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 thesongzhu/Friday --skill content-repurposing-enginegit clone --depth 1 https://github.com/thesongzhu/FridayWrote 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/thesongzhu/friday/content-repurposing-engine)<a href="https://agentmods.dev/skills/thesongzhu/friday/content-repurposing-engine"><img src="https://agentmods.dev/badge/skills/thesongzhu/friday/content-repurposing-engine/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/thesongzhu/friday/content-repurposing-engine"><img src="https://agentmods.dev/badge/skills/thesongzhu/friday/content-repurposing-engine.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 | $0.00000 | $0.00160 |
| Opus 5 | $0.00000 | $0.00080 |
| Sonnet 5 | $0.00000 | $0.00032 |
| Haiku 4.5 | $0.00000 | $0.00016 |
Grade A, and why
content-repurposing-engine 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 9d 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.
What it actually says
Content Repurposing Engine
Converts long-form content into multiple formats like social media threads, short video scripts, or summaries while preserving the core message.
Features
- Extracts key ideas from source content
- Adapts output for specific platforms
- Maintains tone and clarity across formats
Instructions
- Analyze original content
- Identify key points and core message
- Rewrite in the target format
- Keep consistent tone and readability
- Output platform-specific content with engaging headlines/hooks
Constraints
- Preserve original meaning
- Avoid verbosity
- Format must match target channel style
Typical triggers:
repurpose this contentturn this article into a twitter threadconvert this blog post for social mediaadapt this for multiple platforms
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.
- 9d ago First seen · 31 lines · 0 tokens per session scan A 77c011c0fd2d
content-repurposing-engine is a skill published in the GitHub repository thesongzhu/Friday (838 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 160 tokens. 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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