MGID Creative Fatigue Detector

Detects teaser fatigue via period-over-period stats. Rules live here.

Tools: tool reference
Assumptions: threshold assumptions

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Required inputs

Input	Required	Default
Campaign ID(s)	Yes	simulator scope list, user ids, or named campaigns when run standalone
Current period	Yes	last 7 days
Baseline period	Yes	prior 7 days (days 8–14)
Target CPA	No	from campaign stats or user

Campaign type gate

Only content, product and push campaigns have teasers. Skip search_feed and newsletter and say so in the output — see the campaign-type table in tool reference. On push, widget-level signals are absent, so rely on teaser-level CTR/CPA only.

Refresh recommendations name what to replace, never the replacement copy. New headlines and images come from MGID's own creative generation, not from the agent.

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MCP tools

Tool	Purpose
run_custom_report	Primary — all teasers + metrics in one call per campaign (requires customReports grant)
list_teasers	Active teaser count + status guardrail (no metrics)
get_teaser	Config, moderation status
get_teaser_statistics	Fallback — per teaser when custom report unavailable
get_campaign_statistics	Campaign avg CTR/CPA for signal #2 and #5

Bulk stats via custom report

One run_custom_report per campaign beats N× get_teaser_statistics. Use dimension teaserId, filter by filters.campaigns, and the same date windows as other signal skills.

ads-mcp implementation: run_custom_report calls the v2 statistics reports endpoint, which accepts filters.dateRange only — no dateRangePrevious. There is no comparison mode through ads-mcp today.

Period-over-period: run two reports per campaign — current window and baseline window — and join rows on teaserId. Still 2 calls/campaign, not one per teaser.

Example params (current 7d, top spenders first):

{
  "dimensions": ["teaserId"],
  "metrics": ["clicks", "spent", "ctr", "conversionsBuy", "conversionsCostBuy"],
  "filters": {
    "campaigns": [12061865],
    "dateRange": {
      "dateFrom": "2026-06-30T00:00:00.000+03:00",
      "dateTo": "2026-07-06T23:59:59.999+03:00"
    }
  },
  "orders": { "spent": "desc" },
  "limit": 100
}

Repeat with dateRange set to the prior 7d for baseline metrics.

Paginate with offset when meta.total > limit. Skip teasers with zero current spend unless list_teasers shows them as active and recently launched.

Grant missing: fall back to get_teaser_statistics per teaser; cap at 20 teasers (prior-spend order from a single-period custom report is unavailable — use list_teasers + campaign stats to pick candidates).

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Minimum data (ASSUMPTION)

Per teaser, in current period:

• clicks ≥ 100, OR
• impressions ≥ 1,000 (if returned by statistics tool)

Skip non-active teasers. Count active teasers — never pause if only one remains.

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Fatigue signals (ASSUMPTION)

Compare current 7d vs prior 7d only (no day-over-day — too noisy on native):

1. CTR drop ≥ 30% with min clicks
2. CPA increase ≥ 50% vs campaign avg with ≥ 5 conversions
3. CVR drop ≥ 35% vs baseline with ≥ 200 clicks
4. Spend ≥ $30, conversionsBuy = 0, clicks ≥ 150
5. Teaser CPA > 2× best active teaser (both ≥ 5 conversions)

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Recommendations

• pause_teaser when fatigue + ≥ 2 other active teasers
• launch_teaser_variant — guidance only; no create/moderation MCP tools yet
• Rejected teasers: explain via get_teaser; user fixes in UI — no send_to_moderation tool

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Impact (ASSUMPTION)

spend_removed = teaser_spend_7d / 7
recovery_rate = 0.3 to 0.7  (sibling absorption)
net_spend_delta = -spend_removed × (1 - recovery_rate)

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Apply

set_teaser_status (write scope).

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Output

Chat: table of teasers to pause/monitor.

Return: Recommendation[].