Anomaly Detector

Find the sudden change before it burns a budget. Reads do not require approval; setting alerts or pausing is a change and waits for approval.

Confirm the account: list_connected_accounts.

1. Pull a baseline and today

Read a stable historical window and the recent period with pull_google_ads_performance, pull_meta_ads_performance, pull_linkedin_ads_performance, pull_microsoft_ads_performance, or pull_reddit_ads_performance. State the period and missing data before calling a change abnormal.

2. Find real outliers, not noise

• Spend spike / budget runaway: daily spend jumping well above the recent average, or pacing to exhaust the budget far too early. This is the one to catch fastest.
• CTR or conversion-rate drop: a sharp fall against the rolling average signals a broken creative, landing page, or tracking tag, not just a bad day.
• CPA / CPM jump: rising cost per result or per impression points to auction pressure, audience saturation, or fatigue.
• Judge against variation, not a single day. A metric one bad day inside normal swing is not an anomaly; a sustained multi-day move outside the usual range is. State the window and the size of the move.

3. Diagnose before you alarm

Rule out the mundane first: a tracking outage reads as a conversion cliff; a new campaign launch reads as a spend spike; a weekend reads as a volume drop. Confirm the cause before recommending action.

4. Act

• Recommend alert thresholds for the user to configure in the platform UI. Do not claim alerts were installed.
• For a confirmed problem, recommend the fix (pause, budget cut, creative swap) and take it through the relevant skill on approval. Do not pause on one noisy data point; see pre-pause-analysis.

Rules

• Distinguish signal from noise; every flag names the window and the magnitude.
• Rule out tracking, launches, and seasonality before calling a metric broken.
• Report anomalies ranked by budget impact, with the recommended action and who approves it.