Content Automation

内容创作自动化工具 Skill。支持社交媒体内容生成、视频脚本创作、定时发布任务管理。当用户需要批量生成内容、自动化社交媒体运营或创建视频脚本时触发。

Security Scan

The skill's stated metadata omits any credential or install requirements, but the runtime instructions ask you to clone and run an external GitHub repo and place sensitive keys (OpenAI key, Twitter username/password/email, YouTube client secrets) into a local config — this mismatch and the use of an external codebase warrant caution.

Purpose & Capability

The skill claims to be a content-automation helper and the included examples match that purpose, but the SKILL.md requires cloning an external repository (MoneyPrinterV2) and handling platform credentials in a local config. The metadata declares no required env vars or credentials, which is inconsistent with the instructions that explicitly ask for OpenAI keys, Twitter credentials, YouTube client_secrets, and affiliate tags.

Instruction Scope

The SKILL.md instructs the user/agent to clone https://github.com/FujiwaraChoki/MoneyPrinterV2.git, create a venv, pip-install requirements, and place sensitive secrets into config.json. It also shows example code that would post to social platforms and schedule jobs. These steps involve executing third‑party code and storing/transmitting credentials in a manner not declared by the skill metadata; the instructions go beyond mere content generation guidance and require running code from an external source.

Install Mechanism

There is no formal install spec, but the README-style instructions direct cloning a GitHub repo and installing its requirements. GitHub is a common host, but the repo owner is unknown and arbitrary code would be executed on the user's machine if followed. The included quickstart script itself is benign and only checks for the repo/config, but the real behavior depends on the external repository.

Credentials

The skill metadata declares no required environment variables or primary credential, yet SKILL.md requires an openai_api_key, Twitter username/password/email, YouTube client_secrets.json, and affiliate settings in a config.json file. Asking for platform passwords and plaintext keys in a config file is disproportionate and risky; credentials are neither declared in the registry metadata nor scoped or justified (e.g., OAuth flow).

Persistence & Privilege

The skill is not set to always:true and is user-invocable; it does not request elevated platform privileges or attempt to modify other skills' configuration. The included script only provides a local quickstart/help check and does not persist beyond normal usage.

What to consider before installing

This skill's metadata says it needs nothing, but the SKILL.md tells you to clone and run a third‑party GitHub repo and to store sensitive credentials (OpenAI key, Twitter email/password, YouTube client_secrets) in a local config.json. Before installing or running anything: (1) review the referenced GitHub repository code (MoneyPrinterV2) thoroughly — do not run it blindly; (2) avoid putting passwords/API keys in plaintext configs — prefer OAuth and scoped API tokens or environment variables, and limit permissions for any tokens you create; (3) run the code in an isolated environment (dedicated VM or container) if you must test it; (4) verify that posting to social platforms uses official APIs and proper authentication (not raw username/password); and (5) if you cannot audit the external repo or if it requests full account credentials, do not install or use the skill. Document any secrets you supply and rotate them after testing.

Content Automation Skill

内容创作自动化工具，帮助创作者和运营人员提高效率。支持社交媒体内容生成、视频脚本创作、定时任务管理等功能。

注意：本 Skill 专注于内容创作辅助，用户需遵守各平台的使用条款和社区规范。

前置要求

# 克隆仓库
git clone https://github.com/FujiwaraChoki/MoneyPrinterV2.git
cd MoneyPrinterV2

# 需要 Python 3.12+
python --version

# 创建虚拟环境
python -m venv venv
source venv/bin/activate  # Windows: .venv\Scripts\activate

# 安装依赖
pip install -r requirements.txt

# 复制配置文件
cp config.example.json config.json

配置

编辑 config.json：

{
  "openai_api_key": "your-key",
  "twitter": {
    "enabled": false,
    "username": "",
    "password": "",
    "email": ""
  },
  "youtube": {
    "enabled": false,
    "client_secrets_file": "client_secrets.json"
  },
  "affiliate": {
    "enabled": false,
    "amazon_tag": ""
  }
}

核心功能

1. 内容生成器

from src.classes.ContentGenerator import ContentGenerator

# 初始化生成器
generator = ContentGenerator()

# 生成社交媒体帖子
post = generator.generate_post(
    topic="人工智能趋势",
    platform="twitter",
    tone="professional",
    length="short"
)
print(post)

