YouTube
Automate YouTube Uploads Using Node.js
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Prompts
Workflow to automate high quality YouTube script generation in myn speaking style:
STEP 1
Extract a JSON describing the script profile from one of my well-performing old videos.
Prompt:
Watch this YouTube video: [LINK]
Then extract a JSON script profile that describes the style, structure, tonality, pacing, and delivery of the script. The goal is to provide another LLM with all the meta information it needs to recreate scripts in a similar style, regardless of the topic.
Do NOT include any content-specific information. Avoid referring to the subject matter, examples, phrases, keywords, or steps covered in the video. Only focus on:
How the script is structured (e.g., intro → hook → body → CTA)
Style of language (e.g., punchy, casual, formal)
Pacing and delivery tone
Use of repetition, rhetorical questions, personal storytelling, etc.
When and how engagement tactics (like CTAs or jokes) are used
Think like a screenwriter reverse-engineering the blueprint of the script, without knowing what the movie was about.
STEP 2
Extract YouTube video transcript from one of my old videos. I've found several free youtube transcript downloading tools that work. I used youtubetotext.
STEP 3
Use Deep Research on ChatGPT or DeepSearch on Grok to compile information about the video topic.
Prompt:
CONFIGURATION SETTINGS
TOPIC: [Insert your topic]
DEPTH: [Introductory/Intermediate/Advanced/Expert]
TIME FOCUS: [Historical/Contemporary/Future-oriented/Comprehensive]
EMPHASIS: [Theoretical/Practical/Balanced]
PERSPECTIVE: [Consensus/Competing viewpoints/Emerging theories]
TECHNICAL LEVEL: [Basic/Moderate/Detailed/Technical]
RESEARCH DIRECTIVE
Conduct comprehensive research on the TOPIC using the configuration settings above. Focus on depth over breadth, primary sources, and cross-verification of key claims.
RESEARCH PRIORITIES
• Fundamental concepts and frameworks
• Historical development and evolution
• Current state of knowledge and recent advances
• Multiple expert perspectives and debates
• Real-world applications and case studies
• Surprising facts and misconception corrections
• Visual-friendly concepts and data points