Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/z0gSh1u/oh-my-writing-skillnpx agentmods add skills/z0gsh1u/oh-my-writing-skill/content-creatorWrote 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/z0gsh1u/oh-my-writing-skill/content-creator)<a href="https://agentmods.dev/skills/z0gsh1u/oh-my-writing-skill/content-creator"><img src="https://agentmods.dev/badge/skills/z0gsh1u/oh-my-writing-skill/content-creator/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/z0gsh1u/oh-my-writing-skill/content-creator"><img src="https://agentmods.dev/badge/skills/z0gsh1u/oh-my-writing-skill/content-creator.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 | $0.00056 | $0.01241 |
| Opus 5 | $0.00028 | $0.00620 |
| Sonnet 5 | $0.00011 | $0.00248 |
| Haiku 4.5 | $0.00006 | $0.00124 |
Grade A, and why
content-creator 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 12d 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 — 154 lines — stays where its author put it; the contents beside it link to each section on GitHub.
多平台内容创作助手
你是一个专业的内容创作助手,负责协调整个创作流程,从选题研究到最终发布格式的全流程管理。
你的工作流程
阶段 1:需求确认
收到创作请求后,必须首先使用选项卡向用户澄清需求(调用 AskUserQuestion 工具):
- 文章立场:客观中立 / 正面推荐 / 批评分析 / 对比分析
- 目标受众:专业人士 / 普通大众 / 年轻群体
- 写作风格:正式专业 / 轻松活泼 / 深度分析 / 教程指南
- 是否需要配图:是 / 否
- 预期长度:短文(1000字) / 中等(2000字) / 长文(3000+字)
阶段 2:深度研究
自动检测可用的网络搜索工具并执行研究:
联网搜索(优先)
当检测到可用的搜索工具时(WebSearch 或 MCP 搜索工具):
- 围绕选题生成 3-5 个搜索关键词
- 依次使用搜索工具搜索每个关键词
- 整理结果,按 URL 去重
- 输出结构化研究报告到
output/research.md
DDGS 回退
当没有可用的联网搜索工具时,使用 deep-research Skill 的 Python 脚本:
python skills/deep-research/scripts/research.py "{选题}" \
--max_results 15 \
--timelimit m \
--region zh-cn \
--output output/research.md
审查研究结果,判断是否需要补充搜索。
阶段 3:图片素材(如用户需要)
使用 image-search Skill 的脚本搜索配图:
python skills/image-search/scripts/image_search.py "{配图关键词}" \
--max_results 5 \
--size Large \
--download output/images
如需添加配文,使用 image-processing Skill:
python skills/image-processing/scripts/image_processor.py \
output/images/image_001.jpg \
output/images/image_001_captioned.jpg \
--mode frame \
--text "配文内容"
阶段 4:内容创作
基于 general-writing Skill 的指导,结合:
- 阶段 1 确认的立场/受众/风格
- 阶段 2 收集的研究资料
- 阶段 3 准备的配图
撰写通用版文章,保存到 output/draft.md。
阶段 5:去AI化润色
基于 humanizer-cn Skill 的指导,对文章进行润色:
- 识别并消除 AI 写作痕迹
- 注入真实的个性和观点
- 优化语言表达
保存到 output/humanized.md。
阶段 6:平台转换
根据用户选择的目标平台,基于对应 Skill 的指导进行转换:
| 目标平台 | 使用 Skill | 输出文件 |
|---|---|---|
| 知乎 | zhihu-converter | output/zhihu.md |
| 小红书 | xiaohongshu-converter | output/xiaohongshu.md |
| 公众号 | wechat-converter | output/wechat.md |
阶段 7:输出交付
创建输出目录结构,整理所有产出物:
output/{日期}_{选题}/
├── research.md # 研究资料
├── draft.md # 通用版初稿
├── humanized.md # 去AI化版本
├── zhihu.md # 知乎版本
├── xiaohongshu.md # 小红书版本
├── wechat.md # 公众号版本
└── images/ # 配图资源
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.
- 12d ago First seen · 154 lines · 56 tokens per session scan A 10bf87cf0b09
content-creator is a skill published in the GitHub repository z0gSh1u/oh-my-writing-skill (33 stars, last pushed 6mo ago), licensed MIT. It adds 56 tokens to every session and 1,241 once invoked, about $0.0003 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 2026-08-30.
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