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Youtube Data

Community
artemchuikin
youtube-data

Reach for this when structured YouTube data is the goal: video metadata, transcripts for analysis, channel upload history, search results or playlist contents, with no Google Cloud project and no quota units. Triggers on YouTube links, creator names and topic research even when unstated. Skip it for uploads and text-only research.

Overview

Publisherartemchuikin
Repositoryyoutube-skills
Skill nameyoutube-data
Stars
397
Forks
21
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by artemchuikin on GitHub. Read the source before you install it.

Installation

Install the Youtube Data AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/artemchuikin/youtube-skills/tree/main/clawhub/youtube-data
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/artemchuikin/youtube-skills.git /tmp/youtube-skills
mkdir -p .claude/skills
cp -r /tmp/youtube-skills/clawhub/youtube-data .claude/skills/youtube-data
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Youtube Data in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Youtube Data on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Youtube Data is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

YouTube Data

YouTube data access via TranscriptOut.com: a lightweight alternative to Google's YouTube Data API.

Setup

If $TRANSCRIPTOUT_API_KEY is not set, read references/auth-setup.md and follow the instructions there to get and store the key.

Required Header

Every request carries these headers:

  • Authorization: Bearer $TRANSCRIPTOUT_API_KEY
  • X-Client: youtube-skills-clawhub/youtube-data, so TranscriptOut knows the call came from this skill

Every response is one JSON envelope. Success: {"ok": true, "request_id": "...", "data": {...}}. Error: {"ok": false, "code": "...", "detail": "...", "request_id": "..."}. Branch on the machine-readable code, not on the human text. The remaining credit balance rides in the X-Credits-Remaining response header.

API Reference

Base URL: https://api.transcriptout.com/v1. Full reference with the latest parameters and schemas: transcriptout.com/docs.

GET /v1/video · 1 credit

Metadata for one video (title, channel, duration, views, thumbnails) plus the list of available transcript languages, WITHOUT downloading the subtitles.

bash
curl -s "https://api.transcriptout.com/v1/video?id=VIDEO_URL_OR_ID" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

Credit hygiene: if the transcript is wanted anyway, call /v1/transcript with video_metadata=true instead. One call and one credit against two.

Transcript data · 1 credit

Fetch the transcript of any YouTube video.

bash
curl -s "https://api.transcriptout.com/v1/transcript?video=VIDEO_URL_OR_ID&format=text" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

Accepts full URLs (youtube.com/watch?v=ID), short URLs (youtu.be/ID), shorts (youtube.com/shorts/ID), or bare video IDs.

Default for agents: use format=text unless you need timestamps. Plain text is the cheapest form to reason over. Use format=json to cite or seek to exact moments. Add video_metadata=true when the title/channel is also wanted: same call, same 1 credit.

ParamRequiredDefaultValues
videoyes-YouTube URL (full/short/shorts) or 11-char video ID
langnoenlanguage code of the track (en, de, ...)
formatnojsonjson, text, srt, vtt, srv3
kindnomanual if presentmanual, auto
segmentnoauto tracks: 180 (80 for srt/vtt). Manual tracks keep the author's lines20-5000, max characters per segment
video_metadatanofalsetrue adds data.metadata (title, channel, duration, views) for the same 1 credit
downloadnofalsetrue returns the raw file instead of the JSON envelope (text/srt/vtt/srv3 only)

segment controls the size of the pieces: 500-1500 characters makes chunks with enough context for embeddings and retrieval. Left out, an auto-generated track is cut into ~180-character segments and a manual track is returned exactly as its author broke it.

