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Diagnose Meta Ads campaign performance using Meta's actual system mechanics — Breakdown Effect, Learning Phase, Auction Overlap, Pacing, and Creative Fatigue — and produce structured, testable recommendations that avoid judging segments by average CPA instead of marginal efficiency.
Passed 21 of 25 test cases with the skill, and 14 of 25 without it.
and 5 more in the full report
7 fixed14 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
This benchmark measured an earlier version of the skill.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
When presenting reach metrics from Meta Ads Manager in a performance report, how should raw `reach` be displayed?
| Checked | Without skill | With skill |
|---|---|---|
| Displays the reach metric as Reach (Accounts Center accounts). | Missed | Passed |
The instructions your model reads when the skill loads.
Most "Meta Ads analysis" stops at "this CPA is high, pause it." That's wrong more often than it's right. Meta's delivery system optimizes for marginal efficiency — the cost of the next conversion — not average efficiency across a snapshot. A segment with a higher average CPA is often the one keeping your overall campaign cheap. Pausing it makes things worse.
This skill diagnoses Meta campaigns the way a senior media buyer would: at the right evaluation level, accounting for learning state, separating noise from signal, and explaining why the system is making the decisions it's making before recommending any change. It can also audit whether the account supports the complete customer journey without assuming that TOF, MOF, and BOF must be separate campaigns.
Core principle: Holistic first, then drill down. Marginal over average. Customer-journey coverage over rigid funnel structure. Dynamic over static. Every recommendation is a testable hypothesis with expected impact, not a directive.
For account audits, full-funnel reviews, or questions about what is missing, read and apply references/customer-journey-coverage.md before analyzing the account.
test cases passed, vs 14 / 25 without
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