tech-video-metadata_skill

Overview

This skill generates metadata for technical explainer YouTube videos: titles, descriptions, and hashtags optimized for discovery and engagement. I use prospect theory-based loss-aversion phrasing for attention-grabbing titles, clear description templates with timecodes and social links, and a systematic hashtag taxonomy to improve searchability. Outputs are ready-to-copy text blocks tailored to your prompt or article URL. The skill also offers expected comment patterns and suggested replies for post-publish engagement.

How this skill works

I analyze your prompt or source content to extract core themes, key points, and target audience. Using that analysis I produce multiple title candidates that leverage loss-aversion framing, a structured video description containing a table of contents/timecodes, links, and a short presenter bio. I then generate 10–15 hashtags across three categories (broad, topic, audience) and five likely comment+reply pairs to boost engagement. All outputs are delivered as plain text blocks suitable for direct paste into YouTube.

When to use it

• You need high-conversion YouTube titles for technical tutorials or explainers.
• You want a clean, clickable video description with timecodes and social links.
• You need a compact, systematic hashtag list to improve discoverability.
• You are converting an article or script into YouTube-ready metadata.
• You want suggested comment replies to streamline community management.

Best practices

• Provide a clear brief: topic, audience level, runtime, and key timestamps when available.
• Pick one audience and one primary benefit per title to keep messaging crisp.
• Use the provided timecode template exactly as generated to improve watch-time and UX.
• Limit titles to ~50–60 characters for optimal visibility on mobile and search.
• Select 10–15 hashtags mixing broad, topic, and audience tags—avoid unrelated tags.

Example use cases

• Create six title variations for a 12-minute tutorial on optimizing React performance.
• Generate a full description with a 00:00–12:00 timecode breakdown and blog/X links for a DevOps walkthrough.
• Produce 12 targeted hashtags for a Deep Learning model introduction aimed at junior engineers.
• Convert a technical blog post into YouTube title options and a structured description.
• Generate five likely viewer comments and suggested replies for a live-streamed Q&A recap.