Jev Integration Guide

Sep 20

This project provides instructions on how to set up and utilize Jev, an independent index, by integrating it with TypeSafe and Claude Code or plugins to handle small decision-making processes within agent workflows.

Pattern✦ JEV Agent Integration Skills

If you want to try Jev and have no idea where to start, this is basically what I did. 1. Get access from TypeSafe: typesafe.ai 2. Install the skill so Claude Code knows how to use it: npx skills add typesafe-ai/skills --skill typesafe-ai If you’re using the Claude plugin instead: claude plugin marketplace add typesafe-ai/skills claude plugin install typesafe@typesafe-ai 3. Create an API key from the TypeSafe dashboard and you’re pretty much ready. The fun part is figuring out where to actually use it. Don’t go into your code and replace every GPT call with Jev. That’s not really the point. Look for all those tiny decisions your agent is making. “Should I search again?” “Which tool should I call?” “Is this result useful?” “Does this need a human?” “Should I keep this piece of content?” “Is this lead worth following up on?” These are the calls I’d experiment with first. For example, if you’re building a research agent, you could have Jev look at 10 search results and simply decide which ones are worth sending to your main LLM. Or for a content agent: Jev: Is this idea worth writing about? → yes Jev: Which format? → thread Jev: Which audience? → designers Then your actual LLM does the writing. That’s the bit that clicked for me. You don’t really want Jev to be your “smartest model”. You want it sitting in all the boring little decision points around your smarter models. I’ve started experimenting with this on content workflows. Will share what I find once I have something interesting. Because honestly, that’s probably a more useful test than another benchmark screenshot.

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