MrBeast Skill
https://github.com/alchaincyf/mrbeast-skill- Category
- Developer Tools
- Rank
- No. 1943Tools index
- Pricing
- Open Source
- Type
- TOOL
- Builder
- alchaincyf
- GitHub
- 109 stars
- Date
About
Claude Code skill encoding MrBeast's content creation operating system as runnable methodology.
What it does
It turns an AI agent into a direct, data-minded video coach. The guidance focuses on titles, thumbnails, opening hooks, pacing, retention, and escalating stakes. Four companion scripts analyze title collections, inspect scripts for retention signals, audit thumbnail choices, and download YouTube subtitles.
Why it's ranked here
The package goes beyond a voice imitation. It supplies explicit decision rules, response checkpoints, failure fallbacks, worked conversations, research notes, and runnable analysis tools. That breadth makes it useful for structured creative diagnosis. Its conclusions still depend heavily on fixed formulas and keyword heuristics, so creators should treat the output as prompts for testing, not measured truth.
What's good
The advice consistently converts broad goals into concrete edits, such as shortening titles, separating title and thumbnail information, and placing fresh engagement moments through a script. The skill also preserves tensions around budget, platform differences, working conditions, and commercial failures. Its scripts produce readable Markdown reports from ordinary text or image inputs.
Tradeoffs
The agent adopts a first-person MrBeast persona, which may blur the distinction between sourced material and generated interpretation despite an initial disclaimer. Several analyzers infer quality from regular expressions, word lists, brightness, contrast, and saturation. Those signals cannot measure actual audience response. Image inspection requires Pillow, subtitle retrieval requires yt-dlp, and the research workflow expects web search support.
How to use it well
Use it when a YouTube creator has a title, thumbnail, script, or retention problem that needs a disciplined critique. Pair its suggestions with real channel analytics and controlled thumbnail tests. It is less suitable for general content strategy, non-video publishing, or direct analytics collection, and its own guidance says other platforms require adaptation.
Technical notes+
SKILL.md defines YAML activation metadata, persona rules, research checkpoints, fallback behavior, and the content framework. scripts/analyze_titles.py is a standard-library Python CLI that reads one title per line and emits Markdown; classify_titles assigns each title to the first matching regex category. scripts/retention_curve_checker.py estimates duration and scores hooks, re-engagement, endings, action density, and escalation through regex-based heuristics. scripts/thumbnail_audit.py accepts title, thumbnail text, and an optional image; Pillow enables pixel statistics. scripts/fetch_youtube_subtitles.sh wraps yt-dlp, attempts manual subtitles first, then automatic subtitles. examples/demo-conversation-2026-04-07.md provides six worked exchanges, while references/research/ contains five research documents.
Observed
- License
- MIT
- Packaging
- Agent Skills compatible Markdown skill with YAML frontmatter
- Install surface
- Install through the skills CLI with npx, clone manually, or paste the skill text into a conversation
- Interfaces
- Agent skill plus Python command-line analyzers and a shell subtitle downloader
- Runtime support
- README names Claude Code, Codex, Cursor, OpenClaw, Hermes Agent, CodeBuddy, Workbuddy, Gemini CLI, and OpenCode
- Implementation
- Markdown content with three Python analysis scripts and one Bash utility
- Dependencies
- Pillow is optional for image analysis; yt-dlp is required for subtitle retrieval
- Repository structure
- The shown repository tree lists no test directory
Read from README.md, scripts/analyze_titles.py, scripts/thumbnail_audit.py, scripts/retention_curve_checker.py, LICENSE, SKILL.md, scripts/fetch_youtube_subtitles.sh, examples/demo-conversation-2026-04-07.md, references/research/06-timeline.md, references/research/05-decisions.md, references/research/02-conversations.md.
What it can do
Generate viral content ideas
Topic or theme → List of MrBeast-style content concepts
Create video title suggestions
Video concept or description → Clickbait-optimized titles following MrBeast format
Design challenge mechanics
Challenge concept or goal → Structured challenge rules and format
Generate thumbnail concepts
Video title and content description → Thumbnail design ideas and visual elements
Optimize content for engagement
Draft content or video script → Engagement-optimized version with hooks and pacing
Create production workflows
Video concept and requirements → Step-by-step production methodology
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