Headline Analyzer
Score a headline for clarity, curiosity, and attention potential — then get 3-5 improved versions.
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What is Headline Analyzer?
Scores a headline across 7 dimensions — clarity, curiosity, emotional impact, specificity, readability, audience relevance, and attention potential — into one AI Headline Score, then returns 3-5 improved versions in the same pass.
How does it work?
- 1.Reads the headline, plus optional platform, use case (blog / YouTube title / social post / news / marketing / email subject), and audience.
- 2.Scores each of the 7 dimensions as n/10, plus one overall AI Headline Score as n/100 — explicitly not a predicted click-through rate.
- 3.Weighs the score differently by use case — e.g. a news-style headline is judged more on accuracy and clarity, a YouTube title more on curiosity and attention potential since it competes with a thumbnail.
- 4.Factors platform into the read the same way as use case and audience — the same headline scores differently on "Instagram" vs. "a print ad" vs. left unspecified.
- 5.Returns 1-5 concrete strengths, 1-5 concrete weaknesses, and 3-5 full rewritten versions in the same response — no separate regenerate step needed.
How to use it
- 1.Paste the headline you want scored.
- 2.Optionally name the platform it will run on.
- 3.Pick a use case — blog, YouTube title, social post, news, marketing, or email subject.
- 4.Optionally add your audience.
- 5.Click Analyze headline and review the score breakdown plus the improved versions below it.
Examples
Input
Headline: "Why Most Freelancers Underprice Their First 10 Clients" · Use case: YouTube title · Platform: YouTube
Output
AI Headline Score: 82/100. Curiosity: 9/10, Attention potential: 8/10. What works: specific number ("10 clients") creates concrete stakes. Improved version: "The Pricing Mistake That Costs Freelancers Their First 10 Clients."
Input
Same headline, Use case: News-style headline instead
Output
AI Headline Score drops (curiosity and attention potential scored lower, since this use case rewards accuracy/clarity over curious framing) — no click-through-rate language used in either version.
Tips
- •Fill in Platform specifically for YouTube titles — the score shifts to weigh curiosity and attention potential more heavily once it knows it's competing with a thumbnail in-feed.
- •Pick "News-style headline" for a factual headline — this use case is scored down for over-curious, clickbait-style framing rather than rewarded for it.
- •Email subject lines score best kept short — the analysis treats strong emotional intensity as a negative here, since it reads as spammy in an inbox, unlike the social-post use case.
- •The overall score is explicitly not a click-through-rate prediction — use it to compare drafts against each other, not as a guaranteed performance number.
- •Run your current headline first, then paste one of the returned improved versions back in to confirm the score actually moved before committing to it.
Use cases
- •YouTubers A/B testing title options before publishing.
- •Bloggers and writers checking a headline's clarity and specificity before hitting publish.
- •Email marketers checking a subject line isn't overly aggressive or spammy-reading.
- •Content teams standardizing on one measurable score to compare headline drafts instead of going by gut feel.
Frequently asked questions
What does the score actually measure?
An AI-generated content quality/attention score — not a predicted click-through rate. It evaluates clarity, curiosity, emotional impact, specificity, readability, audience relevance, and attention potential in one pass.
Which AI model powers this tool?
OpenAI GPT-4o-mini, which returns strict structured output so every score, strength, weakness, and improved version comes back from a single request.
Can I use this for a video title instead of a written headline?
Yes — pick "YouTube title" as the use case so the analysis weighs curiosity and attention potential appropriately for a title competing with a thumbnail.