DATA OPS

Auto-Archive Stale Dashboards After Owner Silence

When a dashboard's keep/archive decision deadline passes in Notion with no owner response, this flow auto-archives the dashboard via API, logs the action.

CategoryData Ops
Enginesim
Difficultyadvanced
Triggerschedule
Steps6
Setup~25 min

How it runs

The automated pipeline, trigger to output.

  • TriggerDaily schedule checks for overdue decisions
  • ActionQuery Notion for Pending rows past the archive-by dateNotionNotion
  • LogicSkip any row flipped to Keep since the deadline
  • ActionCall the BI admin API to archive each dashboardHTTP webhook
  • ActionSet the Notion row to ArchivedNotionNotion
  • OutputDM the owner on Slack with restore instructionsSlack

What it does

Closes the loop on the decommission process. It watches the Notion decommission register for rows whose archive-by deadline has passed while still marked Pending, then calls the BI platform's admin API to actually archive (not delete) those dashboards. The dashboard's metadata is preserved so it can be restored, the Notion row is moved to Archived, and the owner gets a courtesy heads-up.

When to use it

Use this as the enforcement stage after a register-building sweep. It prevents the common failure mode where owners ignore the decision request and stale dashboards linger forever — silence becomes a safe, reversible archive rather than indefinite limbo.

How it works

  1. 1A daily schedule checks for overdue decisions.
  2. 2Notion returns register rows that are Pending and past their archive-by date.
  3. 3A guard skips any row whose status changed to Keep in the meantime.
  4. 4The BI admin endpoint is called over an HTTP webhook to archive each dashboard.
  5. 5The Notion row is set to Archived and the owner is DMed on Slack with the restore instructions.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect NotionPages, databases, comments.
  2. 2
    Connect HTTP webhookTrigger any URL on agent actions.
  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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