when a designer gets access to Jev
Awesome Jev Skills
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.
- Category
- Tools & Integrations
- Published by
- Community
- Author
- wuyoscar
- Added
- 2026-09-22
Tagscommunitypythonskillsagentscoding-agent
Highlights
- Bundles 57 projects and resources, 5 skills, 108 scenarios, and 14 recorded input and output pairs.
- The default install route needs no Vercel account and no Node or npm; the agent installs into the current project and verifies offline.
- Published v0.2.0 still has 11 entry points while the five-entry collection is a source preview, so upgrade names change.
- Evals are published with negatives: 12 before-and-after pairs came out 12/12 baseline versus 10/12 for the fixed checkpoint.
- A calibration pilot matched 136 of 160 benchmark labels, but the confidence 0.9 and above group still contained 8 errors per 100.
Watch out
MIT-licensed, with linked projects keeping their own licenses. Needs a coding agent and a TypeSafe key for live calls; listed projects are not installed or tested by the collection.
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From the community
Posts from builders shipping with Jev right now.
When a designer gets Jev
Full Jev video tutorial
Full Jev Tutorial What it is, how you can build with it and what new applications it can unlock → 0:00 Intro → 0:34 Jev explained → 4:06 API setup → 5:59 Demo 1: Voice-controlled browser → 11:33 Demo 2: AI memory → 17:27 Demo 3: YouTube predictor
The case against Jev-scored compaction
This is a terrible compaction strategy that fundamentally doesn't understand how compaction and context management work. Seems like a lot of people are confused so let's break this down. 1. Compaction isn't a filter The role of compaction is to clean up history to keep the Show more
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
Classifying rows in DuckDB
I made a DuckDB extension where you can use @typesafeai 's Jev to do quick classification of rows in any csv/parquet file or duckdb table about 10sec for 1k rows ~ better than using an LLM, way more ergonomic than a classifier game-changing for data analysis!
A playable 16-judgment demo
typesafe's jev is fun! live demo you can play with: typesafe-demo.val.run
AI multiple choice, not essay writing
WTF is Jev by @typesafeai? Here’s the tl;dr ELI5: Think AI multiple choice, not AI essay writing. It doesn’t chat. It makes decisions your software can act on: “Spam or not?” “Which tool should this agent use?” “Does this need a human?” The exciting part: roughly 200x faster Show more