# 生成视频脚本
script = generator.generate_video_script(
    topic="如何学习编程",
    duration_seconds=60,
    style="educational"
)
print(script)

# 生成内容创意
ideas = generator.generate_content_ideas(
    niche="科技评测",
    count=10
)
for idea in ideas:
    print(f"- {idea}")

2. 视频创作辅助

# 生成短视频脚本
python -c "
from src.classes.VideoGenerator import VideoGenerator

vg = VideoGenerator()
script = vg.generate_script(
    topic='5个Python技巧',
    style='fast-paced',
    duration=60
)
print(script)
"

# 生成视频描述和标签
python -c "
from src.classes.VideoGenerator import VideoGenerator

vg = VideoGenerator()
metadata = vg.generate_metadata(
    title='Python编程入门',
    keywords=['python', 'programming', 'tutorial']
)
print(f'描述: {metadata[\"description\"]}')
print(f'标签: {metadata[\"tags\"]}')
"

3. 定时任务调度

from src.classes.Scheduler import Scheduler
from datetime import datetime, timedelta

# 创建调度器
scheduler = Scheduler()

# 添加定时发布任务
scheduler.add_job(
    func=post_to_twitter,
    trigger='cron',
    hour=9,
    minute=0,
    args=["早安推文内容"]
)

# 添加延时任务
scheduler.add_job(
    func=generate_daily_content,
    trigger='date',
    run_date=datetime.now() + timedelta(hours=2)
)

# 启动调度器
scheduler.start()

4. 内容日历管理

from src.classes.ContentCalendar import ContentCalendar

# 创建内容日历
calendar = ContentCalendar()

# 添加内容计划
calendar.add_content(
    date="2024-03-25",
    platform="twitter",
    topic="产品发布",
    status="planned"
)

# 查看本周计划
weekly_plan = calendar.get_weekly_plan()
for item in weekly_plan:
    print(f"{item['date']}: {item['topic']} ({item['platform']})")

# 导出日历
calendar.export_to_csv("content_calendar.csv")

完整工作流示例

批量生成一周社交媒体内容

#!/usr/bin/env python3
"""
批量生成一周社交媒体内容
"""

from src.classes.ContentGenerator import ContentGenerator
from src.classes.ContentCalendar import ContentCalendar
import json

def generate_weekly_content(niche: str, platforms: list):
    """为指定领域生成一周内容"""
    
    generator = ContentGenerator()
    calendar = ContentCalendar()
    
    # 内容主题池
    topics = [
        "周一灵感",
        "周二技巧",
        "周三案例",
        "周四趋势",
        "周五总结",
        "周末轻松话题"
    ]
    
    content_plan = []
    
    for i, topic in enumerate(topics):
        for platform in platforms:
            # 生成内容
            content = generator.generate_post(
                topic=f"{niche} - {topic}",
                platform=platform,
                tone="casual" if i >= 5 else "professional"
            )
            
            # 添加到日历
            calendar.add_content(
                day=i,
                platform=platform,
                content=content,
                topic=topic
            )
            
            content_plan.append({
                "day": i,
                "platform": platform,
                "topic": topic,
                "content": content
            })
    
    # 保存计划
    with open("weekly_content.json", "w", encoding="utf-8") as f:
        json.dump(content_plan, f, ensure_ascii=False, indent=2)
    
    # 导出日历
    calendar.export_to_csv("weekly_calendar.csv")
    
    print(f"✅ 已生成 {len(content_plan)} 条内容")
    print(f"📅 日历已保存至 weekly_calendar.csv")
    print(f"📝 详细计划已保存至 weekly_content.json")
    
    return content_plan

# 执行
if __name__ == "__main__":
    generate_weekly_content(
        niche="人工智能",
        platforms=["twitter", "linkedin"]
    )

视频内容生产线

#!/usr/bin/env python3
"""
视频内容自动化生产流程
"""

from src.classes.VideoGenerator import VideoGenerator
from src.classes.ContentGenerator import ContentGenerator
import os

def create_video_pipeline(topic: str, output_dir: str = "./output"):
    """创建完整视频制作流程"""
    
    os.makedirs(output_dir, exist_ok=True)
    
    vg = VideoGenerator()
    cg = ContentGenerator()
    
    print(f"🎬 开始制作视频: {topic}")
    
