Content Repurposer (1 → 5 Platforms)
Turn one piece of content into native posts for X, LinkedIn, and more.
Takes one source piece — blog post, video transcript, podcast — and produces genuinely platform-native versions for X/Twitter, LinkedIn, Instagram, a newsletter blurb, and YouTube description. Not cross-posting: each version restructures the idea for how that platform is consumed.
The prompt
Variables to fill in: {{voice}}{{content}}
Repurpose the content below into five platform-native formats. Each must stand alone — restructure the idea for the platform, don't compress-and-paste.
1. **X/Twitter thread** — 5-8 posts. First post is a hook with a specific claim or number (no "🧵 a thread on..."). One idea per post. Last post: the takeaway + a soft CTA.
2. **LinkedIn post** — 150-250 words. Open with a 1-2 line hook that works before the "see more" fold. Short paragraphs, one insight developed properly, end with a question that invites practitioner replies.
3. **Instagram caption** — hook line + 3-4 short lines + 5 relevant hashtags (no #love #instagood filler).
4. **Newsletter blurb** — 50-80 words teasing the full piece with the single most surprising point, plus link text.
5. **YouTube description** — 2-3 sentences with primary keyword in sentence one, then 4-6 timestamp placeholders based on the content's structure.
Preserve the original's voice: {{voice}}. Never invent statistics or claims not in the source.
Source content:
{{content}}How to use
- 1Paste the full source, not a summary — the platform versions pull different details from different parts.
- 2Describe {{voice}} with 2-3 adjectives plus a writer/creator comparison if helpful.
- 3Post the thread and LinkedIn versions at least a day apart; the algorithms and audiences overlap more than you'd think.
- 4Delete the weakest 1-2 outputs rather than forcing all five — not every idea fits every platform.
Examples
Repurposing a data blog post
Input
Voice: direct, numbers-heavy, slightly contrarian. Content: a 1,500-word post analyzing why 60% of A/B tests at the author's company were called early.
Output
**Thread post 1:** We audited 200 A/B tests. 60% were stopped early — and most 'winners' were noise. Here's what calling tests early actually costs: ... **LinkedIn:** Everyone says they're data-driven. Then a test hits significance on day 3 and gets shipped...
Pro tips
- Batch a month of source content through this in one sitting, then schedule everything.
Frequently asked questions
Which platforms should I actually use?+
Wherever your audience already is — most teams get 80% of the value from two platforms done consistently. Generate all five, measure for a month, drop what doesn't move.
Will the platforms penalize AI-generated content?+
Platforms penalize generic content, AI or not. Because this prompt restructures rather than spins, output quality tracks your source quality — a strong original produces strong repurposes.