Skill Seekers v3.2.0 adds YouTube tutorial extraction for Claude skills

✍️ OpenClawRadar📅 Published: March 1, 2026🔗 Source
Skill Seekers v3.2.0 adds YouTube tutorial extraction for Claude skills
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Skill Seekers v3.2.0 adds video extraction capabilities to this open-source tool that converts documentation into Claude skills. You can now point it at a YouTube tutorial and get a structured SKILL.md file that Claude can use as persistent context.

How it works

The basic command is:

skill-seekers video --url https://youtube.com/watch?v=... --enhance-level 2

The pipeline includes:

  • Transcript extraction using YouTube API → yt-dlp → Whisper fallback
  • Keyframe extraction and classification (code editor, terminal, slides, webcam)
  • OCR on code panels with multi-engine ensemble
  • Code evolution tracking across frames (what lines were added/changed/removed)
  • Two-pass AI enhancement for cleanup

Two-pass AI enhancement workflow

Pass 1 sends the raw reference file (noisy OCR + transcript) to Claude and asks it to reconstruct the Code Timeline. This fixes OCR errors like l/1 and O/0, removes UI junk that leaked in (Inspector panels, tab bars), and uses the transcript narration as context for what the code should be.

Pass 2 takes the cleaned reference and generates the final SKILL.md — a structured document with setup steps, code examples, and concepts extracted from the tutorial.

You can define custom enhancement workflows in YAML:

stages:
  - name: ocr_code_cleanup
    prompt: "Clean OCR artifacts from code blocks..."
  - name: tutorial_synthesis
    prompt: "Synthesize a teaching narrative..."
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Technical insights from development

  • OCR on code editors is surprisingly hard due to IDE decorations (line numbers, collapse markers, tab bars) leaking into text
  • Frame classification matters — webcam frames produce pure garbage when OCR'd; skipping them cut junk output by ~40%
  • The two-pass approach was a big quality jump, letting Claude see both OCR and transcript context to reconstruct mangled code

Other supported sources

  • Documentation websites (presets for React, Vue, Django, FastAPI, Godot, Kubernetes, and more)
  • GitHub repos (AST analysis, pattern detection)
  • PDFs and Word docs
  • Outputs to Claude, Gemini, OpenAI, or RAG formats (LangChain, Pinecone, ChromaDB, etc.)

Installation and setup

Install with: pip install skill-seekers

Video dependencies need GPU setup: skill-seekers video --setup (auto-detects CUDA/ROCm/CPU)

📖 Read the full source: r/ClaudeAI

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👀 See Also