Research top-performing LinkedIn content in your niche and generate a content playbook
Researches top-performing LinkedIn content in your niche by analyzing viral posts, hooks, formats, topics, and engagement patterns. Identifies what resonates with your ICP audience on LinkedIn and produces a structured content playbook with templates, topic clusters, and posting cadence recommendations.
agency.config.json at repo root with services, icp, and outreach sectionsthought-leadership skill for content creation from playbook outputsagency.config.json from the project root.agency.name, agency.founder -- for positioning contextservices[].name, services[].keywords -- content topic seedsicp.segments[].industries, icp.segments[].titles -- audience definitionicp.primary_keywordsicp.secondary_keywordsoutreach.tone -- voice alignment for templatesniche_keywords -- additional topic keywords beyond config (default: use config keywords)influencers -- specific LinkedIn profiles/names to study (default: discover automatically)content_types -- filter: text | carousel | video | poll | article | newsletter (default: all)time_window -- how far back to analyze (default: "past 30 days")max_posts -- max posts to analyze (default: 50)Identify top voices in the niche using WebSearch:
site:linkedin.com/in "{service_keyword}" "followers" "{industry}"site:linkedin.com/posts "{service_keyword}" "likes" OR "comments""top linkedin influencer" "{industry}" OR "{service_keyword}""linkedin creator" "{industry}" "{icp_title}""best linkedin posts" "{service_keyword}" {time_window}{
"name": "Full name",
"profile_url": "LinkedIn URL",
"headline": "Their LinkedIn headline",
"follower_estimate": "Approximate follower count if visible",
"niche": "Their primary topic area",
"relevance_to_icp": "HIGH | MEDIUM | LOW"
}
influencer-finder).For each identified influencer and for niche keywords generally, search for high-performing posts:
site:linkedin.com/posts "{influencer_name}" "{service_keyword}"site:linkedin.com/posts "{service_keyword}" "agree" OR "this" OR "100%" (engagement markers)site:linkedin.com/pulse "{service_keyword}" "{industry}""{influencer_name}" linkedin post "{topic_keyword}"{
"post_url": "URL if available",
"author": "Name",
"hook": "First 2 lines of the post (the scroll-stopper)",
"full_text": "Complete post text (first 500 chars if truncated)",
"format": "text_only | listicle | story | contrarian | how_to | carousel | poll | video | article",
"topic": "Primary topic of the post",
"engagement_signals": "Likes/comments/reposts if visible in search snippet",
"posted_date": "Date if available",
"cta_type": "question | link | dm_me | comment_below | none",
"length": "short (<500 chars) | medium (500-1500) | long (1500+)"
}
Analyze collected posts to identify winning patterns:
Categorize all hooks into types:
Count frequency and estimate engagement per hook type.
For each content format (text, carousel, poll, article, video):
Group posts into topic clusters:
If dates are available:
Based on patterns identified, generate reusable templates:
{
"hook_type": "contrarian",
"template": "Stop [common practice]. Here's what [top performers] do instead:",
"example_filled": "Stop A/B testing your homepage hero. Here's what brands doing 8-figure revenue do instead:",
"when_to_use": "When challenging conventional wisdom in your space",
"engagement_prediction": "HIGH -- contrarian hooks get 2-3x more comments"
}
Generate 20 specific post ideas mapped to:
Return structured playbook:
{
"research_summary": {
"posts_analyzed": 50,
"influencers_studied": 15,
"time_period": "past 30 days",
"platforms": ["LinkedIn"]
},
"top_influencers": [
{
"name": "...",
"profile_url": "...",
"headline": "...",
"follower_estimate": "...",
"niche": "...",
"top_post_hook": "...",
"content_style": "..."
}
],
"hook_analysis": {
"contrarian": { "frequency": 12, "avg_engagement": "high", "examples": [] },
"story_opener": { "frequency": 8, "avg_engagement": "medium", "examples": [] }
},
"format_analysis": {
"text_only": { "count": 25, "avg_engagement": "medium", "best_example": "..." },
"carousel": { "count": 10, "avg_engagement": "high", "best_example": "..." }
},
"topic_clusters": [
{ "topic": "Shopify CRO", "post_count": 8, "engagement": "high", "saturation": "medium" }
],
"templates": [],
"content_calendar": [],
"recommendations": {
"posting_frequency": "3-4x per week",
"best_days": ["Tuesday", "Wednesday", "Thursday"],
"top_formats": ["text_only", "carousel"],
"top_hooks": ["contrarian", "data_lead"],
"topics_to_own": ["...", "..."],
"voice_notes": "Align with agency tone: direct, helpful, zero fluff"
}
}
Present a formatted summary alongside the JSON:
LINKEDIN CONTENT PLAYBOOK
Analyzed: {N} posts from {M} influencers
TOP HOOKS THAT WORK:
1. {hook_type} -- used {N} times, {engagement} engagement
Template: "{template}"
WINNING FORMATS:
1. {format} -- {count} posts, {engagement} avg
TOPIC OPPORTUNITIES:
1. {topic} -- {saturation} saturation, {engagement} potential
CONTENT CALENDAR (Next 20 posts):
1. [{format}] {topic} -- Hook: {hook_type} -- Effort: {level}
...
POSTING CADENCE: {frequency} on {best_days}
Trigger phrases:
User: Research what's working on LinkedIn for Shopify and ecommerce content
Assistant: [reads config, discovers top influencers, collects high-performing posts, analyzes hooks/formats/topics, generates templates and content calendar, presents playbook]
User: Build a LinkedIn playbook focused on CRO content, study these 5 creators: [names]
Assistant: [same flow but focused on CRO keywords, studies specified creators plus discovers additional ones]