Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add superamped/ai-marketing-skills --skill content-repurposergit clone --depth 1 https://github.com/superamped/ai-marketing-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/superamped/ai-marketing-skills/content-repurposer)<a href="https://agentmods.dev/skills/superamped/ai-marketing-skills/content-repurposer"><img src="https://agentmods.dev/badge/skills/superamped/ai-marketing-skills/content-repurposer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/superamped/ai-marketing-skills/content-repurposer"><img src="https://agentmods.dev/badge/skills/superamped/ai-marketing-skills/content-repurposer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.02160 |
| Opus 5 | $0.00030 | $0.01080 |
| Sonnet 5 | $0.00012 | $0.00432 |
| Haiku 4.5 | $0.00006 | $0.00216 |
Grade A, and why
content-repurposer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 310 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Repurposer
Usage
Use when you've just published a newsletter or blog post and need social content to promote and extend it, repurposing a podcast episode or YouTube video transcript, or getting a full week of social posts from one piece of long-form content.
Process
Step 1: Gather Inputs
Ask the user for:
- Long-form content — the hub piece. Can be:
- A newsletter issue (pasted or file path)
- A blog post (pasted, file path, or URL to fetch)
- A podcast/video transcript
- A research doc or set of notes
- Target platform (optional) — LinkedIn, Twitter/X, or both (default: both)
- Voice/tone — what the brand voice sounds like (casual, professional, witty, etc.)
- Target audience — who follows them on social
- Newsletter/content link (optional) — URL to link back to in CTA posts
- Subscriber/reader count (optional) — for social proof in CTA posts
- Number of spokes (optional) — default: 5 (one per template)
- Constraints (optional) — things to avoid, compliance requirements
Step 2: Extract the Core from the Hub
Read the long-form content and extract:
- Main thesis — the one big idea in one sentence
- Key takeaways — 3-7 specific, actionable points
- Supporting stories — personal anecdotes, examples, or case studies
- Data/proof points — any numbers, stats, or results mentioned
- Contrarian or surprising elements — anything that challenges conventional thinking
- Tools/resources mentioned — any recommendations, links, or references
Present this extraction to the user as a summary before generating spokes. This ensures nothing important is missed.
Step 3: Generate Spoke Posts
Create one post for each of the spoke templates:
Template 1: Story
Tell a narrative that leads to the hub's key insight.
Structure:
- Pain/Attention — Open with a personal story or relatable problem
- Agitate — Show how things got worse
- Intrigue — Introduce a turning point
- Positive Future — Show the benefits
- Solution — Bring clarity with a specific action or resource
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 310 lines · 59 tokens per session scan A 85f42d81b5da
content-repurposer is a skill published in the GitHub repository superamped/ai-marketing-skills (67 stars, last pushed 25d ago), licensed MIT. It adds 59 tokens to every session and 2,160 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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