| name | repurpose |
| description | Content Repurposing Engine. Transforms any content (YouTube videos, blog posts, podcasts, local files, pasted text) into platform-optimized outputs for Twitter/X, Threads, LinkedIn, Instagram, TikTok, Pinterest, Snapchat, Facebook, YouTube Community, Skool, Discord, Reddit, Quora, Medium, WhatsApp Channels, Telegram, and email newsletters. Atomizes content into reusable pieces, adapts brand voice per platform, generates polls, image prompts (via /banana), publishing calendars, and SEO metadata. Triggers on: "repurpose", "content repurpose", "turn into social media", "cross-platform", "content atomization", "repurpose blog", "repurpose video", "turn this into posts", "threads", "pinterest", "snapchat", "discord", "medium", "whatsapp", "telegram".
|
| user-invokable | true |
| argument-hint | [url-or-file] [--platforms X,Y] [--voice casual|professional|witty] [--brief] [--images] |
| license | MIT |
| metadata | {"author":"AgriciDaniel","version":"1.0.0","category":"content"} |
Content Repurposing Engine
Transform any content into platform-optimized outputs across 17+ channels.
Quick Reference
| Command | Description |
|---|
/repurpose <url-or-file> | Full repurpose pipeline (all platforms) |
/repurpose <input> --platforms twitter,linkedin | Repurpose to specific platforms only |
/repurpose <input> --voice casual | Override brand voice (casual/professional/witty) |
/repurpose <input> --brief | Quick mode: 1 post per platform, no calendar |
/repurpose <input> --images | Generate image prompts (or /banana images if available) |
/repurpose analyze <input> | Atomize content only, no platform outputs |
/repurpose calendar <input> | Generate 7-day publishing calendar only |
Step 1: Input Detection
Detect the input type and extract raw content accordingly.
Detection patterns (check in order):
| Pattern | Type | Extraction Method |
|---|
youtube\.com/watch|youtu\.be/|youtube\.com/shorts | YouTube video | Run scripts/extract_transcript.py <url> |
https?:// (any other URL) | Blog/article | Run scripts/extract_article.py <url> |
Path ending in .mp3, .wav, .m4a, .ogg, .flac | Audio file | Run scripts/transcribe_audio.py <path> |
Path ending in .md, .txt, .pdf | Local file | Read file directly with the Read tool |
| No URL or file path detected | Pasted text | Use the inline text as-is |
Extraction rules:
- For YouTube: extract transcript, video title, channel name, description, and duration
- For blog URLs: extract title, author, publication date, body text, and any embedded media descriptions
- For audio: transcribe to text, note duration and any speaker labels
- For local files: read full contents; for PDF use the Read tool with page ranges if large
- For pasted text: use verbatim; ask the user for a title/topic if not obvious
If extraction fails, report the error clearly and ask the user to paste the content directly.
Step 2: Content Atomization
Break the extracted content into 5-15 reusable "atoms." Each atom is a self-contained content unit.
Atom types:
| Type | Description | Example |
|---|
stat | A specific number, percentage, or data point | "73% of marketers repurpose content" |
quote | A quotable sentence or phrase | "Distribution is the new creation." |
insight | A non-obvious takeaway or lesson | "Repurposing beats fresh creation 3:1 on ROI" |
question | A thought-provoking question from the content | "What if you never had to write from scratch again?" |
contrarian | A bold or counterintuitive claim | "Posting less actually grows your audience faster" |
howto | An actionable step or mini-tutorial | "Step 1: Record a 10-min video. Step 2: Extract 8 clips." |
analogy | A comparison that makes the concept click | "Repurposing is composting: old material feeds new growth" |
casestudy | A real example, result, or before/after | "Gary Vee turns one keynote into 35M+ views across platforms" |
prediction | A forward-looking claim or trend | "By 2027, 90% of content will be AI-assisted remixes" |
tldr | The single-sentence summary of the entire piece | Always extract exactly one |
Atomization rules:
- Extract between 5 and 15 atoms (aim for 8-12 for most content)
- Always include at least one
tldr, one insight, and one quote or contrarian
- Label each atom with its type
- Rate each atom's standalone impact from 1-5 (5 = works perfectly as a standalone post)
- Identify the main argument, target audience, and primary topic
- Preserve the original author's voice in quoted atoms
- For longer content (>2000 words), aim for 12-15 atoms; for shorter, 5-8
Atomization output format:
## Content Atoms
**Main Argument:** [one sentence]
**Target Audience:** [who benefits from this content]
**Primary Topic:** [category/niche]
| # | Type | Atom | Impact |
|---|------|------|--------|
| 1 | tldr | ... | 5 |
| 2 | insight | ... | 4 |
| ... | ... | ... | ... |
Step 3: Voice Detection and Adaptation
Default behavior: Detect the brand voice from the source content. Analyze formality, humor level, directness, emotion, and jargon to infer the author's natural voice.
