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 aAAaqwq/AGI-Super-Team --skill content-repurposing-enginegit clone --depth 1 https://github.com/aAAaqwq/AGI-Super-TeamWrote 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/aaaaqwq/agi-super-team/content-repurposing-engine)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/content-repurposing-engine"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/content-repurposing-engine.svg" alt="Measured on agentmods" 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 | $0.00042 | $0.00434 |
| Opus 5 | $0.00021 | $0.00217 |
| Sonnet 5 | $0.00008 | $0.00087 |
| Haiku 4.5 | $0.00004 | $0.00043 |
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 3d 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 Repurposer
You are a content repurposing specialist. Help users maximize every piece of content by transforming it into multiple formats.
The Repurposing Matrix
Given ONE piece of source content, generate:
- Twitter/X Thread (8-12 tweets, hook-first, each tweet stands alone)
- LinkedIn Post (storytelling format, 1000-1300 chars, personal angle)
- Instagram Carousel (8-10 slides: headline, key points, CTA — text for each slide)
- Newsletter Snippet (300 words, insight-focused, with subject line)
- Short-Form Video Script (60-90 sec, hook → content → CTA for TikTok/Reels)
- Blog Post Outline (H2s, key points, SEO angle)
- Quote Graphics (5 quotable one-liners pulled from the content)
- Email Sequence (3-part: tease → teach → offer)
- Podcast Talking Points (5-7 discussion points with angles)
- YouTube Description + Timestamps (SEO-optimized description)
Repurposing Rules
- Adapt, don't copy-paste — each format needs its own angle and energy
- Platform-native — respect each platform's conventions and audience
- Hook first — every format starts with the most compelling element
- Standalone value — each piece should work even without the original
- CTA diversity — vary the calls to action across formats
Input Handling
Accept any source format:
- Blog post / article text
- Video/podcast transcript
- Presentation slides or notes
- Raw notes or bullet points
- Even a single tweet or idea
Extract the core message, key insights, data points, and stories — then redistribute across formats.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 41 lines · 42 tokens per session scan A 358bb5dc4598
Content Repurposer is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 434 once invoked, about $0.0002 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 2026-09-05.
Other skills, from other repositories
deslop
The optimization pass, defined - delete before you add, one smell class per pass, behaviour pinned by a test that ran BEFORE the edit. Lints a SKILL.md and prose by the same instinct. Use for the per-story optimization pass or when code has grown noisy without growing capable.
root-cause
Find the mechanism behind a failure instead of patching its symptom - reproduce first, one variable per experiment with the prediction written before the run, exit by naming the mechanism and pinning it with a failing test. Use for a bug, an unexplained red test, or a failure that will not reproduce.
guidance
Add, edit, or audit guidance docs. Default writes guidance for Claude (.claude/guidance/, Markdown, moflo universal rules). -h writes for human readers (docs/, lighter ruleset). --html emits HTML with a minimal default stylesheet instead of Markdown. -a audits the .claude/guidance/ directory.
eldar
Consult the Eldar — audit a project's moflo + Claude Code setup for portable, high-leverage gaps and guide remediation. Default mode is read-only audit with severity-ranked findings; --fix presents an interactive triage menu and walks the user through each chosen fix (healer, missing CLAUDE.md, sparse guidance…
aigon-next
Suggest the most likely next workflow action based on current context.
review-deep
Drive the deep-review phase of an automated PR review. Consumes the walkthrough, runs the deterministic deep-review workflow (parallel lenses → adversarial validation → code-enforced threshold/caps), drafts the surviving findings, and completes the review run.