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jev-playground

A MoonBit playground for TypeSafe's Jev: a client for GET /v1/models and POST /v1/systemone with noul, choice, and score questions, a single-query CLI, a Jev-vs-Jev gomoku game, and a tool that replays game logs as real-time GIFs.

Category
Repos & SDKs
Published by
Community
Author
mizchi
Added
2026-09-22
Tagscommunitymoonbitcligamessdk

Highlights

  • MoonBit client covers noul, choice, and score questions with typed JSON conversion of requests and responses.
  • In the gomoku game Jev picks each move from neighboring-cell candidates, with WINS/BLOCK and line-length hints like '3o' for open threes.
  • The built-in fallback (win > block > center) runs only when the API fails or a move is illegal, and fallback moves are reported in the stats.
  • gomoku_gif turns a JSONL game log with measured per-move milliseconds into a real-time GIF; the sample is 362x362, 26 frames, about 47 KB.
  • The README notes a 15x15 game costs about 58K input tokens (~$0.0024) at $0.042/MTok, with roughly 0.5 s per move.

Quickstart

bash
export TYPESAFEAI_API_KEY=YOUR_API_KEY
moon update
moon run --target native cmd/jev -- --models
moon run --target native cmd/gomoku -- --board 9 --games 2 --verbose

Watch out

No license file, so reuse terms are unclear; needs the MoonBit toolchain (moon 0.1.20260915+) and an early-access TypeSafe API key, and every move is a billable POST /v1/systemone call.

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From the community

Posts from builders shipping with Jev right now.

Follow @typesafeai

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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