Override flags:
--voice casual — friendlier, more emoji, conversational, contractions--voice professional — formal, data-driven, authoritative, measured--voice witty — personality-forward, clever wordplay, punchy, unexpected angles
Core rule: The brand voice stays consistent across all platforms. Only the TONE adapts per platform. Load references/voice-adaptation.md for the full platform-tone matrix.
Step 4: Orchestration — Spawn 6 Parallel Agents
After atomization, spawn 6 subagents in parallel. Each agent receives:
- The full list of content atoms (with types and impact ratings)
- The main argument, target audience, and primary topic
- The detected or overridden brand voice
- The
--brief flag status (if true, produce 1 post per platform instead of full sets)
- The
--images flag status
Agent 1: repurpose-social
Platforms: Twitter/X, Threads, LinkedIn, Facebook
Receives: All atoms, voice profile, platform specs
Produces:
- Twitter: 1 standalone tweet + 1 thread (8-12 tweets) + 1 poll + image prompt
- Threads: 1 thread (5-10 posts) + 3-5 standalone posts + 1 image post concept
- LinkedIn: 1 text post + 1 carousel outline (8-10 slides) + 1 poll
- Facebook: 1 text post + 1 question post + 1 poll
Sub-skills invoked:
repurpose-twitter, repurpose-threads, repurpose-linkedin, repurpose-facebook
Agent 2: repurpose-visual
Platforms: Instagram, TikTok, Pinterest, Snapchat, Quote cards, Image prompts
Receives: All atoms (especially quotes, stats, insights), voice profile
Produces:
- Instagram: 1 carousel (7-10 slides with copy) + 1 reel script (30-60s) + caption + hashtags
- TikTok: 1 video script (15-60s) + 1 carousel (2-10 slides) + 1 stitch/duet concept
- Pinterest: 3-5 pin descriptions + 1 idea pin script (5-10 slides) + board suggestions
- Snapchat: 1 story script (3-5 frames) + 1 Spotlight script (60s) + AR lens concept
- Quote cards: 3-5 text overlays for image generation
- Image prompts: hero image + carousel cover + 3 quote card prompts
Sub-skills invoked:
repurpose-instagram, repurpose-tiktok, repurpose-pinterest, repurpose-snapchat, repurpose-quotes
Agent 3: repurpose-longform
Platforms: Newsletter, Email sequence, Reddit, Quora
Receives: All atoms, full original content reference, voice profile
Produces:
- Newsletter: subject line + preview text + 200-500 word body
- Email sequence: 3-email drip (day 0, day 2, day 4) with subject lines and CTAs
- Reddit: title + post body adapted to subreddit norms
- Quora: 1 answer (300-1000 words) + 1 Space post + question suggestions
Sub-skills invoked:
repurpose-newsletter, repurpose-reddit, repurpose-quora
Agent 4: repurpose-community
Platforms: YouTube Community, Skool, Discord
Receives: All atoms (especially questions, polls, insights), voice profile
Produces:
- YouTube Community: 1 text post + 1 poll (5 options) + 1 image post concept
- Skool: 1 discussion post + 1 challenge/action post + 1 poll
- Discord: 1 announcement post + 1 discussion thread prompt + 1 embed message
Sub-skills invoked:
repurpose-youtube, repurpose-skool, repurpose-discord
Agent 5: repurpose-seo
Platforms: Cross-platform SEO metadata
Receives: All atoms, main argument, target audience, topic
Produces:
- Primary keywords (3-5) and secondary keywords (5-10)
- Hashtag sets per platform
- SEO title and meta description (for blog/newsletter)
- Alt text suggestions for all generated images
- Schema markup suggestions (Article, VideoObject, FAQPage)
Sub-skills invoked:
repurpose-seo
Agent 6: repurpose-broadcast
Platforms: WhatsApp Channels, Telegram Channels, Medium
Receives: All atoms, full original content reference, voice profile
Produces:
- WhatsApp: 1 channel update (100-300 chars) + 1 poll + 1 content teaser
- Telegram: 1 channel post (500-1000 chars) + 1 deep dive (1000-2000 chars) + 1 poll
- Medium: 1 article (1500-3000 words) + title/subtitle + 5 tags + publication suggestions
Sub-skills invoked:
repurpose-whatsapp, repurpose-telegram, repurpose-medium
Platform filtering
If --platforms is specified, only spawn the agents that cover the requested platforms:
twitter, threads, linkedin, facebook → Agent 1instagram, tiktok, pinterest, snapchat, quotes, images → Agent 2newsletter, email, reddit, quora → Agent 3youtube, skool, discord → Agent 4seo → Agent 5whatsapp, telegram, medium → Agent 6
If a single platform is requested, spawn only the relevant agent.
