gh-lttr-claude-marketplace-plugins-video-to-article/skills/video-to-article/SKILL.md

name, description, allowed-tools

name	description	allowed-tools
video-to-article	Use this skill when the user wants to convert a lecture, presentation, or talk video into text formats (transcript, outline, or article). Trigger when user mentions processing video recordings, creating transcripts from lectures, or generating articles from recorded presentations.	Bash, Read, Write, AskUserQuestion, Glob

Video to Article Conversion Workflow

This skill automates the conversion of lecture/presentation videos into various text formats including transcripts, outlines, and article drafts.

Workflow Overview

1. Setup Folder - Create properly named folder if needed
2. Validate Input Metadata - Check for README.md with required frontmatter
3. Extract Audio - Convert video to MP3 using ffmpeg
4. Transcribe - Generate text transcript using ElevenLabs API
5. Process Text - Create progressive text refinements

Step 0: Folder Setup (if starting from scratch)

If user is starting a new talk/lecture conversion and no folder exists yet:

Create folder using format: YYYY Title of Talk

After creating folder, navigate into it and proceed with workflow.

Step 1: Validate Metadata

Look for README.md in the current directory with these frontmatter fields:

• title - Lecture/presentation title
• speaker - Speaker name
• date - Presentation date (YYYY-MM-DD)
• lang - Presentation language (e.g., "english", "czech", "spanish")
• abstract - Brief description
• slides - Link to slides (or file path)
• video - Optional: link to video

If README.md is Missing or Incomplete

Use the AskUserQuestion tool to collect missing information:

- What is the lecture title?
- Who is the speaker?
- What date was this presented?
- What language is the presentation in?
- Brief description or abstract?
- Link to slides or presentation file?

Create or update README.md with collected information.

Step 2: Find or Download Video File

Check for Local Video

Look for video file in current directory:

• Common patterns: *.mp4, *.mov, *.avi, *.mkv
• If multiple found, ask user which to process

If No Local Video Found

Ask user if they have a YouTube URL using AskUserQuestion tool:

• "Do you have a YouTube URL for this talk?"
• If yes, collect the YouTube URL
• If no, ask for local video file path

Download from YouTube (if URL provided)

bash ${CLAUDE_PLUGIN_ROOT}/skills/video-to-article/scripts/download-youtube.sh <youtube-url>

This downloads the video as video.mp4 in medium quality (720p max).

Requirements: User needs yt-dlp installed. If missing, show:

Install yt-dlp:
- pip install yt-dlp
- brew install yt-dlp (macOS)
- sudo apt install yt-dlp (Ubuntu/Debian)

Step 3: Extract Audio

Check if audio.mp3 already exists. If not:

Run the extract-audio.sh script using the plugin root variable:

bash ${CLAUDE_PLUGIN_ROOT}/skills/video-to-article/scripts/extract-audio.sh <video-file>

This creates audio.mp3 in the current directory.

Step 4: Transcribe Audio

Check if generated-transcript.txt already exists. If not:

Map Language to ISO Code

Convert the lang field from README.md to the appropriate ISO 639-1 language code for ElevenLabs API. Use your knowledge of language codes to map language names to their two-letter codes (e.g., "english" → "en", "czech" → "cs", "spanish" → "es").

Run Transcription

bash ${CLAUDE_PLUGIN_ROOT}/skills/video-to-article/scripts/transcribe-audio.sh <language-code>

Step 5: Generate Text Outputs

Execution Protocol

Before generating ANY content, you MUST complete these steps in order:

1. List all required outputs - Read and acknowledge the complete list below
2. Check which files already exist - Use file existence checks for each output
3. Read all existing source files - Load transcript, outline, key-ideas as context
4. Confirm which outputs need generation - Explicitly state which files are missing
5. Only then begin generation - Generate missing files one by one

Required Outputs

You MUST generate ALL of these files:

1. generated-transcript-cleaned.md - Cleaned transcript
2. generated-transcript-readable.md - Readable transcript
3. generated-transcript-outline.md - Content outline
4. generated-key-ideas.md - Key takeaways
5. generated-article-formal.md - Explanatory blog post (long-form, narrative)
6. generated-article-direct.md - Scannable technical brief (concise, bullets)

IMPORTANT: Outputs 5 and 6 are TWO DIFFERENT ARTICLE VARIANTS with distinct styles and audiences. You must generate BOTH.

MANDATORY WORKFLOW:

• Check file existence for ALL files above
• Automatically generate ANY missing files without asking user
• Skip files that already exist (inform user which were skipped)
• NEVER declare completion unless all files exist
• NEVER ask user if they want to generate missing files - just generate them
• Generate BOTH article variants (formal and direct) - they serve different purposes

Idempotent Generation Strategy

This process is idempotent - running the skill multiple times will only generate missing files, never overwrite existing ones:

1. Check each output file before generating - Use file existence checks
2. Skip files that already exist - Inform user which files are being skipped
3. Generate only missing files - Never overwrite existing content
4. Use existing files as context - When generating later outputs (like key-ideas), read all available previous outputs for context

Example: If only generated-key-ideas.md is missing:

• Read existing: generated-transcript-cleaned.md, generated-transcript-readable.md, generated-transcript-outline.md
• Generate: generated-key-ideas.md using the existing files as context
• Skip: All other outputs

This allows users to:

• Resume interrupted workflows
• Generate only specific missing outputs
• Re-run safely without data loss

Output 1: Cleaned Transcript

File: generated-transcript-cleaned.md Input: generated-transcript.txt Check: Skip if file exists

Convert the transcript into a more readable form by dividing it into paragraphs and adding headings.

