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 brainbytes-dev/everything-claude-marketing --skill content-repurposinggit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-marketingWrote 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/brainbytes-dev/everything-claude-marketing/content-repurposing)<a href="https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/content-repurposing"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/content-repurposing/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/brainbytes-dev/everything-claude-marketing/content-repurposing"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/content-repurposing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00026 | $0.02219 |
| Opus 5.5 | $0.00010 | $0.00888 |
| Sonnet 5.5 | $0.00005 | $0.00444 |
| Haiku 4.5 | $0.00003 | $0.00222 |
Grade A, and why
content-repurposing 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 2mo 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 — 217 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Repurposing
When to Activate
- A high-effort content piece (guide, webinar, report) is created and needs maximum distribution
- The content team is under-resourced but needs to maintain multi-channel presence
- Content performance data shows strong pieces that deserve broader reach
- Building a multi-channel content program from limited original production
- Existing content library has untapped value in alternative formats
- Stakeholders ask for "more content" without additional budget or headcount
First Questions
- What is the source content? (Blog, webinar, podcast, research, presentation, video?)
- Which channels need to be fed? (Social, email, blog, video, podcast, community?)
- What formats does your audience engage with most on each channel?
- Do you have design/video production resources, or is repurposing mostly text-based?
- What is the shelf life of this content? (Evergreen vs time-sensitive?)
- What is the key message or insight that should persist across all formats?
- How much time can be allocated to repurposing vs original creation?
The Repurposing Cascade
Start with the highest-effort, most comprehensive content asset and cascade down:
TIER 1: Pillar Content (highest effort, deepest value)
│ Long-form blog guide, webinar, research report, podcast interview
│
├── TIER 2: Mid-Form Derivatives
│ ├── Blog post (if source was non-blog)
│ ├── Newsletter deep-dive
│ ├── LinkedIn article
│ ├── YouTube video or Loom walkthrough
│ └── Slide deck / presentation
│
├── TIER 3: Short-Form Derivatives
│ ├── Social media posts (5-10 per source)
│ │ ├── Key stat or data point
│ │ ├── Pull quote
│ │ ├── Hot take or opinion
│ │ ├── "Did you know?" fact
│ │ └── Question to spark discussion
│ ├── Email snippet or teaser
│ ├── Infographic or visual summary
│ └── Short video clip (60 seconds or less)
│
└── TIER 4: Micro-Content & Engagement
├── Social poll based on a finding
├── Community discussion prompt
├── Internal Slack share for employee advocacy
├── Sales enablement snippet
└── FAQ entry or help doc update
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.
- 2mo ago First seen · 217 lines · 26 tokens per session scan A 182e7e907a28
content-repurposing is a skill published in the GitHub repository brainbytes-dev/everything-claude-marketing (10 stars, last pushed 7mo ago), licensed MIT. It adds 26 tokens to every session and 2,219 once invoked, about $0.0001 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.
content-repurposing compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| content-repurposingbrainbytes-dev/everything-claude-marketing | Skill | 10 | 7mo ago | MIT | A | 26 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |