TICKET MANAGEMENT

Slack bug-report intake with repro completeness check

Turns a Slack slash-command bug report into a scored ClickUp task, replying in-thread to ask for any missing repro details before the ticket is allowed into the engineering queue.

CategoryTicket Management
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerSlack slash-command bug submissionSlack
  • ActionScore reproducibility and find gapsOpenAI
  • ActionCreate ClickUp task with scoreClickUpClickUp
  • LogicBranch on completeness
  • OutputReply in Slack thread requesting missing detailsSlack

What it does

This lets anyone file a bug from Slack without leaving the conversation. A teammate submits a short form via slash command; the workflow scores it for reproducibility, creates a ClickUp task, and replies in the same Slack thread. If repro steps, expected/actual behavior, or environment are missing, the reply asks for them right there and holds the task out of the engineering queue until the gaps are filled.

When to use it

Use it when bugs get reported in Slack channels and never make it into ClickUp, or arrive too thin to action. It captures reports at the source while still enforcing a quality bar.

How it works

  1. 1A Slack slash-command submission triggers the flow with the reporter's text.
  2. 2OpenAI scores reproducibility and identifies missing fields.
  3. 3The workflow creates a ClickUp task with the score and reporter attached.
  4. 4A logic branch checks completeness.
  5. 5If incomplete, it replies in the Slack thread listing what's missing and parks the task in "awaiting repro".
  6. 6If complete, it confirms in-thread and pushes the task to the engineering queue.

Set it up

What you configure once, before turning it on.

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

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