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Use when the user asks to "analyze influencer campaign performance", "compare influencers", or "find what content worked"; produces metric scorecards vs target and benchmark, platform/influencer/content rankings, engagement-quality and sentiment reads, conversion-attribution breakdowns, and ranked learnings. Not for dollar-level return math — use roi-calculator.
Passed 12 of 22 test cases with the skill, and 3 of 22 without it.
and 11 more in the full report
10 fixed2 passed either way9 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
When generating structured quality scores for content and campaign dimensions, what framework should be applied for scope scoring?
| Checked | Without skill | With skill |
|---|---|---|
| Applies C3 scoring architecture for dimension evaluation | Missed | Passed |
The instructions your model reads when the skill loads.
Analyze influencer campaign performance past surface metrics — score results vs target/benchmark, rank platforms/creators/content, read engagement quality and sentiment, attribute conversions, and write ranked learnings.
Cross-discipline (paid ads): this is also the cross-channel paid-ads scorecard/anomaly lens — account-wide metric rollups vs target/benchmark that feed ad-test-designer (what to test) and paid-measurement-loop (what to read back). Save paid runs under
memory/ad/performance-analyzer/.
Analyze performance of [campaign name] influencer campaign
Compare creators within one campaign:
Compare performance of these influencers from [campaign]: @handle1, @handle2, @handle3
memory/creators/<handle-slug>.md (creator-registry roster records) when present.memory/influencer/performance-analyzer/YYYY-MM-DD-<campaign>.md covering core-metric scorecards, platform/influencer/content rankings, engagement-quality and sentiment reads, conversion attribution, and ranked learnings.memory/hot-cache.md.Emit the standard shape from skill-contract.md §Handoff Summary Format.
This family needs no live integrations (Tier 1). The skill runs entirely on inputs you provide — paste platform exports, influencer report screenshots, GA numbers, and promo-code redemption counts, and it builds the full analysis. Ask the user for whatever is missing rather than blocking.
Where a connector could speed the work, the skill marks it with a ~~ placeholder:
~~social platform analytics — native reach/engagement/video metrics per post.test cases passed, vs 3 / 22 without
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