Seven-step guide to wiring Jev into a Grok Bot
A walkthrough for adding Jev decision routing to a Grok Bot: create an API key, put Jev behind LiteLLM on /v1/decisions, run in shadow mode, then switch to active.
Jev is truly the "Internet" moment for the AI industry It tells your agents and LLMs what to do next, in milliseconds and at almost zero cost If you set it up correctly, you will have the AI engineer’s stack for 2028 Here's how to add it to your Grok Bot: step 1 → create an API key at http://docs.typesafe.ai. Keep it in your environment, never in a chat. step 2 → put Jev behind LiteLLM first. It’s a pass-through endpoint on /v1/decisions and /v1/systemone, not /chat/completions. step 3 → install the router. export TYPESAFE_API_KEY=... git clone https://github.com/Bodila51/grok-bot-jev cd grok-bot-jev && python3 -m venv .venv .venv/bin/pip install -r requirements.txt cp config.example.yaml config.yaml step 4 → copy skill/jev-usage-router.SKILL.md into a Grok Bot skill. step 5 → set mode: shadow in config.yaml. Jev logs verdicts, the bot keeps working as before. step 6 → run .venv/bin/python scripts/dry_run.py on your own backlog. Read every row. step 7 → set mode: active once you agree with the log. Kill switches: enabled: false, or bypass jev in the request. Actions Jev returns: reuse_cache, stop_retry, run_deterministic, chat_only, research_capped, allow_subagent, ask_human. It's not so hard. Do it today, then read the full article on Grok Bot below ↓ ↓
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