content-repurposer

name	content-repurposer
description	Transform long-form content into multiple short-form pieces. Use when: converting podcast to social posts; extracting Twitter threads from blog posts; pulling quotes from transcripts; creating content variants from single source
license	MIT
metadata	{"author":"ClawFu","version":"1.0.0","mcp-server":"@clawfu/mcp-skills"}

Content Repurposer

Turn one piece of content into 10+ pieces using AI-powered extraction and reformatting - the "create once, publish everywhere" workflow.

When to Use This Skill

• Podcast repurposing - Convert episode transcripts to threads, posts, quotes
• Blog distribution - Transform articles into LinkedIn posts, Twitter threads
• Video content recycling - Extract quotable moments and insights
• Newsletter content - Generate social snippets from weekly newsletters
• Webinar follow-up - Create post-event content from recordings

What Claude Does vs What You Decide

Claude Does	You Decide
Structures production workflow	Final creative direction
Suggests technical approaches	Equipment and tool choices
Creates templates and checklists	Quality standards
Identifies best practices	Brand/voice decisions
Generates script outlines	Final script approval

Dependencies

pip install anthropic jinja2 click pyyaml
# Requires ANTHROPIC_API_KEY environment variable

Commands

Multi-Format Repurpose

python scripts/main.py repurpose transcript.txt --formats "twitter,linkedin,instagram"
python scripts/main.py repurpose blog-post.md --formats all

Twitter Thread

python scripts/main.py thread article.md --max-tweets 10
python scripts/main.py thread transcript.txt --style educational

Quote Extraction

python scripts/main.py quotes podcast-transcript.txt --count 5
python scripts/main.py quotes interview.txt --style inspirational

Hook Generation

python scripts/main.py hooks content.txt --count 10
python scripts/main.py hooks product-page.txt --style curiosity

Examples

Example 1: Podcast Episode → Full Content Suite

# Input: 45-minute podcast transcript
python scripts/main.py repurpose episode-42-transcript.txt --formats all

# Output directory: episode-42-transcript_repurposed/
# ├── twitter_thread.md (10-tweet thread)
# ├── linkedin_post.md (long-form post)
# ├── instagram_carousel.md (10 slides)
# ├── quotes.md (5 quotable moments)
# └── hooks.md (5 attention grabbers)

Example 2: Blog Post → Twitter Thread

# Convert 2000-word article to thread
python scripts/main.py thread positioning-strategy.md --max-tweets 12 --style educational

# Output: positioning-strategy_thread.md
# 1/ Here's how the best B2B companies position themselves (thread)
# 2/ First, they identify their competitive alternatives...
# ...
# 12/ TL;DR: Position for differentiation, not features. Link in bio.

Example 3: Extract Quotable Moments

# Pull shareable quotes from interview
python scripts/main.py quotes founder-interview.txt --count 10 --style inspirational

# Output: founder-interview_quotes.md
# 1. "We didn't build a product, we built a belief system."
# 2. "Your first 100 customers should feel like co-founders."
# ...

Output Formats

Format	Best For	Typical Length
twitter	Thread with numbered tweets	8-15 tweets
linkedin	Long-form professional post	1,200-1,500 chars
instagram	Carousel slide content	10 slides
quotes	Shareable quote graphics	5-10 quotes
hooks	Opening lines for posts	10 hooks
summary	Executive summary	200-300 words
newsletter	Email-friendly summary	500-800 words

Content Styles

Style	Tone	Use Case
educational	Teaching, explaining	Tutorials, how-tos
inspirational	Motivating, uplifting	Founder stories
provocative	Challenging assumptions	Thought leadership
conversational	Casual, relatable	Personal brand
professional	Formal, authoritative	B2B, enterprise

How It Works

1. Content Analysis - AI reads full content, identifies key themes
2. Format Adaptation - Restructures for each platform's constraints
3. Hook Generation - Creates attention-grabbing openings
4. Quote Extraction - Pulls most shareable moments
5. Consistency Check - Ensures message alignment across formats

Best Practices

1. Start with transcripts - Raw transcripts work better than polished content
2. Review hooks - AI-generated hooks need human judgment
3. Edit threads - Check flow between tweets
4. Add context - AI can't know your audience's inside jokes
5. Test variations - Generate multiple versions, pick the best

Skill Boundaries

What This Skill Does Well

• Structuring audio production workflows
• Providing technical guidance
• Creating quality checklists
• Suggesting creative approaches

What This Skill Cannot Do

• Replace audio engineering expertise
• Make subjective creative decisions
• Access or edit audio files directly
• Guarantee commercial success

Related Skills

• whisper-transcription - Create transcripts to repurpose
• youtube-downloader - Get video content to repurpose
• copywriting-schwartz - Improve repurposed copy

Skill Metadata

• Mode: cyborg

category: automation
subcategory: content-automation
dependencies: [anthropic, jinja2]
difficulty: beginner
time_saved: 8+ hours/week
api_cost: ~$0.02-0.10 per repurpose