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CommunityTools & Integrations22 starsVerified 2026-09-22

jev-guard

A security hook for coding agents that asks Jev three typed questions before every tool call and scans tool results for prompt injection, with adapters for Claude Code, Codex, Copilot CLI, Gemini CLI, Cursor, pi, OpenCode and ACP.

Category
Tools & Integrations
Published by
Community
Author
leepokai
Added
2026-09-22
Tagscommunityjavascriptagentscoding-agentsecurityguardrailsclaude-codecodex

Highlights

  • Before a tool runs, Jev scores the harm, whether the user requested it, and whether it came from untrusted content; destructive calls are denied.
  • After a tool returns, results are scanned for prompt injection and canaries, and hits are remembered for the rest of the session.
  • Instruction files such as skills and CLAUDE.md are checked for exfiltration, covert execution, instruction override, and canaries.
  • A typical call is about 1k tokens, roughly $0.00004 per tool call, with measured p50 around 580 ms through the Vercel AI Gateway.
  • On a machine with 662 installed skills, none crossed the flag line, while planted exfiltration samples scored 0.99.

Quickstart

bash
npm i -g jev-guard
jev-guard key YOUR_API_KEY
jev-guard install claude

Watch out

MIT-licensed. Needs Node.js 20.3+ and a TypeSafe or Vercel AI Gateway key; it is a guardrail, not a sandbox, and tool results can contain anything the agent read.

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From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

Fast browser use with Stagehand

we built blazing fast computer/browser use with Jev + @Stagehanddev. this task cost $0.001 and executed at near instant speed (in a remote browser btw) the loop: observe the page, send a11y tree as state + actions as questions, Jev decides the next action, then Stagehand Show more

Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

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LLM-as-a-judge, sped up

Jev has spoken. It picked which model is AGI. 20–200x faster. 40–400x cheaper. This could make things like LLM-as-a-judge insanely fast and nearly free. (I tried a bunch of prompts and still didn’t burn through $0.10.)

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Diogo Almeida
Diogo Almeida
TypeSafe AI
@CompleteSkeptic

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

Reply

Instant compaction with Jev

A Claude session from 1M to 86K tokens

This is actually insane. This uses @typesafeai Jev model, as a plugin in Claude to review all the un-nesseasary tool calls, and it takes 1s to run! Like, literally, 1 second to take my Claude session from nearly 1M to ... 86K tokens! 😮 Ask your claude to install it and be  Show more

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tamara
tamara
@tamarajtran

found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant

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Vercel's fx safety reviewer, 18x faster

We're seeing extraordinary results from @typesafeai. Default mode in 𝚏𝚡 is auto, with a safety reviewer analyzing every command. That reviewer runs on GPT Luna today. Jev is up to 18x faster (p95) *and* more accurate. It's coming to @vercel AI Gateway and likely new default.

Pranit
Pranit
Vercel
@fazxes

We benchmarked fx auto mode (safety) classifier with @typesafeai's Jev. tl;dr: ~5-18x faster and more accurate than 𝚐𝚙𝚝-𝟻.𝟼-𝚕𝚞𝚗𝚊, our current top choice

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Jev lands on OpenRouter