A Python toolkit that installs nine plain SKILL.md files for Hermes, Claude Code, and Codex, letting Jev route models, filter retrieved passages, select skills, and choose bounded computer or browser actions.
Nine skills ship as plain SKILL.md files that work in Hermes, Claude Code, Codex, or anything that reads a skill file, with Python 3.9+ and no dependencies.
Measured costs in the README: about 0.4 s per routed turn, 2.8 s to choose among 377 skills, and $0.00006 per triage message.
Routing starts in a shadow mode that decides and logs without switching anything, and install.py --check shows what would change before it does.
Every skill documents a safe default when Jev fails or is unsure: routing keeps the current model and memory returns the original list.
The API key stays in the OS keychain rather than reaching the agent, and the test suite is offline with every Jev reply faked.
Quickstart
bash
git clone https://github.com/kerpopule/hermes-jev-skills ~/hermes-jev-skills
python3 ~/hermes-jev-skills/install.py
jev setup-key
jev doctor
Watch out
MIT-licensed and independent of TypeSafe. Needs Python 3.9+ and a TypeSafe key; enabled features send redacted prompts or excerpts to TypeSafe, and suggest and calibrate read local session transcripts.
A collection of 26 production-ready agent skills for Claude Code, Cursor, Kiro, Windsurf, and OpenCode; four skills call TypeSafe Jev for calibrated Score and Noul judgments and fall back to heuristics when it is unavailable.
A cross-platform memory layer for AI coding agents: conversations from Claude Code, Codex, DeepSeek Harness, OpenClaw, and OpenCode become Markdown memories indexed in Milvus, with optional Jev reranking through the TypeSafe API.
A collection of Jev demos, workflows, and agent skills for coding agents: five installable skills and 108 scenarios, installed by pointing Codex, Claude Code, or OpenCode at an agent prompt.
Jev 发布没几天,开源社区已经开始疯狂复刻了🔥
最值得推荐的五个模型:
1、Laya 421M:原生决策模型,支持 Mac
2、Decider-2B:最像 Jev,基于 Qwen3.5
3、NanoJev 0.6B:专门的 Decision Head
4、Reflex:Qwen3.5 + Direct Logits
5、System-One 4B:专门做概率校准Show more
小墨同学
@xiaomovps
Jev 刚发布没几天,开源社区就出现了同款🔥
Decider-2B模型,是基于 Qwen3.5-2B 做了特殊调整
它和 Jev 模型是一样的 只做选择 评分和判断 不是文本类的 LLM 模型
但两者还是有几个明显区别:
1、模型
Jev:闭源 System One Model
Decider:Qwen3.5-2B,约 1.9B 参数,Apache 2.0 开源
2、价格
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
• 40-400xShow more
I built a trading bot with Jev!
Jev decides if it should "buy" or "sell", given the price feed of an asset pair, and executes real trades.
It uses Monad to place the orders on Kuru's on-chain order book in every 300ms block.
Demo link → jev-trader.vercel.app
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
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 StagehandShow more
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
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.)
Diogo Almeida
@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