AI AGENTS

ClickUp Duplicate Task Detector and Merge Proposer

Scans an entire ClickUp list for semantically duplicate tasks using embeddings, groups the near-matches.

CategoryAI Agents
Enginepaperclip
Difficultyadvanced
Triggermanual
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerOperator starts a de-dup pass
  • ActionPull all open tasks from ClickUp listClickUpClickUp
  • ActionEmbed task titles and descriptionsOpenAI
  • LogicCluster near-duplicate tasks, drop singletons
  • ActionDraft canonical merge proposal per clusterOpenAI
  • OutputPost merge proposals to Slack for approvalSlack

What it does

Finds tasks that say the same thing in different words — the classic "three cards for one feature" problem. It embeds every open task, clusters the ones that are semantically close, and proposes a canonical survivor plus the duplicates to fold into it. Nothing is closed automatically; a human approves each merge from Slack.

When to use it

Use it after a busy quarter or a team merge, when the same work has been filed multiple times by different people and the backlog count is misleadingly high. Best when you want de-duplication but not autonomous deletion.

How it works

  1. 1Triggered manually when you want a de-dup pass.
  2. 2The agent pulls all open tasks from the target ClickUp list.
  3. 3An LLM generates embeddings for each task title and description.
  4. 4A clustering step groups tasks above a similarity threshold.
  5. 5A branch drops singletons and keeps only real duplicate clusters.
  6. 6For each cluster the agent picks a canonical task and drafts a merge proposal.
  7. 7Proposals post to Slack with approve and reject actions for an owner to confirm.

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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