Where the tool lives

Repository: github.com/CloudAxisAi/markdown-to-social

Install with npm install, then run node convert.js --file ./post.md. By default you get output/twitter-thread.txt, output/linkedin.txt, and output/instagram.txt. Use --stdout if you prefer piping instead of files.

What makes the output usable

Twitter / X: the script flattens your body copy, splits on word boundaries, and reserves space for 1/n numbering so each tweet stays under the limit — not a naive "split by H2 only" that breaks mid-paragraph.

LinkedIn: list lines become alternating 👉 / ✅ rows; links become label (url) so you can decide what to keep. Paragraphs are spaced for the "broetry" style that tends to read well in the feed.

Instagram: first ~150 words plus hashtag suggestions derived from tags: in frontmatter and section headings — still your job to trim for brand voice.

Honest limits

This is heuristic text shaping, not an LLM. It will not invent hooks, debate nuance, or match your company tone — it gives you paste-ready scaffolding. For fully automated multi-step publishing with agents, schedules, and integrations, that is a different product surface (see below).

When you want an agent, not a script

If your workflow is "research draft → edit in Notion → schedule to three channels → track replies," a one-shot CLI is not enough. CloudyBot is built for recurring execution with Specialists, file workspace, and optional cloud browser work — with hard caps so bills stay predictable. Try free → and see pricing for current task and browser-minute limits.

Further reading

Related reading

Ready to automate this? CloudyBot can handle tasks like this on a schedule — with a real browser, memory, and WhatsApp delivery.

Try CloudyBot free →

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