OpenClaw · Open source
Turn YouTube research into X threads and LinkedIn posts weekly
A Chinese developer blogger set up OpenClaw to mine YouTube for topics every Monday, draft X threads and LinkedIn posts, and wait for approval in Telegram. He says daily content time fell from about three hours to about thirty minutes.
What they did
He installed a YouTube skill to watch chosen channels and keywords and scheduled a topic research run every Monday at 9am. He iterated the drafting prompts for X threads and LinkedIn long posts more than ten times, connected both platforms through their APIs with keys kept in environment variables, and added a Telegram review step so nothing posts without his confirmation. A weekly job summarizes performance into a report.
How it went
The poster says his daily content time dropped from about three hours to about thirty minutes, and that he edits roughly 20% of each AI draft instead of writing from scratch.
Worth knowing
Early hooks were weak, drafts often ran over length limits and the AI sometimes missed the source's main point; he rates the output about 70 out of 100 and keeps a human check. No follower or engagement numbers are shared.
Try it with OpenClaw
Every Monday at <time>, check new videos from <YouTube channels> about <topic keywords> and pick the three most useful ideas. For each, draft one X thread under <character limit> per post and one LinkedIn post, each with a strong first line. Send the drafts to me in <chat app> and publish only the ones I approve.
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Someone using it at work posted about it. Any numbers are theirs, so we write "the poster says".
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