Content OS: Multi-Format Content Orchestrator
The "produce everything" button. Give one seed idea → get all content types. Or give long-form content → get it split into short-form pieces.
Quick Start
Forward Mode (Seed → All Content)
User: "Content OS: Statins myth-busting for Indians"
Output: ├── Long-form (quality-passed) │ ├── YouTube script (Hinglish) │ ├── Newsletter (B2C - patients) │ ├── Newsletter (B2B - doctors) │ ├── Editorial │ └── Blog post ├── Short-form (accuracy-checked) │ ├── 5-10 tweets │ ├── 1 thread │ └── Carousel content └── Visual ├── Instagram carousel slides └── Infographic concepts
Backward Mode (Long-form → Split)
User: "Content OS: [paste your blog/script/newsletter]"
Output: ├── 5-10 tweets (key points) ├── 1 thread (condensed narrative) ├── Carousel slides (visual summary) └── Snippets (quotable sections)
How It Works
Mode Detection
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Forward Mode: Input is a topic/idea (short text, question, or concept)
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Backward Mode: Input is existing long-form content (>500 words)
Forward Mode Pipeline
PHASE 1: RESEARCH │ ├── PubMed MCP │ └── Search for relevant papers, trials, guidelines │ ├── knowledge-pipeline (RAG) │ └── Query AstraDB for ACC/ESC/ADA guidelines, textbooks │ ├── social-media-trends-research (optional) │ └── Check trending angles, audience questions │ └── OUTPUT: research-brief.md └── Synthesized knowledge with citations
PHASE 2: LONG-FORM CONTENT (Full Quality Pipeline) │ ├── youtube-script-master │ └── Hinglish script → Quality Review → Final │ ├── cardiology-newsletter-writer │ └── B2C newsletter → Quality Review → Final │ ├── medical-newsletter-writer │ └── B2B newsletter → Quality Review → Final │ ├── cardiology-editorial │ └── Editorial → Quality Review → Final │ └── cardiology-writer └── Blog post → Quality Review → Final
PHASE 3: SHORT-FORM CONTENT (Quick Accuracy Pass) │ ├── x-post-creator-skill │ └── 5-10 tweets → Accuracy Check → Final │ ├── twitter-longform-medical │ └── Thread → Accuracy Check → Final │ └── Extract carousel content from long-form
PHASE 4: VISUAL CONTENT │ ├── carousel-generator │ └── Generate Instagram slides from key points │ └── cardiology-visual-system └── Infographic concepts (if data-heavy)
PHASE 5: OUTPUT │ └── Organized folder structure with all content
Backward Mode Pipeline
PHASE 1: ANALYZE │ └── Parse long-form content ├── Extract key points ├── Identify data/statistics ├── Find quotable sections └── Determine topic/theme
PHASE 2: SPLIT (Quick Accuracy Pass) │ ├── Generate tweets (5-10) │ └── One key point per tweet │ ├── Generate thread │ └── Condensed narrative │ ├── Extract carousel content │ └── Key points for slides │ └── Create snippets └── Quotable sections
PHASE 3: VISUAL │ └── carousel-generator └── Generate slides from extracted content
PHASE 4: OUTPUT │ └── All short-form pieces organized
Quality Gates
Long-Form Quality Pipeline (FULL)
Each long-form piece goes through:
scientific-critical-thinking
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Evidence rigor check
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Citation verification
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Claim accuracy
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Statistical interpretation
peer-review
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Methodology review
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Logical consistency
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Completeness check
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Counter-argument consideration
content-reflection
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Pre-publish QA
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Audience appropriateness
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Clarity check
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Structure review
authentic-voice
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Anti-AI pattern removal
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Voice consistency
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Natural language check
Short-Form Accuracy Pass (QUICK)
Each short-form piece gets:
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Data Interpretation Check
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Are trial results stated correctly?
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Are statistics accurately represented?
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Is the study conclusion not misrepresented?
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Are effect sizes/NNT/HR correctly stated?
This is a sanity check, not full review. User can iterate manually.
Skills Invoked
Research Skills
Skill Purpose
knowledge-pipeline
RAG + PubMed synthesis
PubMed MCP Direct paper search
social-media-trends-research
Trending angles
Writing Skills
Skill Content Type Quality Gate
youtube-script-master
YouTube script (Hinglish) Full
cardiology-newsletter-writer
Patient newsletter Full
medical-newsletter-writer
Doctor newsletter Full
cardiology-editorial
Editorial Full
cardiology-writer
Blog post Full
x-post-creator-skill
Tweets Quick
twitter-longform-medical
Thread Quick
Quality Skills
Skill Purpose Used For
scientific-critical-thinking
Evidence rigor Long-form
peer-review
Methodology check Long-form
content-reflection
Pre-publish QA Long-form
authentic-voice
Anti-AI cleanup Long-form
Visual Skills
Skill Purpose
carousel-generator
Instagram slides
cardiology-visual-system
Infographics
Repurposing Skills
Skill Purpose
cardiology-content-repurposer
Backward mode splitting
Output Structure
/output/content-os/[topic-slug]/ ├── research/ │ └── research-brief.md # Foundation for all content │ ├── long-form/ # Full quality pipeline │ ├── youtube-script.md ✓ Quality passed │ ├── newsletter-b2c.md ✓ Quality passed │ ├── newsletter-b2b.md ✓ Quality passed │ ├── editorial.md ✓ Quality passed │ └── blog.md ✓ Quality passed │ ├── short-form/ # Quick accuracy pass │ ├── tweets.md ✓ Accuracy checked │ ├── thread.md ✓ Accuracy checked │ └── snippets.md ✓ Accuracy checked │ ├── visual/ │ ├── carousel/ │ │ └── slide-01.png... │ └── infographic-concepts.md │ └── summary.md # What was produced
Invocation Examples
Forward Mode
"Content OS: GLP-1 agonists cardiovascular benefits" "Content OS: Statin myths for Indian patients" "Content OS: When to get a CAC score" "Content OS: SGLT2 inhibitors in heart failure"
Backward Mode
"Content OS: [paste your 2000-word blog post]" "Content OS: [paste your YouTube script]" "Content OS: [paste your newsletter]"
Configuration
What Gets Produced (Forward Mode)
Content Type Default Can Skip
YouTube Script Yes Yes
Newsletter B2C Yes Yes
Newsletter B2B Yes Yes
Editorial Yes Yes
Blog Yes Yes
Tweets Yes Yes
Thread Yes Yes
Carousel Yes Yes
Customization
"Content OS: Statins - only YouTube and tweets" "Content OS: Heart failure - skip editorial" "Content OS: CAC scoring - long-form only"
Integration with Existing System
Content OS orchestrates skills that already exist in your system. It doesn't replace them - it coordinates them.
You can still use individual skills directly:
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youtube-script-master for just a script
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x-post-creator-skill for just tweets
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carousel-generator for just slides
Content OS is for when you want everything at once.
Notes
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Long-form content takes longer due to quality pipeline
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Short-form is faster (quick accuracy pass only)
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Research phase runs once, shared by all content
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Visual content generated from text output
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All content uses same research foundation for consistency
Voice & Quality Standards
All content follows:
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YouTube: Peter Attia depth + Hinglish (70% Hindi / 30% English)
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Twitter/Writing: Eric Topol Ground Truths style
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B2B (Doctors): JACC editorial voice
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Anti-AI: No "It's important to note", no excessive hedging
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Citations: Q1 journals, specific statistics, NNT/HR/CI when relevant