Type a ticket key (e.g. GEBR-6000) and press Look up. The app fetches the issue through the edvardas_jira_lookup flow and shows the summary, status, priority, assignee, reporter, project, dates, description and comments.

Translation

• The app guesses if a ticket looks non-English and shows a badge.
• Hit 🌐 Translate to English to translate summary, description and comments via the edvardas_translations flow.
• Tick Auto-translate to do it automatically on every non-English lookup.

AI summary

Hit 🧠 Summarize on any ticket for an AI TL;DR — a short overview, key points and action items. It reads the summary, description and comments and (for long tickets) summarizes in parts, then combines. Uses the same edvardas_translations (Anthropic) flow.

Recently looked up

The last 10 keys you opened are saved in your browser with the time you opened them. Click any to reopen it. Use Clear to wipe the list.

Project overview

The 📊 Project tab combines a feed and a dashboard. Pick a project (searchable picker filled live from Jira via edvardas_jira_projects — every project the token can access; falls back to GEBR/SUP) and choose how many tickets (10–100). The left column lists the latest tickets (click one to open it in Lookup); the right shows a live breakdown — totals (open / done / aging) and bar charts by status, priority, type and top assignees, aggregated in the browser.

Release notes

On the 📊 Project tab hit 📝 Release notes →. The picker loads the project's real workflow statuses via edvardas_jira_statuses (falls back to statuses seen in recent tickets) and defaults to Done + Client ok for release. Choose statuses and a period, then Generate: a by-status fetch through edvardas_jira_released pulls every matching ticket (not just the recent ones), and the AI writes grouped notes (✨ Features / 🔧 Improvements / 🐛 Fixes / 🧹 Other). When more than one status is selected each ticket is tagged with its status; ticket keys are Jira links, and Copy puts rich HTML on the clipboard so it pastes formatted into Teams.

Setup (once)

• 1Create the Eneqto Flows: edvardas_jira_lookup (single ticket), edvardas_translations (AI translate), edvardas_jira_recent (project feed), edvardas_jira_released (release-notes by-status fetch), and optional edvardas_jira_projects (project list) + edvardas_jira_statuses (workflow statuses).
• 2Open ⚙️ Settings and enter the slugs — the defaults already match those names.
• 3Done — everything runs client-side against those flows.

Flow call format

Every call is GET {base}/{slug}/1?authorization={token} with query params — a POST body never reaches the flow input, so everything goes in the query string:

• Lookup — &key=GEBR-6000
• Translate — &prompt=…
• Project feed / dashboard — &project=GEBR&maxResults=10
• Release notes — &jql=… (full JQL built client-side)
• Project statuses — &key=GEBR
• Projects list — no params

This app was built for the Eneqto Summer Hackathon. The goal: look up any Jira ticket in seconds, and — because our tickets come in several languages — translate non-English tickets to English so the whole team can read them.

How it's built

• A single static page (HTML + JS), no backend of its own.
• It talks to Eneqto Flows for anything secret: a edvardas_jira_lookup flow calls the Jira REST API, a edvardas_translations flow calls an AI model. Keys never touch the browser.
• Config (base URL + token) lives in proxy.js next to index.html.
• Packaged as a ZIP with index.html in the root, then deployed to eneqto.ai.

The full platform guide (build → connect → deploy → Data)

The original Eneqto handleiding, embedded below: