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-rewritergit 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-rewriter)<a href="https://agentmods.dev/skills/aaaaqwq/agi-super-team/content-rewriter"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/content-rewriter/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/aaaaqwq/agi-super-team/content-rewriter"><img src="https://agentmods.dev/badge/skills/aaaaqwq/agi-super-team/content-rewriter.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 | $0.00037 | $0.00490 |
| Opus 5 | $0.00018 | $0.00245 |
| Sonnet 5 | $0.00007 | $0.00098 |
| Haiku 4.5 | $0.00004 | $0.00049 |
Grade A, and why
content-rewriter 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 4d 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 Rewriter — 内容多平台改写器
Repurpose one piece of content across multiple platforms with native formatting.
When to Activate
Trigger when the user mentions: 改写, rewrite, 转载, cross-post, 多平台分发, repurpose, 内容复用.
Workflow
- Accept original content + list of target platforms
- Rewrite for each target platform independently
Rewriting Rules
→ 小红书 (from any platform)
- Shorten to 300-800 characters
- Add emoji every 2-3 sentences
- Title: "number + keyword + emoji" format
- Short paragraphs (1-3 sentences each)
- Add 5-10 hashtags
- Tone: bestie sharing / personal experience
→ 知乎 (from any platform)
- Expand to 1000-2000 characters
- Add logical structure (thesis → evidence → conclusion)
- Include data citations and case studies
- Tone: professional but approachable
- Open with a direct answer to the core question
→ 公众号 (from any platform)
- 1500-3000 characters
- Add subtitles for sections
- Open with empathy (pain point / story)
- Close with elevation
- Tone: deep but readable
→ 抖音 Script (from any platform)
- Compress to 200-500 character oral script
- First 3 seconds must hook
- Conversational, avoid written language
- Mark pauses and tone shifts
- End with comment-driving CTA
Output Format
Generate each platform version as a standalone, ready-to-publish piece. Label each with platform name and word count.
Guidelines
- Rewriting ≠ translating — match platform-native voice
- Each version must be independently publishable
- Check platform-specific banned words
What ships with it
2 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.
- 4d ago First seen · 72 lines · 37 tokens per session scan A be446a869cbc
content-rewriter is a skill published in the GitHub repository aAAaqwq/AGI-Super-Team (91 stars, last pushed 2d ago), licensed MIT. It adds 37 tokens to every session and 490 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.
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