Response for format=json. With format=text/srt/vtt/srv3 the transcript field is one string in that format:

json
{
  "ok": true,
  "request_id": "req_...",
  "data": {
    "video_id": "dQw4w9WgXcQ",
    "language": "en",
    "kind": "manual",
    "transcript": [
      { "text": "Never gonna give you up", "start": 18.0, "duration": 4.12 },
      { "text": "Never gonna let you down", "start": 22.12, "duration": 3.85 }
    ],
    "available_langs": [
      { "code": "en", "kind": "manual", "name": "English" },
      { "code": "en", "kind": "auto", "name": "English (auto-generated)" }
    ]
  }
}

GET /v1/search · 1 credit/page

Search YouTube for videos or channels.

bash
# Videos
curl -s "https://api.transcriptout.com/v1/search?q=QUERY&type=video&limit=20" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

# Channels
curl -s "https://api.transcriptout.com/v1/search?q=QUERY&type=channel&limit=10" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

# Next page
curl -s "https://api.transcriptout.com/v1/search?next_page_token=TOKEN" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"
ParamRequiredDefaultValidation
qyes*-the query (*or pass next_page_token)
typenovideovideo, channel
limitno201-50
next_page_tokenno-token from a previous page

The response carries next_page_token and has_more. Video entries have video_id, title, channel, duration ("M:SS"), view_count, published, url, thumbnails.

GET /v1/channel/videos · 1 credit/page

Every video from a channel's Videos tab, newest first.

bash
# First page (100 videos)
curl -s "https://api.transcriptout.com/v1/channel/videos?name=@3blue1brown" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

# Next pages
curl -s "https://api.transcriptout.com/v1/channel/videos?next_page_token=TOKEN" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

# IDs only, 500 per page (feed these into the bulk job)
curl -s "https://api.transcriptout.com/v1/channel/videos?name=@3blue1brown&ids_only=true" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

Provide name on the first call and only next_page_token afterwards. limit goes up to 100, or up to 500 with ids_only=true (the response is then video_ids[] instead of full video objects). The response carries next_page_token and has_more.

GET /v1/playlist/videos · 1 credit/page

Every video of a playlist, in playlist order.

bash
# First page (100 videos)
curl -s "https://api.transcriptout.com/v1/playlist/videos?id=PL_ID_OR_URL" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

# Next pages
curl -s "https://api.transcriptout.com/v1/playlist/videos?next_page_token=TOKEN" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

# IDs only, 500 per page (feed these into the bulk job)
curl -s "https://api.transcriptout.com/v1/playlist/videos?id=PL_ID_OR_URL&ids_only=true" \
  -H "Authorization: Bearer $TRANSCRIPTOUT_API_KEY" \
  -H "X-Client: youtube-skills-clawhub/youtube-data"

id accepts a PL... playlist ID or any URL with list=. limit goes up to 100, or up to 500 with ids_only=true. The response carries playlist, title, count, videos[] (or video_ids[]), next_page_token and has_more.

Credit Costs

EndpointCost
transcript1
video (metadata)1
search1/page
channel/latest1
channel/videos1/page
channel/search1/page
playlist/videos1/page
playlist/search1
transcripts (bulk job)1 per video
job status / results / cancelfree

Credits are refunded automatically when a call fails before reaching YouTube (validation, rate limit, service capacity). A definitive "this video has no captions" (404) is an answer and is billed like one.

Errors

CodeMeaningAction
400/422Bad parameterFix the request. Credit refunded automatically
401Bad or missing API keyCheck the key. It must start with sk_
402Out of creditstranscriptout.com/billing
404No captions on that language/track, or bad IDDefinitive answer, do not retry. Try another lang or kind=auto. Billed
410Video removedDo not retry
451Age-restricted or members-onlyDo not retry
429Rate limit (200 req/min per key)Wait, respect Retry-After. Refunded
502Failed on YouTube's sideOne retry is reasonable. Billed
503Service at capacityRetry after Retry-After. Refunded

Every error body carries a machine-readable code and a request_id. Include the request_id when contacting support.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Youtube Data AI skill do?

Reach for this when structured YouTube data is the goal: video metadata, transcripts for analysis, channel upload history, search results or playlist contents, with no Google Cloud project and no quota units. Triggers on YouTube links, creator names and topic research even when unstated. Skip it for uploads and text-only research.

Why use Youtube Data on TypingMind?

Because you install it once and use it with any model. Youtube Data is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Youtube Data in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/artemchuikin/youtube-skills/tree/main/clawhub/youtube-data. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Youtube Data?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Youtube Data?

As many as you like. As long as a model supports skills, you can use Youtube Data with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Youtube Data AI skill free?

Yes. It is published on GitHub by artemchuikin under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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