Break one blog post into platform-specific social snippets
Repurposing content by hand is tedious—most writers either copy-paste paragraphs or write from scratch. This prompt extracts the strongest ideas from an existing post and reformats them for three distinct platforms in one pass.
You are a content strategist who specializes in extracting maximum signal from long-form writing. Use the blog post below to complete the following steps.
1. IDEA EXTRACTION: Read the post and identify the 5 strongest standalone ideas, findings, or arguments. List each as a one-sentence summary.
2. PLATFORM SNIPPETS: For each of the 5 ideas, write one post for each of the three platforms listed below. Respect the format rules strictly.
- {{PLATFORM_ONE}}: {{PLATFORM_ONE_FORMAT_RULES}}
- {{PLATFORM_TWO}}: {{PLATFORM_TWO_FORMAT_RULES}}
- {{PLATFORM_THREE}}: {{PLATFORM_THREE_FORMAT_RULES}}
3. HOOK VARIANTS: For the single strongest idea (your pick), write three alternative opening hooks with different angles: one data-led, one contrarian, one story-led.
4. WHAT TO SKIP: Note any sections of the blog post that don't translate well to social and briefly explain why.
Blog post:
{{BLOG_POST_TEXT}}
Note: If the post is a listicle with more than 12 items, focus on the 5 most distinctive items, not the most generic ones. {{PLATFORM_ONE}}{{PLATFORM_ONE_FORMAT_RULES}}{{PLATFORM_TWO}}{{PLATFORM_TWO_FORMAT_RULES}}{{PLATFORM_THREE}}{{PLATFORM_THREE_FORMAT_RULES}}{{BLOG_POST_TEXT}}
How to use this prompt
- Copy the prompt above (Copy button on the top-right).
- Replace each
{{VAR}}with your own value. Variables:{{PLATFORM_ONE}}{{PLATFORM_ONE_FORMAT_RULES}}{{PLATFORM_TWO}}{{PLATFORM_TWO_FORMAT_RULES}}{{PLATFORM_THREE}}{{PLATFORM_THREE_FORMAT_RULES}}{{BLOG_POST_TEXT}}. - Paste it into one of the recommended tools below.
- Iterate: tighten constraints in the prompt if the output is generic.
Why this prompt is structured this way
The prompt is split into explicit steps because LLMs do better when the path is named, not implied. Each variable forces specificity at the input layer — vague inputs get vague outputs.
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