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Skillsyoutube-transcript

youtube-transcript

Design & creation

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Updated 10-15 22:15

About this skill

YouTube Transcript

Fetch the full transcript of any YouTube video and turn it into whatever the user needs — summaries, blog posts, social content, quotes, show notes, or raw text.

Requirements

If youtube_transcript is not in the tool list, stop and tell the user to enable the YouTube toolkit in Hyper.

Two tools — pick the right one

Tool When to use Returns
youtube_transcript You need the raw transcript text or timestamped segments. Fast, reliable, always get this first. Full text string + segments with start/duration timestamps
youtube_reader You need AI-powered extraction from the video — summaries, Q&A, topic segmentation, translation, visual descriptions. Free-form answer to your instruction

Default: start with youtube_transcript. Use youtube_reader when you need something the raw text can't give you (e.g. visual descriptions, translation, or a structured extraction from a very long video).

Critical rules

  1. youtube_transcript takes 15–30 seconds. It spins up an isolated sandbox. Tell the user it's running and to expect a short wait — don't make them think it's stuck.
  2. Both video IDs and full URLs are accepted. "NZLAdOL9fP8" and "https://www.youtube.com/watch?v=NZLAdOL9fP8" both work.
  3. Don't fabricate transcript content. Always fetch before summarizing. Never rely on training knowledge about what a specific video says.
  4. Very long videos (>2 hours): youtube_transcript handles these fine. Only use youtube_reader on long videos if you specifically need AI-powered extraction — it can hit token limits on very long content.
  5. No transcript available: Some videos have transcripts disabled. If youtube_transcript fails, try youtube_reader as a fallback — it uses a different extraction method.

Fetching the transcript

youtube_transcript(
    video_id_or_url="https://www.youtube.com/watch?v=NZLAdOL9fP8",
    language="en"   # optional — omit to auto-detect
)

Response structure:

{
  "success": true,
  "video_id": "NZLAdOL9fP8",
  "language": "English (auto-generated)",
  "text": "Full transcript as one string...",
  "segments": [
    { "text": "This week we launched Hyper MCP.", "start": 0.0, "duration": 3.2 },
    { "text": "It brings Hyper's built-in tools...", "start": 3.2, "duration": 4.1 }
  ],
  "total_duration": 342.0
}

Use text for most tasks. Use segments when you need timestamps (e.g. chapters, clip references, karaoke captions).

Using youtube_reader for AI-powered extraction

youtube_reader(
    url="https://www.youtube.com/watch?v=NZLAdOL9fP8",
    instruction="Summarize the key points. Then list the main features demonstrated, with timestamps."
)

Good instruction examples:

  • "Extract every claim made about pricing or cost."
  • "List the action items mentioned, in order."
  • "Translate this to Spanish."
  • "What tools or products does the speaker mention by name?"
  • "Identify the main sections of this video and give me a timestamp for each."

What to do with the transcript

Once you have the text, ask the user what they need — or infer it from context:

What the user wants What to produce
Blog post Restructure the transcript into intro → sections → CTA. Clean up filler words. Add subheadings.
LinkedIn / Twitter post Extract the 1–2 sharpest insights. Rewrite in first person if it's the user's own video.
Summary 3–5 bullet points of key takeaways.
Show notes / description Title, 2-sentence summary, timestamped chapters, links mentioned.
Quote extraction Pull verbatim quotes with start timestamps from the segments array.
Repurpose for email Rewrite as a narrative email — opening hook, key insight, CTA.
Research / competitive analysis Summarize what the speaker claims, what products they recommend, and what pain points they describe.

Example outputs

Input: "Get the transcript of https://www.youtube.com/watch?v=NZLAdOL9fP8 and write a LinkedIn post from it"

Flow:

  1. Call youtube_transcript(video_id_or_url="https://www.youtube.com/watch?v=NZLAdOL9fP8")
  2. Read the returned text
  3. Identify the 1–2 sharpest moments — what's surprising, useful, or quotable
  4. Draft a LinkedIn post in the speaker's voice (first person) with a hook and a clear point

Input: "Summarize this video for me: [URL]"

Flow:

  1. Call youtube_transcript(video_id_or_url="[URL]")
  2. Return 4–6 bullet points of key takeaways, without padding or filler

Input: "Pull the timestamps for each section of this video"

Flow:

  1. Call youtube_transcript(video_id_or_url="[URL]")
  2. Use the segments array to identify topic shifts
  3. Return a chapter list: 00:00 — Intro, 01:23 — Feature demo, etc.

Related skills

When to hand off Skill
Mining comments from YouTube videos for customer research customer-research
Finding top YouTube videos by topic Use youtube_top_videos directly
Generating video content video-generation