alter123-zz/content-factory
skills/content-factory/SKILL.md
多代理内容生产线。自动化从选题研究到内容创作的全流程。Keywords: 内容创作, 文案, content creation, copywriting.
$ install --global
skillsauthnpx skillsauth add alter123-zz/RaccoonClaw content-factoryInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 16, 2026, 2:29 AM111.3s3 files scanned
SKILL.md
- name:
- content-factory
- description:
- 多代理内容生产线。自动化从选题研究到内容创作的全流程。Keywords: 内容创作, 文案, content creation, copywriting.
内容工厂 — 自动化从选题研究到内容创作全流程
概述
自动化从选题研究到内容创作全流程。适用于自媒体运营者批量生产高质量内容、内容团队协同创作、品牌内容矩阵化管理等场景。
触发关键词: 内容创作, 文案, content creation, copywriting
前置依赖
pip install requests jinja2 markdown
核心能力
能力1：多平台内容生成——公众号/知乎/小红书/Twitter
多平台内容生成——公众号/知乎/小红书/Twitter
能力2：SEO优化写作——自动插入关键词和元描述
SEO优化写作——自动插入关键词和元描述
能力3：内容日历管理——规划每周发布排期
内容日历管理——规划每周发布排期
命令列表
| 命令 | 说明 | 用法 |
|------|------|------|
| write | 生成内容 | python3 scripts/content_factory_tool.py write [参数] |
| calendar | 管理发布日历 | python3 scripts/content_factory_tool.py calendar [参数] |
| seo | SEO优化 | python3 scripts/content_factory_tool.py seo [参数] |
使用流程
场景 1
生成AI趋势公众号文章
执行：
python3 scripts/content_factory_tool.py write --platform wechat --topic 'AI趋势'
场景 2
规划下周内容发布日历
执行：
python3 scripts/content_factory_tool.py calendar --plan next-week
场景 3
优化文章SEO
执行：
python3 scripts/content_factory_tool.py seo --file article.md
输出格式
# 📊 内容工厂报告
**生成时间**: YYYY-MM-DD HH:MM
## 核心发现
1. [关键发现1]
2. [关键发现2]
3. [关键发现3]
## 数据概览
| 指标 | 数值 | 趋势 | 评级 |
|------|------|------|------|
| 指标A | XXX | ↑ | ⭐⭐⭐⭐ |
| 指标B | YYY | → | ⭐⭐⭐ |
## 详细分析
[基于实际数据的多维度分析内容]
## 行动建议
| 优先级 | 建议 | 预期效果 |
|--------|------|----------|
| 🔴 高 | [具体建议] | [量化预期] |
| 🟡 中 | [具体建议] | [量化预期] |
| 🟢 低 | [具体建议] | [量化预期] |
参考资料
原有链接
- 内容营销学院策略指南
- 内容工厂Agent完整用例
- YouTube内容管道用例
HackerNews
- HackerNews: AI内容工厂的工作流设计
- Reddit r/content_marketing: content_marketing社区AI相关讨论
微信公众号
- 微信公众号: AI内容工厂——批量生产高质量内容
小红书
- 小红书: 自媒体AI内容工厂——批量生产高质量内容
注意事项
- 所有分析基于脚本获取的实际数据，不编造数据
- 数据缺失字段标注"数据不可用"而非猜测
- 建议结合人工判断使用，AI分析仅供参考
- 首次使用请先安装Python依赖：
pip install requests jinja2 markdown
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