Ops heat 1 · Quiet★ 0heat incomplete (no X)

Jev Inbox Triage

Experiment that reads each customer email of a small online store once with eight parallel Jev questions (a topic Choice, urgency and mood Scores, five risk Nouls), then plain rules send it to Human now, Human queue, Automated or Archived.

What it is

A quiet first reader for a store inbox.

What it does: Each email goes to Jev once with eight questions answered in parallel: topic, how soon a reply is needed, how the sender feels, and five risk checks (health or safety, chargeback or legal, public complaint, refund request, sales pitch). Rules in code then pick a lane. Risk flags trigger early, a pitch must be clear before it is archived, and anything the model is unsure about goes to a person.

Why it belongs in the showcase: A worked example of asymmetric thresholds, with the misses and near-misses written up next to the results.

Caveats: Test inbox of 20 emails; n8n flow not yet run live.

Evidence

Public MIT README; author-recorded run on 2026-10-06 with `jev-1.13.0`, raw output in `results/raw.json`: 19 of 20 test emails in the right lane, 0 urgent or risky emails sent to automation, median 338 ms per email, about 1,000 input tokens per email, about 2.5 US cents for 600 emails a month; safety rules run first and unsure answers go to a person; thresholds were set before the run; a shadow-mode n8n workflow is included.

Caveats

  • The 20 emails are a test inbox written for the experiment, not a live store
  • The n8n workflow has not yet been run inside a live n8n instance
  • On a real inbox, customer emails go to TypeSafe; check the data terms and the store's privacy policy first

Unofficial case page. Stars / list position observed for heat; do not treat heat as a quality SLA. Review the upstream README before you depend on it.