSafe AI (Jev) adversarial reviewer and typesafe_ask tool for the omp coding agent
req=urllib.request.Request('https://api.typesafe.ai/v1/systemone',data=json.dumps(p).encode(),headers={'Authorization':'Bearer '+self.key,'Content-Type':'applicReproducible evaluation of TypeSafe Jev on all 58,492 BBQ questions: accuracy, stereotype bias, uncertainty, cost and latency.
url = "https://api.typesafe.ai/v1/systemone",
A native R client for Jev System 1 model decisions
$columns['jev_triage'] = __( 'Jev', 'jev-comment-triage' );
Async Jev-powered WordPress comment triage: background spam, scam/phishing, and toxicity moderation that keeps comment submission fast.
const kDefaultBaseUrl = 'https://api.typesafe.ai';
Typesafe Jev Api
4. HTTP: `POST https://api.typesafe.ai/v1/systemone`
Unofficial list of insanely useful TypeSafe AI Jev / System One projects
import { choice, TypeSafeClient } from "@typesafe-ai/sdk";Turn any word into probability distributions over taste, material, scent, and shape. Powered by Jev.
import { experimental_evaluate as evaluate } from 'ai';iOS 6-inspired Jev calculator demo with a lifetime API budget
e = estimate({"state": "...", "model": "jev-latest", "questions": {...}})Unofficial CLI + Python estimator of tokens, cost and context limits for TypeSafe (System One / Jev) API requests. Not affiliated with TypeSafe.
TypeSafeClient,
Computer Use Agent developed with Jev
const API_URL = "https://api.typesafe.ai/v1/systemone";
TypeSafe Jev arcade
endpoint: str = "https://api.typesafe.ai/v1/systemone"
用 TypeSafe Jev(System One)驱动扫雷自动通关:HTML 扫雷页每走一步实时问模型,并把它的选项、概率、代码已证明的事实全部可视化。Play Minesweeper with TypeSafe Jev (System One): an HTML game that asks the model every move and visualises its options, probabilities and the facts the code proved.
import { choice, TypeSafeClient } from "@typesafe-ai/sdk";8 AI snakes, 1 human, 1 arena. Every snake is driven live by TypeSafe's Jev, making all decisions in real time
.post("https://api.typesafe.ai/v1/systemone")File-scoped maintainability review with TypeSafe Jev
jev_api_url: str = "https://api.typesafe.ai/v1/systemone"
A local playground for comparing Laya and Jev decision models with article recommendations.
const response = await (this.options.fetch ?? fetch)('https://api.typesafe.ai/v1/systemone', {Jev-powered tool and skill selection, context search, and output triage for Codex via MCP
const JEV_URL = process.env.JEV_URL || 'https://api.typesafe.ai/v1/systemone';
Every token passes the gate before the screen.
import type { EntryType } from '@typesafe-ai/sdk';Rule-based code review for AI coding agents, powered by TypeSafe Jev.
// Thin client for TypeSafe AI's Jev (POST /v1/systemone).
Real-time support triage + response bot Jev routes the ticket to a specialist agent (general / account / billing / technical) and decides whether a human should take it instead — all as typed data, no text to parse. Cerebras then drafts the reply using whichever agent Jev picked. The script times both calls separately so you can see the split.
const response=await fetchImpl('https://api.typesafe.ai/v1/systemone',{A nutrition label for privacy policies. Plain-language answers, confidence scores, and source excerpts powered by Jev.
response = await request('https://api.typesafe.ai/v1/systemone', { method: 'POST',A small advisory tool for comparing supplied alternatives against supplied evidence.
"how_used_jev": "The backend works with api.typesafe.ai and with openjev-sglang, an open Jev HTTP API on SGLang.",
What people are actually shipping with Jev — real builds, tracked as they ship.
import { noul } from "@typesafe-ai/sdk";Semantic PR gate: .jev.yml rules as TypeSafe Jev questions. Not a review bot.
import { experimental_evaluate as evaluate } from 'ai';A vocabulary-driven TypeScript runtime for safe, stateful applications powered by TypeSafe AI Jev.
from langchain_typesafe import Choice, Noul, NoulCriteria
LangChain / Deep Agents middleware that uses TypeSafe's System One model (Jev) for typed judgments in unattended coding agents: a shell-command gate (database, production, destructive, secrets), issue triage and routing by severity and urgency, merge-request detection, and review of weakened tests. Measured with live probes.
