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Find Key Opinion Leaders (KOLs) in a given domain by combining web research with LinkedIn post search. Given a company/idea and target domain, generates authority keywords, searches LinkedIn posts to find prolific authors with high engagement, and merges with web-researched influencers.
Passed 18 of 22 test cases with the skill, and 6 of 22 without it.
and 14 more in the full report
13 fixed7 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which Apify actor is used under the hood by the discovery pipeline to fetch LinkedIn post search results without cookie authentication?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies apimaestro/linkedin-posts-search-scraper-no-cookies as the search actor. | Missed | Passed |
The instructions your model reads when the skill loads.
Find Key Opinion Leaders in any domain by searching LinkedIn posts for prolific, high-engagement authors and merging with web-researched influencers.
Core principle: Search for authority/thought-leadership keywords, not pain-language. We want people who shape conversation in the space — conference speakers, newsletter writers, podcast hosts, and prolific LinkedIn posters.
Ask the user these questions:
Based on intake, generate 15-25 topic/authority keywords. These are NOT pain-language — they're the terms thought leaders use when sharing expertise:
Also generate:
Present keywords to user for approval before running.
Save config in the current working directory or wherever the user prefers:
Config JSON structure:
{
"client_name": "example",
test cases passed, vs 6 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.