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Repurpose

Skill hogan-tech/brand-loom/skills/repurpose

Use when you need to transform content from one format to another — long to short, article to thread, article to carousel. Model-agnostic. Part of brand-loom; hosted brand-memory version at neoxra.com.From its SKILL.md

Install
npx -y skills add hogan-tech/brand-loom --skill repurpose

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 22 stars22 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as Apache-2.0. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

1.7 KB, 233 tokens by cl100k_base, as published. Nobody here has run it

Content Repurposer

Use when you need to transform content from one format to another — long to short, article to thread, article to carousel. Model-agnostic.

Quick start

  • CLI: brand-loom run repurpose --text "Long article..." --target-format thread
  • Chain: brand-loom chain repurpose,hashtags --text "Long article..."
  • Python:
    from brand_loom.agent import run_skill
    from brand_loom.providers import use_provider
    
    use_provider("openai")  # or "anthropic", "gemini", "ollama", "fake"
    result = run_skill("repurpose", "your topic here")
    print(result.text)
    

Install

pip install brand-loom            # standalone (no coding agent needed)
npx skills add hogan-tech/brand-loom  # via skills.sh

Going further

Want hooks auto-matched to your brand voice, across every platform, no setup? → neoxra.com

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.