System One Models & Jev documentation. typesafe.ai documentation extracted in .md format for LLMs. Used to train LLMs.
DEFAULT_ENDPOINT = "https://api.typesafe.ai/v1/systemone"
Benchmarking Jev (Typesafe.ai) against a strong LLM on the Who&When Pro agent-failure-attribution benchmark (text subset).
"""Client for TypeSafe's Jev decision model (POST /v1/systemone).
Benchmarking TypeSafe's Jev decision model as a cost-efficient LLM router on RouterArena
DEFAULT_MODEL = "~typesafe/jev-latest"
A Hermes Agent model-provider plugin that routes selected auxiliary tasks through bounded Jev decision calls on OpenRouter instead of free-form chat prompts.
const UPSTREAM_URL = 'https://api.typesafe.ai/v1/systemone';
トランプの スピード を、CPU 側の頭脳に TypeSafe AI の Jev を使って対戦する WebGL デモアプリ。Jev の判断速度と判断精度をリアルタイムに計測して見せることが目的。
This module never imports `typesafe_sdk` or `alpaca`: `check_sdk_log_level` has to run BEFORE the SDK is imported anywhere.
Options trading bot (backtest + Alpaca paper only) with TypeSafe Jev as the decision core
} from "@typesafe-ai/sdk";
JEV picks which stream idea becomes the live MVP. TypeSafe System One decision board.
constructor({ apiKey = process.env.TYPESAFE_API_KEY, endpoint = process.env.TYPESAFE_ENDPOINT ?? "https://api.typesafe.ai/v1/systemone", model = process.env.TYPPortable System-1 decision layer for agent harnesses with host-owned routing, receipts, replay, and fail-open integrations.
The `jev` decorator discards confidence, so this calls Jev through `typesafe_sdk` directly.
Review Kotlin files against From Objects to Functions principles using Jev
"jev",
Portable agent skill: TypeSafe Jev as a cheap code-review classifier (HTTP + optional jev-review MCP)
questions to typesafe_sdk types and projects the response back to jcyber's
Agent-driven bug bounty / pentest framework: one gated chain over five systems (Caido, HexStrike, Jev, Memgraph, TencentDB, Prometheus)
data, response, err := c.execute(ctx, http.MethodPost, "/v1/systemone", body, resolved)
A Go SDK for the TypeSafe API, enabling quick integration with Jev.
"""FastAPI app: POST /v1/systemone, Jev-compatible contract."""
Local Jev-compatible evaluation server: POST /v1/systemone with typed noul/choice/score, open weights, no waitlist
def __init__(self, model="jev-latest", url="https://api.typesafe.ai/v1/systemone", threads=4):
화재 피난자 개인별 판단 엔진 — 타입 안전 판독(Bonsai 2 27B / TypeSafe Jev) + 소셜포스 이동, FDS-GPU 화재장 위에서 역할·구조·경로 결정 · Meteor Simulation
default: 'https://api.typesafe.ai',
Helper n8n community node for Jev by TypeSafe. Classify, route, and score text with questions you define, and get a probability for every answer so unsure items can go to review.
* Non-blocking client for TypeSafe Jev's {@code /v1/systemone} endpoint.Non-blocking Spring Boot Starter for Spring WebFlux that implements a Semantic Circuit Breaker to detect silent HTTP 200 failures using TypeSafe Jev.
name="jev",
Give any MCP-capable LLM harness an on-demand real-browser search tool (TypeSafe Jev) with per-run timing and cost tracking.
"model": os.environ.get("JEV_DECISIONS_MODEL", "~typesafe/jev-latest"),jev-mcp turns browser-use/jev-ultrafast into one local, session-aware MCP server for fast read-only product research. Jev selects an action and observed target from a DOM snapshot;
export const ENDPOINT = 'https://api.typesafe.ai/v1/systemone';
Jev-powered context curation for Codex. Build compact, traceable handoff context through native plugins and skills.
API_URL = "https://api.typesafe.ai/v1/systemone"
Local console + CLI for TypeSafe's Jev (System One) model: send a state and typed questions, get calibrated probabilities back.
baseUrl: "https://api.typesafe.ai/v1/systemone",
Jev decides what to keep. Compaction never rewrites the transcript.
const TYPESAFE_ENDPOINT = "https://api.typesafe.ai/v1/systemone";
A beautifully minimal Magic 8 Ball powered by Jev from TypeSafe. Twenty classic answers, one fast AI judgment.
