CUSTOMER SUPPORT

Agent that triages Intercom tickets and files confirmed bugs to Linear

A Paperclip agent reads each Intercom conversation, tags it, suggests a macro for routine issues.

CategoryCustomer Support
Enginepaperclip
Difficultyadvanced
Triggerevent
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew or updated Intercom conversationIntercomIntercom
  • ActionAgent reads thread and classifies request vs bugOpenAI
  • LogicBranch: routine request or confirmed bug
  • ActionTag and suggest macro in Intercom (routine path)IntercomIntercom
  • ActionCreate structured Linear issue (bug path)LinearLinear
  • OutputLink Linear issue back to Intercom and notify SlackSlack

What it does

This agentic workflow goes beyond tagging. For routine questions it tags the Intercom conversation and recommends a macro. When it determines the report is an actual product bug, it extracts reproduction steps, severity, and affected area, opens a structured Linear issue, and links that issue back into the Intercom conversation so support and engineering stay connected.

When to use it

Use this when support is the front door for bug reports and handoffs to engineering are inconsistent or lossy. It keeps triage and escalation in one motion so customers get acknowledged and engineers get an actionable ticket.

How it works

  1. 1A new or updated Intercom conversation triggers the agent.
  2. 2The agent reads the thread and decides whether it is a routine request or a bug.
  3. 3A logic branch splits routine versus bug handling.
  4. 4For routine items, an action tags the conversation and suggests a macro in Intercom.
  5. 5For bugs, an action creates a Linear issue with extracted repro steps and severity.
  6. 6The output posts the Linear link back onto the Intercom conversation and notifies the team in Slack.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect IntercomConversations, contacts, articles.
  2. 2
    Connect LinearIssues, projects, cycles, triage.
  3. 3
    Connect OpenAIModels, embeddings, files.
  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.

Run this workflow in your colony.

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