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 liyecom/liye-ai --skill content-writergit clone --depth 1 https://github.com/liyecom/liye-aiWrote 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/liyecom/liye-ai/content-writer)<a href="https://agentmods.dev/skills/liyecom/liye-ai/content-writer"><img src="https://agentmods.dev/badge/skills/liyecom/liye-ai/content-writer/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/liyecom/liye-ai/content-writer"><img src="https://agentmods.dev/badge/skills/liyecom/liye-ai/content-writer.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 | $0.00010 | $0.00900 |
| Opus 5 | $0.00005 | $0.00450 |
| Sonnet 5 | $0.00002 | $0.00180 |
| Haiku 4.5 | $0.00001 | $0.00090 |
Grade A, and why
content-writer 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 10d 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 Research Writer
来源: ComposioHQ/awesome-claude-skills 适配: LiYe OS 三层架构
协助撰写高质量内容，通过研究收集资料、添加引用、优化开头、提供分节反馈。
When to Use This Skill
当需要撰写高质量内容时：
- 研究并收集主题相关资料
- 撰写带引用的专业文章
- 优化文章开头吸引读者
- 获取结构和内容反馈
- 创作 SEO 友好的内容
Core Capabilities
1. 主题研究
- 收集权威来源资料
- 整理关键信息点
- 识别知识缺口
- 验证事实准确性
2. 引用管理
- 添加内联引用
- 生成参考文献列表
- 支持多种引用格式 (APA, MLA, Chicago)
- 确保引用完整性
3. 开头优化
- 创作吸引人的开头
- 设置文章基调
- 建立读者兴趣
- A/B 测试不同开头
4. 结构建议
- 分析文章结构
- 建议章节划分
- 优化信息流
- 确保逻辑连贯
5. 分节反馈
- 逐节质量评估
- 改进建议
- 语言润色
- SEO 优化建议
Usage Examples
示例 1: Amazon Listing 文案
用户: 帮我写一个厨房用具的 Amazon 产品描述
Claude: [使用 content-writer 研究竞品文案、提取卖点、撰写优化描述]
示例 2: 博客文章
用户: 写一篇关于跨境电商选品的深度文章
Claude: [使用 content-writer 研究资料、创建大纲、逐节撰写、添加引用]
示例 3: 技术文档
用户: 帮我优化这份 API 文档的结构和内容
Claude: [使用 content-writer 分析结构、提供反馈、改进内容]
Dependencies
- 研究数据库访问（可选）
- 引用管理工具（可选）
LiYe OS Integration
业务域引用
此技能被以下业务域引用：
- 08_Communication: 内容创作（主域）
- 02_Operation_Intelligence: Listing 文案优化
三层架构位置
- 物理层 (本文件): Skills/00_Core_Utilities/communication/content-writer/
- 逻辑层索引: Skills/{domain}/index.yaml
- L3 指令层: .claude/skills/{domain}/content-writer/
Created: 2025-12-28 | Adapted for LiYe OS
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.
- 10d ago First seen · 122 lines · 10 tokens per session scan A e5211e2ce22f
content-writer is a skill published in the GitHub repository liyecom/liye-ai (33 stars, last pushed 2d ago), licensed Apache-2.0. It adds 10 tokens to every session and 900 once invoked, about $0.0001 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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