Step 5: Collect Outputs and Generate Summary
After all agents complete:
- Compile all outputs into the output directory structure (see below)
- Generate images — ALWAYS attempt image generation when /banana is available (do NOT wait for
--images flag). If /banana is unavailable, save prompts to quotes/banana-prompts.md for manual use later
- Generate a summary table showing what was produced per platform
- Generate a 7-day publishing calendar (unless
--brief was used)
- Generate HTML viewer — Run
python3 scripts/generate_html.py <output-dir> to create index.html (dark-themed viewer with Copy buttons per content piece) and all-content.md (single consolidated file with all platform outputs)
- Report to user — Show summary and link to
index.html for easy browsing and copying
Output Directory Structure
./repurposed/<YYYY-MM-DD_HHMMSS>/
summary.md # Overview of all outputs + publishing calendar
atoms.md # Content atomization results
twitter/
standalone-tweet.md
thread.md
poll.md
linkedin/
post.md
carousel.md
poll.md
instagram/
carousel.md
reel-script.md
caption.md
threads/
thread.md
standalone-posts.md
image-post.md
facebook/
post.md
question.md
poll.md
pinterest/
pins.md
idea-pin.md
boards.md
snapchat/
story-script.md
spotlight-script.md
ar-concept.md
youtube-community/
text-post.md
poll.md
image-post.md
skool/
discussion.md
challenge.md
poll.md
discord/
announcement.md
thread-prompt.md
embed.md
tiktok/
video-script.md
carousel.md
stitch-duet.md
reddit/
post.md
quora/
answer.md
space-post.md
questions.md
newsletter/
newsletter.md
email-sequence.md
medium/
article.md
tags-publications.md
crosspost-note.md
whatsapp/
update.md
poll.md
teaser.md
telegram/
post.md
deep-dive.md
poll.md
seo/
keywords.md
hashtags.md
metadata.md
quotes/
quotes.md # 5 quotable moments
banana-prompts.md # /banana prompts (always generated)
images/ # Generated images (auto when /banana available)
quote-card-*.png
carousel-cover.*
hero.*
seo-metadata.md # Cross-platform SEO metadata
all-content.md # MANDATORY: Single consolidated markdown (all platforms)
index.html # MANDATORY: HTML viewer with Copy buttons per content piece
calendar.md # 7-day publishing calendar
MANDATORY OUTPUT: Every /repurpose run MUST produce all-content.md (single file with everything) and index.html (viewer with Copy buttons). Run python3 scripts/generate_html.py <output-dir> as the final step.
Reference Files
Load these references as needed during the pipeline:
| File | When to Load |
|---|
references/platform-specs.md | Always — before generating any platform output |
references/hook-formulas.md | When writing hooks, headlines, thread openers, email subjects |
references/voice-adaptation.md | After voice detection, before generating any output |
references/repurposing-frameworks.md | During atomization and calendar generation |
references/poll-strategy.md | When generating polls for any platform |
references/image-sourcing.md | When sourcing images (3-tier: website → stock → AI) |
references/mistakes-to-avoid.md | Quality check pass before finalizing outputs |
references/engagement-benchmarks.md | Calendar generation, engagement predictions |
Sub-Skills
| Sub-Skill | Platform | Key Output |
|---|
repurpose-twitter | Twitter/X | Standalone tweet, thread, poll |
repurpose-threads | Threads | Thread, standalone posts, image post |
repurpose-linkedin | LinkedIn | Text post, carousel, poll |
repurpose-instagram | Instagram | Carousel, reel script, caption |
repurpose-tiktok | TikTok | Video script, carousel, stitch/duet concept |
repurpose-pinterest | Pinterest | Pin descriptions, idea pin, board suggestions |
repurpose-snapchat | Snapchat | Story script, Spotlight script, AR concept |
repurpose-facebook | Facebook | Post, question, poll |
repurpose-youtube | YouTube Community | Text post, poll, image concept |
repurpose-skool | Skool | Discussion, challenge, poll |
repurpose-discord | Discord | Announcement, thread prompt, embed |
repurpose-reddit | Reddit | Subreddit-adapted post |
repurpose-quora | Quora | Answer, Space post, question suggestions |
repurpose-medium | Medium | Article, tags/publications, crosspost note |
repurpose-whatsapp | WhatsApp | Channel update, poll, teaser |
repurpose-telegram | Telegram | Channel post, deep dive, poll |
repurpose-newsletter | Email | Newsletter, 3-email drip |
repurpose-quotes | Visual | Quote cards, text overlays |
repurpose-seo | Cross-platform | Keywords, hashtags, metadata |
repurpose-calendar | Scheduling | 7-day publishing calendar |
Image Sourcing Pipeline — 3-Tier System
Images are sourced automatically for every platform. The pipeline follows a 3-tier priority chain.
