ブログ — ガイドと開発ノート
Jev を使った開発に関する製品アップデート、開発ノート、実践ガイド。型付きの質問と、コードで分岐できる構造化された回答について解説します。
Open-source projects built on Jev
Hands-on guides to six independent GitHub projects: what each does, how to install it, and how to call Jev with a JevStation API key. We are not affiliated with any of them.

jev-seo
Live SEO audit from one homepage URL: 52 checks, Core Web Vitals and Jev page questions, exported as PDF, XLSX and Markdown.

jev-ultrafast
A browser agent that picks its next click or keystroke with one Jev call over a numbered element table.

jev-review
AI code review for a Git diff or a whole codebase, with risk, severity and routing steps and a local dashboard.

semdecide
Grep for meaning: a CLI that turns typed Jev answers into exit codes for shell scripts and CI.

jev-router
Per-turn model routing for Claude Code and Codex: Jev picks a fast, balanced or strong tier and fails open.

winnow
A Rust parser-combinator library, paired here with Jev: winnow parses the structure, Jev judges the meaning.
These repositories belong to their authors and are unrelated to JevStation.
最新の記事
Cloudflare Clef Tested: Context Cap, Tokens, Cost
We called Clef and Clef-flash on Workers AI ~70 times: at launch they read only ~2,048 state tokens; a 10-07 retest found the cap gone. Costs per call.
Jev のユースケース:System One モデルが下せる 12 の判断
Jev に何ができるのか。チケットのトリアージからツール呼び出しのガードまで、エージェントやパイプラインで Jev が下す 12 の判断を、質問セットと無料のツールページ付きで紹介します。
Jev Benchmarks: Every Independent Test So Far
Is Jev accurate? Every independent Jev test to date, from an AI-control pilot to GLiNER and routing tests, with sample sizes, caveats and vendor claims apart.

Jev as a Judge: What One Yes/No Question Catches
Can a text-free model judge LLM output? One Jev question ranks backdoored code at AUROC 0.976 for ~$0.04 per 1,000 checks. Where it holds, where it breaks.

Jev Alternatives: Clef, GLiNER and LLMs Compared
Five ways to get typed decisions from text: Clef, structured-output LLMs, GLiNER, your own classifier and Jev. Measured accuracy, cost and where each wins.

fast-jev-compaction: Claude Code Context Compaction
fast-jev-compaction is a Claude Code plugin that drops stale tool calls with Jev instead of summarising them. How it works, install steps, and what it keeps.

System One モデルとは何か、そして何ではないのか
System One モデルは生成テキストではなく、型付きの判断とキャリブレーションされた確率を返します。その意味、RLCD と RLHF の違い、そして独立した検証がまだ乏しい点を解説します。

What One Jev Evaluation Costs, Measured
We made 11 real Jev calls across every state size and question count, fitted the token model and measured the cost: $0.000012 to $0.000377 per evaluation.

Building a Harness with Jev
An agent loop is only as fast as its slowest decision. Where Jev, the System One model from TypeSafe, fits: model routing, action gating, escalation.

Jev が答えられる質問の設計:Choice、Score、Noul
Jev の 3 つの質問タイプ Choice、Score、Noul が、コードで分岐できる内容を決めます。それぞれの戻り値と制限、アトミックな質問の書き方、評価基準の磨き方、信頼度によるエージェントの行動制御を解説します。