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 travisjneuman/.claude --skill content-repurposergit clone --depth 1 https://github.com/travisjneuman/.claudeWrote 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/travisjneuman/.claude/content-repurposer)<a href="https://agentmods.dev/skills/travisjneuman/.claude/content-repurposer"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/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/travisjneuman/.claude/content-repurposer"><img src="https://agentmods.dev/badge/skills/travisjneuman/.claude/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 | $0.00043 | $0.02389 |
| Opus 5.5 | $0.00017 | $0.00956 |
| Sonnet 5.5 | $0.00009 | $0.00478 |
| Haiku 4.5 | $0.00004 | $0.00239 |
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 1mo 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 — 329 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Repurposer
Frameworks for systematically transforming content across formats, platforms, and audiences while maintaining message integrity and maximizing reach.
Content Transformation Matrix
Platform-Specific Formats
| Source Format | Twitter/X | Newsletter | Blog | Podcast Notes | ||
|---|---|---|---|---|---|---|
| Blog post | Thread (5-10 tweets) | Article excerpt + CTA | Carousel (5-10 slides) | Summary + link | N/A | Episode outline |
| Research report | Key stat tweets | Executive summary | Infographic | Top findings | Summary article | Discussion points |
| Presentation | Quote cards | Slide highlights | Carousel | Key takeaways | Written recap | Interview format |
| Video/Webinar | Clip highlights | Key moments + transcript | Reels/clips | Timestamps + summary | Full transcript post | Audio extract |
| Case study | Results thread | Before/after story | Testimonial graphic | Customer spotlight | Full narrative | Interview episode |
| Data/Report | Single stat graphics | Analysis + chart | Data visualization | Trend commentary | Deep dive analysis | Data storytelling |
Transformation Workflow
CONTENT REPURPOSING PIPELINE:
1. AUDIT SOURCE CONTENT
- Identify core message (1 sentence)
- Extract key data points (3-5 stats)
- List supporting arguments (3-5 points)
- Note quotable phrases
- Identify visual elements
2. MAP TARGET PLATFORMS
For each platform, define:
- Format constraints (character limits, dimensions)
- Audience expectations (tone, depth, style)
- Best posting times
- CTA appropriate for platform
- Hashtag/keyword strategy
3. TRANSFORM CONTENT
- Adapt tone to platform voice
- Restructure for format requirements
- Add platform-native elements (polls, carousels, threads)
- Optimize headlines/hooks for each platform
- Create platform-specific CTAs
4. SCHEDULE AND DISTRIBUTE
- Stagger releases (don't post everywhere simultaneously)
- Primary platform first, then secondary
- Monitor performance per platform
- Iterate based on engagement data
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.
- 1mo ago First seen · 329 lines · 43 tokens per session scan A 2937ac3563e3
content-repurposer is a skill published in the GitHub repository travisjneuman/.claude (106 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 2,389 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-03.
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