Tier 1: Website Images (if input is a URL)
When the input is a blog post or article URL, extract_article.py extracts images from the page.
- Use
scripts/fetch_images.py --article-images to filter: skip logos, icons, avatars, ads, SVGs, < 400px
- Rank by keyword overlap with content atoms
- These are the MOST relevant — they came from the source content itself
Tier 2: Stock Photos (Pixabay → Unsplash → Pexels)
Search for topic-relevant images via WebSearch:
site:pixabay.com [topic keywords] wide professional (preferred, no attribution required)site:unsplash.com [topic keywords] professional (resize params supported)site:pexels.com [topic keywords] high quality (fallback)- Extract direct CDN URLs from results
- Verify each URL with HEAD request before using
- Target: 3-5 relevant images
Tier 3: AI-Generated (Gemini via /banana)
- ALWAYS for quote cards (text overlay requires custom design)
- ALWAYS for carousel covers with title text
- FALLBACK when Tiers 1-2 produce < 3 suitable images
- Uses 6-Component Brief: Subject → Action → Context → Composition → Lighting → Style
- Load
references/image-sourcing.md for templates and platform dimensions
Execution Order
- Check if input URL has images → extract and filter (Tier 1)
- Generate stock photo queries → use WebSearch to find Pixabay/Unsplash/Pexels images (Tier 2)
- Count total images found. If < 3 usable, generate more via /banana (Tier 3)
- ALWAYS generate 5 quote cards via /banana (or save prompts if unavailable)
- Save all images to
./repurposed/<timestamp>/images/
- Include image URLs/paths in platform output files
/banana Detection
Check for gemini_generate_image MCP tool OR ~/.claude/skills/banana/SKILL.md OR GOOGLE_API_KEY env var.
- Available: generate images automatically
- Not available: save all prompts to
quotes/banana-prompts.md for manual generation later
Error Handling
| Error | Resolution |
|---|
| YouTube transcript unavailable | Ask user to paste transcript or provide alternate URL |
| Blog URL returns 403/404 | Ask user to paste article text directly |
| Audio transcription fails | Check file format; suggest converting to .wav or .mp3 |
| Extraction script not found | Fall back to WebFetch for URLs; Read for local files |
| Platform not recognized | Show supported platforms list; suggest closest match |
| Content too short (<100 words) | Warn user; reduce atom target to 3-5; skip thread/carousel |
| Content too long (>10,000 words) | Chunk into sections; atomize each; merge top atoms |
| /banana not available | Generate prompts only; note in summary |
| Output directory write fails | Fall back to printing all outputs inline |
| Voice detection ambiguous | Default to professional; note in summary |
Subcommand: analyze
Usage: /repurpose analyze <url-or-file>
Runs only Steps 1-2 (input detection + atomization). Does NOT generate platform outputs.
Output:
- Content atoms table with types and impact ratings
- Main argument, target audience, primary topic
- Recommended platforms based on content type
- Suggested voice profile
- Atom count and quality assessment
Use this to preview what the engine extracts before committing to full repurposing.
Subcommand: calendar
Usage: /repurpose calendar <url-or-file>
Runs Steps 1-2 (extraction + atomization), then generates a 7-day publishing calendar.
Calendar rules:
- Monday: Long-form (newsletter or Reddit post)
- Tuesday: Thread (Twitter) + Carousel (LinkedIn)
- Wednesday: Quote cards + Instagram carousel
- Thursday: Polls across all platforms
- Friday: Newsletter send or email drip start
- Saturday: YouTube Community + Skool posts
- Sunday: Stories + light engagement posts (Facebook question, Skool discussion)
Calendar output includes:
- Day-by-day schedule with platform, content type, and which atom(s) to use
- Suggested posting times per platform (from platform-specs.md)
- Dependencies (e.g., "Tuesday carousel requires Monday's images")
- Total pieces count
Output: Saved to ./repurposed/<timestamp>/calendar.md and printed to console.
Execution Flow Summary
User input
|
v
[1] Detect input type (URL/file/text)
|
v
[2] Extract raw content (script or Read)
|
v
[3] Atomize into 5-15 labeled atoms
|
v
[4] Detect or apply voice profile
|
v
[5] Spawn 6 agents in parallel:
|-- repurpose-social (Twitter + Threads + LinkedIn + Facebook)
|-- repurpose-visual (Instagram + TikTok + Pinterest + Snapchat + Quotes)
|-- repurpose-longform (Newsletter + Email + Reddit + Quora)
|-- repurpose-community (YouTube Community + Skool + Discord)
|-- repurpose-seo (Keywords + Hashtags + Metadata)
|-- repurpose-broadcast (WhatsApp + Telegram + Medium)
|
v
[6] Collect all outputs → write to ./repurposed/<timestamp>/
|
v
[7] Generate summary table + 7-day calendar
|
v
[8] Report results to user
