AI for Customer SupportIntermediate15 minutesCustomer SupportClickUpBug reports

Auto create bug tickets in ClickUp from a Customerly conversation

Stop swivel chairing. Fire one Flow and Aura collects reproduction steps, summarizes the bug, opens the ClickUp task, and replies in the conversation with the link, before the agent has closed the tab.

The problem

Every bug logged from a customer chat eats five plus minutes of agent time. Copy pasting messages into ClickUp. Chasing missing reproduction steps. Formatting the ticket. Reassigning. The invisible tax that quietly drains support teams all day.

The outcome

The moment a bug is identified, an agent fires the Flow. Aura reads the full conversation, asks the customer for any missing reproduction details, summarizes everything into a clean bug report, creates the ClickUp task, drops the task link back in the Customerly conversation, and assigns it to the dedicated bug team. Zero copy paste. Zero "I'll log this later."

Tools you'll use
AuraFlowAI MissionREST API block

The Flow you'll build

This is the exact Flow as it appears in the Customerly editor. Drag it around, then follow the steps below to build it.

Step by step

  1. 1

    Create a Flow with an on demand trigger

    Flow

    In Customerly, go to AI Studio → Flows → New Flow. Name it Bug → ClickUp. Set the trigger to On Demand so any agent can fire it from inside a conversation.

    On demand triggers add a one click button in the agent inbox. The agent reviews the conversation, decides it's a real bug, and clicks the button. Everything below runs automatically from there.

    textFlow name
    Bug → ClickUp
    
  2. 2

    Add an AI Mission that gathers missing info and summarizes the bug

    AI Mission

    Add an AI Mission step right after the trigger. This is where Aura takes over the conversation, asks the customer for anything missing, and produces a clean bug report.

    Paste the prompt below into the Mission's instructions. Aura will use the full conversation history as context, ask follow up questions if reproduction steps or environment details are missing, then output the structured bug report into the Mission's output variables (so the next step can use them).

    promptAI Mission prompt
    You are a senior support engineer helping the customer report a bug to the engineering team.
    
    Read the full conversation history. Your goal is to produce a clean, structured bug report. Before you write it, check that you have:
    
    1. A one line description of what the customer was trying to do
    2. The exact steps to reproduce the issue
    3. The expected behavior vs. the actual behavior
    4. The customer's environment (browser, device, app version)
    5. A screenshot or screen recording if the bug is visual
    
    If anything from items 1 to 5 is missing, ask the customer for it in one short message. Keep your tone warm, never robotic. When you have everything, stop asking questions.
    
    Output the final bug report in this exact JSON shape and nothing else:
    
    {
      "title": "<10 word bug title>",
      "description": "<one paragraph summary>",
      "reproduction_steps": ["<step 1>", "<step 2>", "..."],
      "expected": "<one sentence>",
      "actual": "<one sentence>",
      "environment": "<browser, OS, app version>",
      "customer_attachments": ["<urls if any>"],
      "severity_guess": "low | medium | high"
    }
    
  3. 3

    Add a REST API block that creates the ClickUp task

    REST API block

    Add a REST API step after the Mission. This will POST the bug report to ClickUp's "Create Task" endpoint. Map the Mission's output JSON into the ClickUp body so the title, description, and reproduction steps land in the right ClickUp fields.

    You'll need:

    • Your ClickUp API token (create one in ClickUp → Settings → Apps)
    • The List ID of the ClickUp list where bugs should land (Settings → Bugs list → "Copy link", the number after /li/ is the ID)
    httpHTTP method + endpoint
    POST https://api.clickup.com/api/v2/list/{LIST_ID}/task
    
    httpRequest headers
    Authorization: pk_XXXXXXXXXXXXXXXXXXXXXX
    Content-Type: application/json
    
    jsonRequest body (uses Mission output variables)
    {
      "name": "{{mission.output.title}}",
      "markdown_description": "**Summary**\n{{mission.output.description}}\n\n**Steps to reproduce**\n{{mission.output.reproduction_steps}}\n\n**Expected**\n{{mission.output.expected}}\n\n**Actual**\n{{mission.output.actual}}\n\n**Environment**\n{{mission.output.environment}}\n\n**Reported by**\n{{contact.email}}\n\n**Conversation**\n{{conversation._url}}",
      "priority": 3,
      "tags": ["bug", "from-customerly"],
      "assignees": [12345678]
    }
    
  4. 4

    Reply in the conversation with the ClickUp task link

    Flow

    Add a final Send Message step. This drops a quick note back into the original Customerly conversation so both the customer and the agent can see the bug was logged, with a direct link to track it.

    Map the REST API step's response into the message template so the ClickUp URL is real, not a placeholder.

    textMessage template
    Thanks for the report. I've logged this with the engineering team and you can follow the fix here:
    {{rest.response.url}}
    
  5. 5

    Test it on a real bug, then turn it loose

    Flow

    Open a real bug conversation in your inbox. Click the Bug → ClickUp button at the top of the conversation. Watch Aura ask for anything missing, generate the report, post it to ClickUp, and reply in the chat with the task URL.

    Once you've run it on three or four real bugs without correcting anything, share the trigger with the rest of the support team. From that day on, your reps don't open ClickUp to log bugs. They just fire the Flow.

FAQ

How does this differ from a Zapier or Make integration?

Zapier and Make trigger on events (new conversation, new message) and run rule based steps. This recipe is on demand, so the agent decides which conversations are bugs. And the AI Mission gathers missing reproduction details from the customer mid Flow, which a no code automation can't do.

Does Aura actually talk to the customer to get missing info?

Yes. The AI Mission step writes messages into the conversation and waits for the customer to reply, just like a human agent would. It only stops asking once all required fields are present, then continues the Flow.

Can I replace ClickUp with Jira, Asana, Linear, or GitHub Issues?

Yes. The Flow shape stays the same. Only the REST API block changes. Swap the endpoint, headers, and body to match the target tool's "create issue" API. The Mission prompt and reply step don't need to change.

Does this only work for bugs?

No. The same pattern (on demand Flow + Mission + REST API + reply) works for any handoff that involves an agent moving information out of Customerly. Common variants are filing feature requests, opening incident tickets, creating CRM leads, and queuing legal review requests.

Ready to ship this recipe in your workspace?

Book a 1:1 demo and we'll build this Flow live in your Customerly account.