Instructions:

• Do not change the content, except for obvious typos
• Do not change the tone of voice - if the speaker uses informal language, keep it
• Remove filler words like "Eh", "Ehm", "Um", "Uh"
• Remove comments related to the transcription itself, or rewrite them elegantly if possible (e.g., "(laughter)" or "(2 second pause)")
• Respond in {lang} language - maintain the same language as the original transcript

The cleaned transcript should preserve the speaker's authentic voice while being easier to read and follow.

Output 2: Readable Transcript

File: generated-transcript-readable.md Inputs: generated-transcript.txt and generated-transcript-cleaned.md Check: Skip if file exists

You have two inputs:

1. The first text contains the direct transcript of a lecture
2. The second text contains a better structured version of this transcript

The slides are available here: {slides}

Create a more readable text from this transcript:

Instructions:

• Preserve the style, but optimize for reading comprehension
• Fix typos, repetitions, and improve stylistic clarity
• Shorten where it doesn't affect the message
• Make it flow naturally for readers while keeping the speaker's voice
• Respond in {lang} language - the output must be in the same language as the input

The goal is to make the content accessible to readers while maintaining the essence of the spoken presentation.

Output 3: Outline

File: generated-transcript-outline.md Inputs: Cleaned and readable transcripts Check: Skip if file exists

From the provided transcript inputs, create an outline of what was discussed.

Instructions:

• List the main ideas and messages with very brief content
• Use bullet points for clarity
• Focus on key takeaways and core concepts
• Keep descriptions concise - just enough to understand the point
• Respond in {lang} language - the outline must be in the same language as the source material

This outline should serve as a quick reference guide to the presentation's structure and main points.

Output 4: Key Ideas

File: generated-key-ideas.md Inputs: Cleaned and readable transcripts (or all available generated files if running incrementally) Check: Skip if file exists

From the provided transcript inputs, extract the key ideas, tips, and main concepts.

Instructions:

• Focus on interesting insights, actionable tips, and core concepts
• Unlike the outline, don't follow chronological order - prioritize importance
• Exclude generic or procedural content
• Each idea should have a brief description explaining why it matters
• Use bullet points or numbered list
• Respond in {lang} language - the output must be in the same language as the source material

This should capture the most valuable takeaways someone would want to remember from the talk.

Output 5: Explanatory Blog Post

File: generated-article-formal.md Inputs: All previous outputs (or all available generated files if running incrementally) Check: Skip if file exists

Create a traditional blog post with complete explanations and smooth narrative flow.

Target audience: General readers discovering the topic, browsing casually Reading context: Website visitors who have time and want full understanding

Instructions:

• Write in complete, flowing sentences with careful transitions
• Provide context and background before diving into details
• Use storytelling elements to maintain engagement
• Example opening: "V průběhu posledního roku jsme zaznamenali značné změny..." (Czech) or equivalent
• Explain why concepts matter, not just what they are
• Guide readers through ideas with clear signposting
• Respond in {lang} language - the article must be in the same language as the source material

Style characteristics:

• Narrative structure with introduction, development, conclusion
• Welcoming tone that assumes less prior knowledge
• Longer paragraphs with descriptive language
• Educational approach that builds understanding step-by-step

Output 6: Scannable Technical Brief

File: generated-article-direct.md Inputs: All previous outputs (or all available generated files if running incrementally) Check: Skip if file exists

Create a condensed, high-signal article optimized for rapid scanning and information extraction.

Target audience: Technical readers or busy professionals who skim content Reading context: Newsletter, Slack/Discord shares, or quick reference

Instructions:

• Lead with short, declarative statements - skip warm-up sentences
• Frontload key information in each paragraph
• Heavy use of bullets, numbered lists, and visual breaks
• Example opening: "AI modely: radikální skok za rok." (Czech) or equivalent
• Cut all filler words, hedging, and obvious statements
• Dense information - every sentence earns its place
• Respond in {lang} language - the article must be in the same language as the source material

Style characteristics:

• Telegraphic style - fragments are encouraged when clearer
• Bullets and lists dominate over prose paragraphs
• Assumes reader familiarity with domain
• Optimized for 2-minute skim, not 10-minute read

Summary

After completion, inform the user which files were:

• Skipped (already existed)
• Generated (newly created)

Example output:

Workflow complete!

Skipped (already exists):
- audio.mp3
- generated-transcript.txt
- generated-transcript-cleaned.md
- generated-transcript-readable.md
- generated-transcript-outline.md

Generated:
- generated-key-ideas.md
- generated-article-formal.md
- generated-article-direct.md

All outputs in <language> language.

If everything was generated fresh, simply list all outputs under "Generated".

Error Handling

• Missing ffmpeg: Prompt user to install ffmpeg
• Missing API key: Prompt user to set ELEVENLABS_API_KEY
• Transcription errors: Show error message and suggest checking API key/quota
• Script not found: Use absolute paths to skill scripts directory