HR & RECRUITING
Real-Time PTO Request Burnout-Context Enricher
When a leave request webhook arrives, looks up the requester's recent usage and balance in BigQuery and posts the approving manager a Slack message with burnout context.
How it runs
The automated pipeline, trigger to output.
- TriggerLeave request webhook receivedHTTP webhook
- ActionLook up requester balance and usage in BigQueryBigQuery
- LogicClassify request as routine or overdue and pick recommendation
- ActionAssemble burnout-context approval card
- OutputSlack the enriched request to the approving managerSlack
What it does
This workflow reacts the moment an employee submits a PTO request. It enriches the raw request with the person's recent leave history and current balance, then gives the approving manager an at-a-glance read on whether this employee is well-rested or overdue, nudging toward approval when the data shows a long stretch without time off.
When to use it
Use this when approvals happen ad hoc and managers lack context at decision time. Surfacing burnout signals inside the approval moment helps prevent reflexive denials of leave for employees who most need the break.
How it works
- 1An incoming webhook fires when a new leave request is submitted.
- 2BigQuery is queried for the requester's balance and trailing 90-day usage.
- 3A logic step classifies the request as routine or overdue based on time since last leave and balance size, and picks the recommendation text.
- 4The workflow assembles a context card with dates, balance, usage trend, and the recommendation.
- 5A Slack message delivers the enriched request to the approving manager as the output.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect BigQueryDatasets, queries, schemas.
- 3Connect SlackChannels, DMs, threads, mentions.
- 4Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 5Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 6Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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