Agent skill

Repurpose

by AgriciDaniel in AgriciDaniel/claude-repurpose

Content Repurposing Engine. An agent skill from AgriciDaniel/claude-repurpose.

Install Repurpose

skills CLI

$ npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install AgriciDaniel/claude-repurpose repurpose --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/AgriciDaniel/claude-repurpose.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/repurpose .claude/skills/repurpose && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "repurpose" agent skill from https://github.com/AgriciDaniel/claude-repurpose/tree/main/skills/repurpose into .claude/skills/repurpose/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "repurpose", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/AgriciDaniel/claude-repurpose/tree/main/skills/repurpose

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install AgriciDaniel/claude-repurpose repurpose --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AgriciDaniel/claude-repurpose.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/repurpose .agents/skills/repurpose && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "repurpose" agent skill from https://github.com/AgriciDaniel/claude-repurpose/tree/main/skills/repurpose into .agents/skills/repurpose/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "repurpose", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install AgriciDaniel/claude-repurpose repurpose --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AgriciDaniel/claude-repurpose.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/repurpose .cursor/skills/repurpose && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "repurpose" agent skill from https://github.com/AgriciDaniel/claude-repurpose/tree/main/skills/repurpose into .cursor/skills/repurpose/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "repurpose", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/AgriciDaniel/claude-repurpose.git --path skills/repurpose

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install AgriciDaniel/claude-repurpose repurpose --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AgriciDaniel/claude-repurpose.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/repurpose .gemini/skills/repurpose && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "repurpose" agent skill from https://github.com/AgriciDaniel/claude-repurpose/tree/main/skills/repurpose into .gemini/skills/repurpose/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "repurpose", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install AgriciDaniel/claude-repurpose repurpose

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/AgriciDaniel/claude-repurpose.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/repurpose .github/skills/repurpose && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "repurpose" agent skill from https://github.com/AgriciDaniel/claude-repurpose/tree/main/skills/repurpose into .github/skills/repurpose/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "repurpose", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install AgriciDaniel/claude-repurpose repurpose --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/AgriciDaniel/claude-repurpose.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/repurpose .opencode/skills/repurpose && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "repurpose" agent skill from https://github.com/AgriciDaniel/claude-repurpose/tree/main/skills/repurpose into .opencode/skills/repurpose/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "repurpose", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: repurpose
GitHub stars: 155
Token cost: ~5.1k tokens
SKILL.md length: 1,979 words
Files: 9 (incl. references)
Skills in repo: 21
Repo updated: Apr 10, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Content Repurposing Engine. An agent skill from AgriciDaniel/claude-repurpose.

Works in 5 steps: Input Detection → Content Atomization → Voice Detection and Adaptation → …
Content repurpose
SKILL.md covers Quick Reference, Step 1: Input Detection, Step 2: Content Atomization and Step 3: Voice Detection and…, plus 9 more sections
Calls python3; needs GOOGLE_API_KEY

What it does

Repurpose is an agent skill from AgriciDaniel/claude-repurpose. 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…

Its SKILL.md is about 5.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files, including reference files (for example `references/engagement-benchmarks.md`, `references/hook-formulas.md` and `references/image-sourcing.md`).

It sits in Writing & Content, covering Content repurposing. It works with YouTube, Discord, Pinterest and Telegram. The repository describes itself as: Content Repurposing Engine for Claude Code. Turn 1 piece of content into 10+ platform-optimized posts for Twitter, LinkedIn, Instagram, Facebook, YouTube, Skool, Reddit, and… The licence is MIT.

When your agent uses it

Content repurpose
Turn into social media
Content atomization
Repurpose video

Example prompts

“repurpose”
“content repurpose”
“turn into social media”
“/repurpose”

Requirements

Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

Input Detection
Content Atomization
Voice Detection and Adaptation
Orchestration — Spawn 6 Parallel Agents
Collect Outputs and Generate Summary

What it can do on your machine

Read from SKILL.md and the folder at commit 669187e. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- GOOGLE_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Repurpose loads about 5.1k tokens when it runs, and up to ~19k if it reads all its reference files. Until then it costs about 191 tokens; SKILL.md has 1,979 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~191
When it runs · the whole SKILL.md, loaded when a task matches: ~5.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them: ~19k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from AgriciDaniel/claude-repurpose at commit 669187e, republished under its MIT licence (© AgriciDaniel). 1,979 words, ~5,060 tokens.

Download SKILL.mdSave it as .claude/skills/repurpose/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.

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
metadata.version: 1.0.0
metadata.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 1
instagram, tiktok, pinterest, snapchat, quotes, images → Agent 2
newsletter, email, reddit, quora → Agent 3
youtube, skool, discord → Agent 4
seo → Agent 5
whatsapp, 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

Show full SKILL.md (780 more words)Show less

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

Files

SKILL.md and 8 other files (references) in skills/repurpose of AgriciDaniel/claude-repurpose.

