Snapshot a Post's Engagement Alongside Its Markdown

The text isn't the whole record — the counts matter for anything analytical. Thirdwatch's Tweet to Markdown converts public X posts — including long-form articles — to clean Markdown with author and engagement metadata, through a guest path that needs no login.

Skip the setup: Run this as a ready-to-go task on Apify — pre-loaded with the configuration from this guide.

Why archive engagement too

For research or reporting you need the post and its traction: a screenshot captures vibes, a row captures numbers.

replyCount, retweetCount, and favoriteCount come back on the same row as the Markdown — the archive is one run.

The converter resolves each status URL through X's guest API and renders the body as Markdown, so the archive path is a URL list in and Markdown rows out.

How does this compare to the alternatives?

Why this Actor

• Long-form support — note tweets and X articles, not just 280-character posts.
• Clean Markdown output: links, headings, and media references preserved.
• No login or cookies — the guest path is used.
• Engagement counts (replies, reposts, likes) land on every row.
• Batch input converts a reading list in one run.

How to do it in 3 steps

Step 1: Configure the input

Set the inputs as shown below — urls takes the targets, each entry is an x.com or twitter.com status URL.

Step 2: Run the Actor

Run it from the console, the API, or the linked saved task. One dataset row is written per post.

Step 3: Use the output

Each row carries the post body as markdown, the author handle and display name, timestamp, engagement counts, and an isArticle flag for long-form posts.

{
  "urls": [
    "https://x.com/jack/status/20"
  ]
}

Each dataset row looks like:

{
  "id": "20",
  "url": "https://x.com/jack/status/20",
  "author": "jack",
  "authorName": "jack",
  "createdAt": "2006-03-21T20:50:14.000Z",
  "isArticle": false,
  "markdown": "just setting up my twttr",
  "replyCount": 12000,
  "retweetCount": 95000,
  "favoriteCount": 180000
}

What to watch for

Public posts only — protected accounts and deleted tweets return error rows. The guest path occasionally rate-limits; retry error rows rather than treating them as permanent failures.

Related use cases

• Convert an X Post to Clean Markdown
• Export an X Long-Form Article as Markdown
• Convert a Batch of X Posts to Markdown in One Run
• Feed X Posts to an LLM as Clean Markdown
• All Thirdwatch use-case guides

Run the Tweet to Markdown on Apify Store — pay per result, free to try, no credit card to test.