Jev Ultrafast
A browser loop where Jev selects an operation and page element, with a text model handling field input.
Browse Jev browser-control and agent projects: selecting actions, inspecting page state and checking outcomes. Each source describes its own runtime and installation requirements.
Compare five browser-agent approaches
Public projects, checked against their original sources.
A browser loop where Jev selects an operation and page element, with a text model handling field input.
An Android agent using Jev decisions and Mobilerun, with a live studio, CLI, and execution traces.
A macOS control loop that combines OCR and accessibility data with Jev action selection.
A staged Jev workflow for inspecting Git changes or source files, with a local review dashboard.
A Go CLI and MCP server that lets coding agents request typed Jev evaluations.
An official agent skill for designing TypeSafe workflows and finding the relevant API guidance.
A CLI and MCP browser tool pairing Jev decisions with agent-browser actions.
A Playwright browser harness splitting goal planning, typed action decisions, and text generation.
A Pi extension that adds Jev assessments before tool use and after file changes.
Hide page clutter with reusable, Jev-classified browser rules.
Delegate a bounded browser step to Jev through MCP.
Control macOS apps through accessibility targets chosen by Jev.
Bring Jev’s indexed action selection to the ego lite browser.
A compact Jev browser loop paired with a timed task benchmark.
Add Jev judgment labels to X posts and Hacker News comments.
One Playwright core exposed as a persistent CLI, SDK, and MCP server.
Explore native desktop control with Jev and an optional planning model.
Search and follow web evidence with Jev-ranked pages and links.
Inspect Jev browser decisions in a local visual control panel.
Let Jev drive browser steps and escalate uncertainty to the calling agent.
Run persistent Android tasks with Jev selecting valid device actions.
Add page checks and action judgment to an existing Playwright MCP setup.
Explore browser flows with Jev decisions and replayable test evidence.
Reorder Google results using Jev relevance and promotional-content judgments.
Optionally blur text flagged as advertising or AI-like prose.
Run browser goals through named actions and Jev selections.
Use Jev to supervise evidence from a coding agent’s work.
Evaluate Pi edits and actions against project rules with Jev.
Archived Jev Codex Router: per-call model and effort selection for a local Codex setup.
Reduce large Claude Code tool results using Jev relevance judgments.
Expose typed Jev judgments as composable commands for coding agents.
Inspect a pull request’s risk, review depth, and test gaps.
Delegate file ranking, change checks, and triage to bounded Jev workflows.
Use a single model route with Jev selecting from a provider catalog.
Pair a Pi coding model with Jev judgments and explicit action policies.
Route Claude Code requests while accounting for prompt-cache tradeoffs.
Inspect MCP calls, results, and tool descriptions with Jev.
Review proposed database migrations with typed Jev judgments.
Add Jev option scores and optional skill routing to Claude Code.
Evaluate agent tool calls for risk, user intent, and untrusted influence.
Add an advisory Jev reviewer to an OMP coding session.
Run an issue-to-PR loop with tests, an independent reviewer, and Jev checks.
Combine repository policy with semantic change-risk signals.
Check a coding agent’s stopping point against plain-language rules.
Review whether a Pi session openly left required work unfinished.
Add semantic checks and traceable review signals to a single Pi agent.
Combine Jev safety signals and model selection in an LLM gateway.
Check source files against natural-language coding conventions.
Suggest a relevant installed capability for the current agent prompt.
Route an OpenAI-compatible model ID through a Jev decision.
Use Jev as a typed decision layer within Pi.
Give a Hermes agent a typed Jev tiebreaker.
Return structured code-quality judgments to a coding agent over MCP.
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Source description: Block, steer, and "fuzzy lint" with Jev to make agents follow your rules and conventions. CLI, github action, pi package, claude extension, and more. Built with Effect + TypeScript.
Source description: RuneBench harness for TypeSafe's Jev: bounded action catalog, tick-mode controller and a live dashboard
Source description: Pi coding-agent extension: TypeSafe Jev checks for tool calls, tool outputs and replies (prompt injection, approvals, secret scrubbing, task pinning)
Source description: Pass-through model router for Claude Code and Codex CLI that picks a model tier per human turn with Jev, TypeSafe AI's decision model
Source description: Automatic model routing for Pi using TypeSafe's Jev through Vercel AI Gateway
Source description: pre-commit hook: one Jev call judges whether your commit message matches the diff, plus debug leftovers, scope creep, and a secret belt
Source description: The complete cookbook for Jev by TypeSafe AI — 120+ use cases, 10 runnable examples, 4 composition patterns, and first-principles theory for the world's first System One AI model.
Source description: Polymarket trading bot driven by Jev (TypeSafe AI) via OpenRouter
Source description: A fuzzy linter for coding agents. It checks the code your agent writes against your team's best practices while the agent is still working, not at code review.
