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Get Started Free →LinkedIn Ads deep analysis for B2B advertising. Evaluates 25 checks across technical setup, audience targeting, creative quality, lead gen forms, and bidding strategy. Includes Thought Leader Ads, ABM, and predictive audiences. Triggers on: "LinkedIn Ads", "B2B ads", "sponsored content", "lead gen forms", "InMail", "LinkedIn campaign", "LinkedIn audit"
.claude/skills/miosa-osa-ads-linkedin/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | 213% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 19% | 0% |
| case-12 | ✗→✓ | ▲ Improved | 14% | 0% |
| case-22 | ✗→✓ | ▲ Improved | 17% | 0% |
| case-23 | ✗→✓ | ▲ Improved | 2% | 0% |
> 25-check audit of LinkedIn Ads accounts with B2B-specific strategy assessment.
bash/ads linkedin
For B2B Enterprise accounts:
| Metric | Pass | Warning | Fail | |--------|------|---------|------| | CTR (Sponsored Content) | >=0.44% | 0.30-0.44% | <0.30% | | CPC (average) | <=$7.00 | $7-10 | >$10.00 | | Lead Gen CVR | >=10% | 5-10% | <5% | | Message frequency | <=1/30 days | 1/15-30 days | >1/15 days | | TLA budget share | >=30% | 15-30% | <15% |
LINKEDIN-ADS-REPORT.md — Full 25-check findings with pass/warning/fail| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 49,200 | 46,586 | -5% | 1 | 1 | 0% | 8,276 | 9,269 | +12% | 0 | 0 | — |
case-02 | fail→fail | 48,104 | 51,599 | +7% | 1 | 1 | 0% | 7,920 | 7,955 | +0% | 0 | 0 | — |
case-03 | fail→pass | 21,604 | 47,238 | +119% | 1 | 1 | 0% | 2,658 | 8,314 | +213% | 0 | 0 | — |
case-04 | pass→pass | 19,963 | 23,322 | +17% | 1 | 1 | 0% | 3,155 | 4,645 | +47% | 0 | 0 | — |
case-05 | pass→pass | 11,619 | 22,288 | +92% | 1 | 1 | 0% | 1,789 | 4,489 | +151% | 0 | 0 | — |
case-06 | pass→pass | 16,803 | 48,671 | +190% | 1 | 1 | 0% | 2,584 | 7,140 | +176% | 0 | 0 | — |
case-07 | pass→pass | 15,573 | 35,802 | +130% | 1 | 1 | 0% | 2,430 | 3,353 | +38% | 0 | 0 | — |
case-08 | pass→pass | 13,245 | 10,617 | -20% | 1 | 1 | 0% | 1,744 | 2,395 | +37% | 0 | 0 | — |
case-09 | fail→pass | 12,699 | 5,770 | -55% | 1 | 1 | 0% | 1,637 | 1,945 | +19% | 0 | 0 | — |
case-10 | pass→pass | 9,880 | 7,307 | -26% | 1 | 1 | 0% | 1,552 | 1,916 | +23% | 0 | 0 | — |
case-11 | pass→pass | 16,134 | 13,443 | -17% | 1 | 1 | 0% | 2,276 | 3,056 | +34% | 0 | 0 | — |
case-12 | fail→pass | 14,611 | 10,697 | -27% | 1 | 1 | 0% | 2,301 | 2,634 | +14% | 0 | 0 | — |
case-13 | pass→pass | 15,856 | 11,341 | -28% | 1 | 1 | 0% | 2,024 | 2,708 | +34% | 0 | 0 | — |
case-14 | pass→pass | 11,596 | 12,569 | +8% | 1 | 1 | 0% | 1,889 | 2,833 | +50% | 0 | 0 | — |
case-15 | pass→pass | 13,730 | 18,872 | +37% | 1 | 1 | 0% | 2,056 | 3,529 | +72% | 0 | 0 | — |
case-16 | pass→pass | 12,019 | 12,426 | +3% | 1 | 1 | 0% | 1,905 | 3,153 | +66% | 0 | 0 | — |
case-17 | pass→pass | 6,190 | 7,515 | +21% | 1 | 1 | 0% | 1,052 | 2,097 | +99% | 0 | 0 | — |
case-18 | pass→pass | 12,461 | 58,513 | +370% | 1 | 1 | 0% | 2,044 | 2,628 | +29% | 0 | 0 | — |
case-19 | pass→pass | 12,677 | 14,251 | +12% | 1 | 1 | 0% | 2,062 | 2,724 | +32% | 0 | 0 | — |
case-20 | pass→pass | 13,885 | 11,915 | -14% | 1 | 1 | 0% | 1,857 | 2,459 | +32% | 0 | 0 | — |
case-21 | pass→pass | 16,229 | 14,544 | -10% | 1 | 1 | 0% | 2,457 | 3,232 | +32% | 0 | 0 | — |
case-22 | fail→pass | 15,450 | 11,671 | -24% | 1 | 1 | 0% | 2,349 | 2,751 | +17% | 0 | 0 | — |
case-23 | fail→pass | 12,379 | 3,028 | -76% | 1 | 1 | 0% | 1,525 | 1,557 | +2% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +22 percentage points is the difference between those two pass rates over the 23 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.