FINANCE
GL Anomaly Explanation Router
Takes flagged GL anomalies, looks up each account's responsible owner, and creates a tracked explanation task on a Monday board with a due date tied to the close calendar…
How it runs
The automated pipeline, trigger to output.
- TriggerWebhook receives flagged anomaly batchHTTP webhook
- ActionResolve account owner + cost center from SnowflakeSnowflake
- LogicSplit new anomalies from already-tracked ones
- ActionCreate Monday explanation items for new anomaliesmonday.com
- ActionUpdate existing Monday items with latest variancemonday.com
- OutputPost routing summary to close-status SlackSlack
What it does
This workflow turns a list of flagged anomalies into accountable work. For each anomaly it resolves the account owner from a mapping table, then opens a Monday item that captures the account, the variance amount, and a required explanation field, with a due date set ahead of the lock deadline. Items that already exist for the same account and period are updated rather than duplicated.
When to use it
Use it right after your variance scan produces flags. It is for controllers who need an auditable trail showing who explained each unusual movement and when, instead of chasing explanations over email.
How it works
- 1A webhook receives the batch of flagged anomalies from the upstream scan.
- 2A Snowflake lookup maps each GL account to its responsible owner and cost center.
- 3A logic step splits new anomalies from ones already tracked for the current period.
- 4New anomalies create Monday items with owner, variance, and a blank required explanation field.
- 5Existing items are updated in Monday with the latest variance figure.
- 6A confirmation summary is posted to the close-status Slack channel.
Set it up
What you configure once, before turning it on.
- 1Connect HTTP webhookTrigger any URL on agent actions.
- 2Connect SnowflakeWarehouses, queries, shares.
- 3Connect monday.comVisual work management for teams.
- 4Connect SlackChannels, DMs, threads, mentions.
- 5Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
- 6Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
- 7Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.
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This workflow drops into a full company template. Import the org, and this is one of the playbooks its agents run.
Run this workflow in your colony.
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