That’s the standard I hold everything on this page to. Below is the proof, real LinkedIn audits showing exactly how I think, then the tools, GPTs, and partners I actually use to help friends like you get there.
My personal briefing prompt for tracking which AI models are actually best at what, this week, evidence-based, not hype. Open it, copy it, run it yourself.
Two real LinkedIn posts from friends in this world, audited and rewritten using the same method behind everything else on this page.
Overall Score: 74/100. A genuinely strong post with real credibility and a powerful reframe, the engagement (76 reactions, 12 comments, 4 reposts) confirms it resonates. Six structural gaps were holding it back from elite-tier performance.
Scoring: Hook Strength 21/25 · Credibility 13/15 · Story & Emotion 16/20 · Insight Delivery 12/15 · Call to Action 6/15 · Format 6/10 · Total 74/100
The biggest gap: Call to Action lost 9 of 15 points. The original CTA, “What pattern do you keep seeing but not addressing?”, invites comments but offers no next step toward working with Christine: no offer, no DM invitation, no link.
Top fixes to reach 96/100:
Projected score after enhancements: 96/100.
Overall Score: 56/100. Genuine warmth and exceptional social proof (the comments read like a who’s-who: a former CIA Chief Wellbeing Officer, a Northwestern professor, an AI company founder), but the post itself dramatically underperforms what Greg actually had to work with. (The original page displayed 61/100 here; the six criterion scores below actually sum to 56, flagging that for you to confirm which number is right.)
Scoring: Hook Strength 12/25 · Credibility 8/15 · Story & Emotion 13/20 · Insight Delivery 9/15 · Call to Action 4/15 · Format 10/10 · Total 56/100
The biggest gap: the hook. “What happens when you bring strangers, friends, and colleagues together?” is a rhetorical question that cost 13 of 25 points, zero tension, zero specificity, answerable without reading further. Greg had a room of 22 people, a named event, and a quote that moved people. He led with none of it.
Top fixes to reach 96/100:
Projected score after enhancements: 96/100.
Both audits above were produced by the same prompt, refined using Rick’s own “PVES Quick Wrapper” method for turning a vague AI request into one that reliably produces elite output.
The original ask (“score it, explain the scoring, enhance it to 95+”) had six real gaps: no defined scoring rubric, no audience or CTA goal, no output format, no constraints on what NOT to change, no voice anchor, and an undefined “95+” target.
The rewritten prompt adds:
This is the same discipline behind every tool on this page, a vague request produces a mediocre answer; a well-engineered prompt is what actually produces work this specific.
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