Cross platform reformatter

Cross-Platform Reformatter

Take one existing piece and ship the same idea as a native post on each requested channel - not the same text with hashtags swapped.

Workflow

1. Extract the core: pull the single transferable idea plus its proof (the stat, story, or takeaway). This stays constant across every version; everything else is rebuilt around it.
2. Confirm the target channels. Reformat only the channels the user named; do not invent a full distribution stack. If they named none, ask which channels.
3. Rebuild - do not truncate - for each target, in its native grammar:
   • LinkedIn: text-first, ~1300-2000 chars, short lines with white space, professional-but-human, one clear insight.
   • X: a tight single post under 280, or a thread where each post stands alone; punchy, no corporate tone.
   • Instagram: caption ~125-150 chars or a short narrative; the image/Reel carries the weight.
   • TikTok: a spoken script with a verbal hook in the first two seconds; conversational, written to be said aloud.
   • YouTube Shorts / Reels: the same script logic with on-screen text beats.
   • Newsletter: longest form; keep the nuance the social cuts drop.
4. Apply native conventions per channel: hashtags 3-5 on Instagram, 1-2 on LinkedIn/X, a couple of discovery tags at most on TikTok; use features as intended (carousels/Reels on IG, document posts and polls on LinkedIn, threads and quote-posts on X); tune emoji density to the channel.
5. Hold voice, shift register: keep signature phrasing so the brand stays recognizable; go more formal on LinkedIn, looser on TikTok and X; drop jargon that does not travel to a casual feed.
6. If output feeds a calendar, note sequencing: long-form first (the anchor), then the atomized versions pointing back to it, staggered over days rather than dumped at once.
7. Label each version with its target channel and format on delivery.

Worked example

Source: a newsletter section arguing that most A/B tests are called too early, with the proof point "tests stopped at 50 conversions flip their winner a third of the time."

Bad (truncated, not rebuilt) - X:

Most A/B tests are called too early. Teams stop tests when they see an early leader, but tests stopped at 50 conversions flip their winner a third of the time. You need to pre-commit to a sample size and… (1/4)

This is the newsletter paragraph chopped at 280 characters with a thread number stapled on - the first post doesn't stand alone, the hook is buried, and the register is still newsletter-formal.

Good - X:

Your A/B test winner is probably fake.

Tests stopped at 50 conversions flip their winner a third of the time.

Pick the sample size before you launch, or you're just reading tea leaves.

Good - LinkedIn (same core, rebuilt):

We killed a "winning" variant last quarter.

It had beaten control for two straight weeks. Then we let the test run to the pre-set sample size - and the result flipped.

That's not bad luck. Tests stopped at ~50 conversions flip their winner about a third of the time.

The fix is boring and unpopular: decide the sample size before launch, and don't peek.

What's the earliest you've been burned by calling a test?

Same idea, same proof point, two different structures: X leads with the punch and stands alone; LinkedIn opens with a story, breathes with white space, and ends with a conversation prompt.

Deliverable

Produce a channel-labeled post set containing, for each requested channel:

1. The rebuilt post in that channel's native structure, length, and register - script form (with hook timing and on-screen beats) for TikTok/Shorts, text form for the rest.
2. The conventions applied - hashtags at the channel's norm, feature notes (carousel, poll, thread) where relevant.
3. A one-line core statement at the top of the set, so anyone can verify every version carries the same idea and proof.
4. Sequencing notes (anchor first, atomized versions staggered and linking back) if the set feeds a calendar.

Quality bar

• Every version reads as if written for that channel first, not resized from another.
• The core idea and its proof survive intact in each version.
• Lengths, hashtag counts, and structure match the channel's real norms.
• No version is the source text with only hashtags or emoji changed.

Do NOT

• Do not truncate the long version to fit a short one - a shorter post needs a different structure, not fewer words.
• Do not post the same text verbatim across channels.
• Do not produce versions for channels the user did not ask for.
• Do not force a piece onto a channel where it will flop; if it genuinely fits only one channel (a niche technical thread, a platform-specific trend), say so instead of shipping a weak version.
• Do not turn one source into a spread of new asset types (clip, quote card, blog paragraph) - that is content-repurposing's job.