DefaultBaseURL = "https://api.typesafe.ai"
Typed answers from Jev, in idiomatic Go.
"3. Would a sensible person answer it in under a second from text you can show them? -> TypeSafe/Jev.\n" +
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.
"jev_model": "typesafe/jev-1.13", "base_model": base_model,
A Jev decision toolbox for agents and people: 56 recipes, an OpenRouter CLI, and transparent paired evaluations.
const response=await fetch('https://api.typesafe.ai/v1/systemone',{method:'POST',headers:{Authorization:`Bearer ${process.env.TYPESAFE_API_KEY}`,'Content-Type':弈瞬:双 Jev 五子棋九宫格输入实验台,逐手查看模型决策,支持真实对局回放与实时对战。
return [{ client, name: 'jev', fresh: true }];Jev 活动看板:自动接入 MCP,实时查看真实输入、判断结果与用量。Local-first, passive MCP observability.
const args=proxyPath?['--no-warnings',proxyPath,...(proxyPath.endsWith('cli.mjs')?['proxy']:[]),process.env.JEV_MCP_SERVER||'jev']:Discover real Jev use cases. A source-linked catalog with MCP classification, semantic deduplication, and a public browsing demo.
import { choice, TypeSafeClient } from "@typesafe-ai/sdk";이름으로 나이대를 맞히는 React 웹 (TypeSafe Jev)
export const TYPESAFE_ENDPOINT = "https://api.typesafe.ai/v1/systemone";
Isolated Playwright browser for pi, driven by Jev typed decisions through the TypeSafe API or the model pi already has configured.
string $baseUrl = 'https://api.typesafe.ai',
Démo : trier des demandes de support avec Jev (TypeSafe) et Symfony AI. Messenger, Live Components, Turbo, kit shadcn de UX Toolkit.
from .engine import FoqEngine, FoqConnectionError, SystemOneResponse
⚡ 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
export const CLASSIFICATION_MODEL = "typesafe/jev-1.13";
Pi extension that uses Jev task classification (via OpenRouter) to route each run to explicitly configured models with fail-open policy. Public Preview.
import { experimental_evaluate as evaluate } from "ai";Hide what you'd rather not see: a Chrome extension demo where natural-language rules are judged by TypeSafe's Jev
DEFAULT_MODEL = "typesafe/jev-1.13"
Instant semantic code search: local ripgrep shortlist, meaning-ranked by TypeSafe Jev via OpenRouter.
endpoint: "https://api.typesafe.ai/v1/systemone".to_string(),
System One TypeSafe AI Rust Client (unofficial)
defaultBaseURL = "https://api.typesafe.ai"
Idiomatic Go SDK for the TypeSafe AI API
MODEL = "~typesafe/jev-latest"
Can a TypeSafe Jev prior read from a README on day one predict which new agent-skill repos gain stars? Zero-shot Jev ≈ a text model trained on ~150 labels; best used as a feature. Prospective test running.
MODEL = "~typesafe/jev-latest"
Can a Jev-labelled GitHub issue stream catch a broken release before the fix? No at daily cadence (null, n=7). Per issue, Jev matches triage labels far better than keywords or sentiment.
MODEL = "~typesafe/jev-latest"
Does a Jev-labelled support-tweet stream spike before a brand admits an outage? At equal false alarms it catches 17 vs 10 incidents (volume), ~4h ahead; a good keyword list is almost as good.
"""调用 OpenRouter decisions API(typesafe/jev-latest)的最小示例。
a repo that helps you learn jev model.
python scripts/run_baseline.py --model jev --base-url https://api.typesafe.ai/v1 --api-key-env TYPESAFE_API_KEY
Typed-decision benchmark from PadFlow (land development SaaS): schemas, anonymized labeled rows, and a runner for confidence-calibrated models like TypeSafe Jev.
const API = "https://api.typesafe.ai/v1/systemone";
Let Jev, TypeSafe's ~100ms decision model, drive your browser. A plug-and-play skill for Claude Code and Codex.
POST /v1/systemone {state, model, questions} -> {model, answers, usage}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.
const TYPESAFE_ENDPOINT = 'https://api.typesafe.ai/v1/systemone';
Jev-powered integer sorting experiment: serial selection versus parallel rank prediction.