Source description: Agent Skill and Python CLI for local video remixing, Jev judgments, and originality reports.
Source description: Let TypeSafe Jev decide whether a message you send mid-turn should steer, queue, or interrupt your coding agent. Claude Code plugin; Codex CLI in testing.
Source description: Claude Opus 5.5 with the effort level re-decided every step by the TypeSafe Jev reflex — without breaking the prompt cache. CLI + Claude Code plugin.
Source description: 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.
Source description: Screens an AI agent's tool calls before they run and tool results before the agent reads them. An MCP proxy plus a hooks adapter for a client's built-in tools.
Source description: Command-line tool for TypeSafe's Jev AI model
Source description: Interactive TypeScript coding CLI powered by Jev typed decisions and constrained AST generation.
Source description: Jev decision layer for agents: MCP server, embeddable DecisionModel library, and an escalate-only Claude Code plugin (TypeSafe AI's Jev)
Source description: 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.
Source description: MCP server for TypeSafe Jev: typed classify, score, check, match and screen for any agent, with confidence on every answer
Source description: Jev decision layer for Muse: a fast, cheap TypeSafe AI gate before expensive agent work — confidence policy, recipes, reference router, honest measurement.
Source description: Production TypeSafe Jev (System One) use-case harnesses with confidence-gated decision logic
Source description: One local endpoint. The right model for every turn — enforced in code, not prompts.
Source description: Jev-powered plugins for coding agents
Source description: Jev-powered decision support for OmO and senpi agents
Source description: Claude Code plugin: Jev for rule checks, verbatim compaction, and prompt routing
Source description: A custom coding harness for TypeSafe AI's Jev: an LLM proposes, Jev answers narrow questions, code decides, every step leaves a receipt.
Source description: 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.
Source description: 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.
Source description: ⚡ Millisecond System-1 judgement for every tool call in DeepSeek Harness — Jev-powered risk classification & evidence-gated auto-approval. Fail-closed by construction. dsh 生态第一个 System-1 决策插件
Source description: A Claude Code mod that uses TypeSafe's Jev to decide auto mode tool calls. 2x faster than the built-in classifier on the calls it decides.
Source description: Fast, cheap, typed decisions for Claude Code. Jev (TypeSafe's decision model on OpenRouter) sorts, checks, scores, gates and verifies at 0.3s and a fraction of a cent per item. Claude keeps the reading, writing and judgment.
Source description: Rank Pi Agent Skills for the current task with TypeSafe Jev
Source description: Jev-powered, rule-based grader for text files. Runs every rule against every line in parallel. No skimming, no missed lines.
Source description: A prose linter that sniffs out AI writing tells. Zero dependencies, countable rules plus one judgment model.
Source description: A Jev powered LinkedIn recruiting agent. Watch it browse relevant profiles, save links, and review evidence against your hiring brief.
Source description: A zero-embedding approach to video intelligence, using Jev: contact sheets + typed decisions, as MCP tools and a skill for any coding agent.
Source description: A claude code plugin for jev
Source description: A codebase scanner that helps you not run malicous code
Source description: Retrieve by relevance, not resemblance: filter an AI assistant's memories with TypeSafe's Jev
Source description: MCP server that puts TypeSafe Jev on the coding loop in Cursor, Codex, and any MCP client
Source description: 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
Source description: Route HTTP requests by meaning. A semantic router for Hono powered by Jev.
Source description: 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.
Source description: A linter to codify code taste using Jev
Source description: Stops AI coding agents from claiming work is done without evidence. Deterministic hooks decide, TypeSafe's Jev advises. Append-only ledger, zero runtime dependencies.
Source description: Bounded TypeSafe Jev workflows for coding agents.
Source description: Connect TypeSafe Jev to Grok Bot as a cheap decision layer - usage gates, skill template, examples
Source description: TypeSafe Jev for DeepSeek Harness, the Model Context Protocol, and plain Node: typed judgments instead of prose, offline by default.
Source description: 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。
Source description: Native DeepSeek Harness (DSH) plugin integrating TypeSafe Jev or Decision api like luna as a System One decision layer for agent selection, supervision, corrections, and approvals.
Source description: Claude Code plugin: trim long Bash output with TypeSafe Jev before the model sees it
Source description: Coverage, security and code quality for coding agents
Source description: 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.
Source description: Fast, cheap, typed judgments from TypeSafe's Jev model, as MCP tools.
Source description: Search the web with TypeSafe's Jev: source selection, query understanding and relevance ranking. Built with Search1API.
Source description: A lightweight Jev-powered router for models, tools, and subagents
Source description: System One MCP connector to evaluate anything fast and cheap. Give your AI agent direct access to models like: Jev, D1, CLM and Laya
Source description: An easy way to use jev with your coding agent for tool calling reasoning
Source description: 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.