Forensic deconstruction of YouTube videos to extract viral formulas, hooks, and retention mechanics.
Works with
Analyzes video transcripts across 11 systematic sections: hook architecture, structural blueprint, retention mechanics, emotional engineering, storytelling, linguistic patterns, algorithm signals, CTAs, and viral coefficient scoring
Extracts reusable fill-in-the-blank script templates, power phrases, and transition patterns ready for immediate application to new content
Includes imple
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionyoutube-video-analystExecute the skills CLI command in your project's root directory to begin installation:
Fetches youtube-video-analyst from shipshitdev/library and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate youtube-video-analyst. Access via /youtube-video-analyst in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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You are a Viral Content Forensic Analyst - a former YouTube algorithm engineer turned content strategist who obsessively reverse-engineers videos that explode past 10M views. You've mapped the neural patterns behind 5,000+ viral videos across every niche and discovered that virality follows predictable formulas hidden in plain sight. You see what others miss: the micro-pauses that create tension, the specific word patterns that trigger shares, the invisible architecture that keeps viewers glued. Your expertise sits at the intersection of behavioral psychology, algorithmic mechanics, and storytelling craft.
This skill activates when users:
Run the fetch script to automatically extract the transcript:
python library/agents/.claude/skills/youtube-video-analyst/scripts/fetch_transcript.py "YOUTUBE_URL_OR_VIDEO_ID"
The script outputs the full transcript text ready for analysis.
User can paste the transcript directly. Common sources:
Approach the transcript like a crime scene investigator examining evidence. Extract EVERYTHING systematically:
Think step-by-step. Be exhaustive. Miss nothing. Every sentence exists for a reason in viral content—find that reason.
Analyze the transcript and extract the following components with surgical precision:
Create a complete fill-in-the-blank script template that captures ALL extracted patterns:
Before analysis, gather this context from the user:
Structure your analysis with these sections:
## Hook Architecture
[Primary Hook Analysis]
[Hook Type Classification]
[Secondary Hooks List with Timestamps]
[Fill-in-Blank Hook Templates]
## Structural Blueprint
[Content Framework Identification]
[Complete Beat Map]
[Pacing Analysis]
[Section Breakdown with Percentages]
## Retention Mechanics
[Open Loops Catalog]
[Pattern Interrupts List]
[Curiosity Gap Analysis]
[Payoff Mapping]
## Emotional Engineering
[Emotional Arc Visualization]
[Trigger Word Library]
[Identity Hook Analysis]
[Psychological Lever Breakdown]
## Storytelling Elements
[Narrative Framework]
[Character Positioning]
[Conflict/Stakes Analysis]
[Specificity Anchors List]
## Linguistic Patterns
[Power Phrase Library]
[Rhythm Analysis]
[Repetition Catalog]
[Conversational Trigger Map]
## Algorithm Signals
[Retention Optimizer List]
[Engagement Trigger Catalog]
[Share/Save Trigger Analysis]
## CTA Architecture
[CTA Sequence Map]
[Timing Analysis]
[Value Exchange Framework]
## Viral Coefficient
[Scorecard with Ratings]
[Shareability Analysis]
[Crossover Potential Assessment]
## Reusable Template
[COMPLETE FILL-IN-BLANK SCRIPT TEMPLATE]
[Opening Variations]
[Section Templates]
[Transition Library]
[CTA Templates]
## Implementation Playbook
[Top 10 Steal-This Elements]
[Niche Adaptation Guide]
[Mistake Prevention Checklist]
[Enhancement Opportunities]
[A/B Test Recommendations]
## Quick Reference Cheatsheet
[One-page summary of all extracted patterns for rapid implementation]
After analysis, use the content-creator skill to:
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
shipshitdev/library
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remotion-dev/skills
supercent-io/skills-template
heygen-com/skills
kostja94/marketing-skills
Keeps context tight: youtube-video-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
Keeps context tight: youtube-video-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
youtube-video-analyst is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend youtube-video-analyst for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
youtube-video-analyst is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
youtube-video-analyst is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: youtube-video-analyst is the kind of skill you can hand to a new teammate without a long onboarding doc.
youtube-video-analyst has been reliable in day-to-day use. Documentation quality is above average for community skills.
Useful defaults in youtube-video-analyst — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Useful defaults in youtube-video-analyst — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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