TICKET MANAGEMENT

Auto-raise Linear priority when a deduplicated bug crosses a report threshold

Each new Intercom report of a known bug increments its Linear issue count, and when the count crosses configured thresholds the issue's priority is bumped and the eng lead is…

CategoryTicket Management
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerIntercom conversation tagged 'bug'IntercomIntercom
  • ActionFingerprint and match/create Linear issueLinearLinear
  • LogicCompare reporter count to thresholds
  • ActionUpdate Linear issue priorityLinearLinear
  • OutputAlert eng lead in Slack on Urgent crossingSlack

What it does

Makes bug priority self-adjusting. A defect that one person reports stays low; the same defect reported by twenty people automatically climbs to Urgent and pulls in the engineering lead. The decision is driven by the live reporter count, not by who shouts loudest.

When to use it

Use it when you already dedup bugs into Linear and want impact to drive prioritization instead of manual gut calls. Ideal for teams that want a defensible, count-based escalation policy.

How it works

  1. 1An Intercom conversation tagged `bug` fires the trigger.
  2. 2OpenAI normalizes the report to a fingerprint and the flow finds (or creates) the matching Linear issue, incrementing its reporter count.
  3. 3A logic step compares the new count against thresholds: 5 reports moves the issue to High, 15 moves it to Urgent.
  4. 4If a threshold was just crossed, the flow updates the Linear issue priority.
  5. 5On an Urgent crossing it posts a Slack alert to the engineering channel naming the issue, count, and last reporter so the lead can react immediately.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect IntercomConversations, contacts, articles.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect LinearIssues, projects, cycles, triage.
  4. 4
    Connect SlackChannels, DMs, threads, mentions.
  5. 5
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  6. 6
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  7. 7
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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