TICKET MANAGEMENT

Detect duplicate ClickUp tasks across spaces and post a merge proposal

Scans all ClickUp spaces on a schedule, uses an LLM to cluster near-duplicate tasks by title and description similarity.

CategoryTicket Management
Enginesim
Difficultyintermediate
Triggerschedule
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule fires
  • ActionFetch open tasks across all ClickUp spacesClickUpClickUp
  • ActionCluster near-duplicate tasks with an LLMOpenAI
  • LogicDrop single-member clusters, rank by confidence
  • OutputPost ranked merge proposal to SlackSlack

What it does

Finds the same work tracked twice across different ClickUp spaces. It pulls open tasks from every space, asks an LLM to group near-duplicates (accounting for reworded titles and shared context), and delivers a Slack proposal that names a canonical keeper and the tasks to fold into it — without touching ClickUp until a human says yes.

When to use it

Run it weekly when multiple teams file tickets in their own spaces and the same bug or feature ends up logged three times. It surfaces the overlap before sprint planning so you dedupe deliberately instead of discovering it mid-standup.

How it works

  1. 1A weekly schedule fires the run.
  2. 2ClickUp returns all open tasks across every accessible space.
  3. 3An OpenAI step embeds and clusters tasks, flagging pairs above a similarity threshold and picking the oldest or most-detailed as the canonical keeper.
  4. 4A logic step drops clusters with only one member and ranks the rest by confidence.
  5. 5Slack receives a proposal card per cluster — keeper, duplicates, and a one-line rationale — for an operator to approve.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ClickUpDocs + tasks + chats in one workspace.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect SlackChannels, DMs, threads, mentions.
  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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