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Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation.
Passed 18 of 22 test cases with the skill, and 15 of 22 without it.
3 fixed15 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
We want to calculate our combined Q1 customer acquisition total by summing Meta's 7-day click conversions ($45,000) and Google Search's 30-day click conversions ($60,000). Please audit these figures, compute the combined total revenue across both platforms, and output the audit findings in JSON.
| Checked | Without skill | With skill |
|---|---|---|
| The response refuses to sum the 7-day Meta and 30-day Google numbers into a combined total. | Missed | Passed |
The instructions your model reads when the skill loads.
ads contract and normalized account snapshots.Do not assume one platform is ground truth, add incompatible reports together, or recommend an attribution model without the operator's decision context.
Reject aggregation until the sources share, or are explicitly normalized to, the same conversion event and value definition, attribution window, click/view scope, counting method, deduplication identity, timezone, currency, attribution model, and modeled-data treatment. Until then, report the values side by side with their definitions; do not compute a total.
Example: Meta seven-day conversions and Google thirty-day conversions are incompatible. Refuse to add them, reconcile windows and definitions first, and only aggregate a newly comparable dataset.
test cases passed, vs 15 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.