SKILL.md
references/engagement-benchmarks.md
references/hook-formulas.md
references/image-sourcing.md
references/mistakes-to-avoid.md
references/platform-specs.md
references/poll-strategy.md
references/repurposing-frameworks.md
references/voice-adaptation.md

Open the folder on GitHubat commit 669187e

Compare with similar skills

Repurpose next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Repurpose compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Repurpose this skillAgriciDaniel/claude-repurpose	155	—	~5.1k	Automated safety check: Pass	MIT	5 mo ago
Content Repurposer Smsblacktwist/social-media-skills	557	—	~3.7k	Automated safety check: Pass	MIT	5 mo ago
Social Media Managementmanojbajaj95/claude-gtm-plugin	104	1 repos	~3.9k	Automated safety check: Pass	MIT	19 days ago
Creating Letta Code Channelsletta-ai/skills	147	—	~1.1k	Automated safety check: Pass	MIT	5 days ago
Idea Extractoraiskilloftheweek/claude-ai-skill-of-the-week	145	—	~1.5k	Automated safety check: Pass	None	4 mo ago
Hook Writer Smsblacktwist/social-media-skills	557	—	~3.7k	Automated safety check: Pass	MIT	5 mo ago

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Repurpose Calendar
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Repurpose Discord
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Repurpose Facebook
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Repurpose Instagram
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Repurpose Linkedin
AgriciDaniel/claude-repurpose
Generates LinkedIn content from content atoms: text posts with hook-first formatting, PDF carousel slide scripts (10-12 slides), and strategic polls.
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Repurpose Medium
AgriciDaniel/claude-repurpose
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Works with

Questions about Repurpose

What does Repurpose do?

Content Repurposing Engine. An agent skill from AgriciDaniel/claude-repurpose. Repurpose is an agent skill from AgriciDaniel/claude-repurpose. Content Repurposing Engine.

When should I use Repurpose?

Repurpose fits situations like: content repurpose; turn into social media; content atomization; repurpose video.

How do I install Repurpose in Claude Code?

Run `npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a claude-code`. Or copy the skill folder (skills/repurpose in AgriciDaniel/claude-repurpose) into .claude/skills/repurpose in your project. Claude Code loads it when a task matches its description.

How do I install Repurpose in Codex?

Run `npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a codex`. Or copy the skill folder (skills/repurpose in AgriciDaniel/claude-repurpose) into .agents/skills/repurpose in your project. Codex loads it when a task matches its description.

Can I use Repurpose in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add AgriciDaniel/claude-repurpose --skill repurpose -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/repurpose, .gemini/skills/repurpose, .github/skills/repurpose and .opencode/skills/repurpose in your project.

What does Repurpose need to run?

Going by SKILL.md and its folder, Repurpose needs the command-line tools its instructions call (python3) and credentials named GOOGLE_API_KEY. Our summary lists: Python 3.

Does Repurpose access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Repurpose safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Repurpose use?

Repurpose is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Repurpose use?

About 5.1k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 14k tokens, read only when the agent opens those files.

What are the alternatives to Repurpose?

Skills that share tags, products or a category with Repurpose: Content Repurposer Sms (blacktwist/social-media-skills, 557 stars), Social Media Management (manojbajaj95/claude-gtm-plugin, 104 stars), Creating Letta Code Channels (letta-ai/skills, 147 stars) and Idea Extractor (aiskilloftheweek/claude-ai-skill-of-the-week, 145 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Repurpose?

AgriciDaniel (a GitHub user) maintains it in AgriciDaniel/claude-repurpose, which has 155 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on April 10, 2026.

Source: AgriciDaniel/claude-repurpose on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Repurpose

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

Content Repurposing Engine

Quick Reference

Step 1: Input Detection

Step 2: Content Atomization

Step 3: Voice Detection and Adaptation

Step 4: Orchestration — Spawn 6 Parallel Agents

Agent 1: repurpose-social

Agent 2: repurpose-visual

Agent 3: repurpose-longform

Agent 4: repurpose-community

Agent 5: repurpose-seo

Agent 6: repurpose-broadcast

Platform filtering

Step 5: Collect Outputs and Generate Summary

Output Directory Structure

Reference Files

Sub-Skills

Image Sourcing Pipeline — 3-Tier System

Tier 1: Website Images (if input is a URL)

Tier 2: Stock Photos (Pixabay → Unsplash → Pexels)

Tier 3: AI-Generated (Gemini via /banana)

Execution Order

/banana Detection

Error Handling

Subcommand: analyze

Subcommand: calendar

Execution Flow Summary

Files

Compare with similar skills

Similar skills

More from AgriciDaniel/claude-repurpose

Related

Questions about Repurpose

Agent 1: `repurpose-social`

Agent 2: `repurpose-visual`

Agent 3: `repurpose-longform`

Agent 4: `repurpose-community`

Agent 5: `repurpose-seo`

Agent 6: `repurpose-broadcast`

Subcommand: `analyze`

Subcommand: `calendar`