    # 1. 生成脚本
    print("📝 生成脚本...")
    script = vg.generate_script(
        topic=topic,
        style="educational",
        duration=90
    )
    
    with open(f"{output_dir}/script.txt", "w", encoding="utf-8") as f:
        f.write(script)
    
    # 2. 生成视频描述
    print("📄 生成视频描述...")
    metadata = vg.generate_metadata(
        title=topic,
        keywords=["教程", "教育", topic]
    )
    
    with open(f"{output_dir}/metadata.json", "w", encoding="utf-8") as f:
        import json
        json.dump(metadata, f, ensure_ascii=False, indent=2)
    
    # 3. 生成缩略图描述
    print("🎨 生成缩略图创意...")
    thumbnail_ideas = cg.generate_content_ideas(
        niche=f"视频缩略图: {topic}",
        count=3
    )
    
    with open(f"{output_dir}/thumbnail_ideas.txt", "w", encoding="utf-8") as f:
        for idea in thumbnail_ideas:
            f.write(f"- {idea}\n")
    
    print(f"✅ 视频制作素材已保存至 {output_dir}/")
    print(f"   - 脚本: script.txt")
    print(f"   - 元数据: metadata.json")
    print(f"   - 缩略图创意: thumbnail_ideas.txt")
    
    return {
        "script": script,
        "metadata": metadata,
        "thumbnail_ideas": thumbnail_ideas
    }

# 执行
if __name__ == "__main__":
    create_video_pipeline("Python异步编程入门")

内容分析与优化

#!/usr/bin/env python3
"""
分析内容表现并生成优化建议
"""

from src.classes.Analytics import Analytics
from src.classes.ContentGenerator import ContentGenerator

def analyze_and_optimize(content_history: list):
    """分析历史内容表现并生成优化建议"""
    
    analytics = Analytics()
    generator = ContentGenerator()
    
    # 分析表现
    print("📊 分析内容表现...")
    insights = analytics.analyze_performance(content_history)
    
    print("\n🔍 关键洞察:")
    print(f"  最佳发布时间: {insights['best_posting_time']}")
    print(f"  高互动话题: {', '.join(insights['top_topics'])}")
    print(f"  最佳内容长度: {insights['optimal_length']}")
    
    # 生成优化建议
    print("\n💡 优化建议:")
    recommendations = generator.generate_recommendations(insights)
    for rec in recommendations:
        print(f"  - {rec}")
    
    # 生成下周期内容策略
    print("\n📅 下周期内容策略:")
    strategy = generator.generate_content_strategy(
        insights=insights,
        timeframe="下周"
    )
    print(strategy)
    
    return insights, recommendations

# 示例数据
sample_history = [
    {"topic": "AI趋势", "engagement": 150, "posted_at": "09:00"},
    {"topic": "编程技巧", "engagement": 230, "posted_at": "14:00"},
    {"topic": "行业新闻", "engagement": 89, "posted_at": "18:00"},
]

analyze_and_optimize(sample_history)

高级功能

批量脚本执行

项目提供了一系列便捷脚本：

# 从项目根目录运行

# 上传视频
bash scripts/upload_video.sh /path/to/video.mp4 "视频标题"

# 批量生成内容
bash scripts/generate_batch.sh topics.txt

# 发布定时内容
bash scripts/scheduled_post.sh

自定义内容模板

from src.classes.TemplateManager import TemplateManager

# 创建模板管理器
tm = TemplateManager()

# 注册自定义模板
tm.register_template(
    name="product_launch",
    template="""
    🚀 新品发布！
    
    {product_name} 现已上线！
    
    ✨ 核心功能:
    {features}
    
    🎯 适合人群: {target_audience}
    
    了解更多: {link}
    """
)

# 使用模板生成内容
content = tm.render_template(
    "product_launch",
    product_name="AI助手Pro",
    features="- 智能回复\n- 多语言支持\n- 数据分析",
    target_audience="内容创作者",
    link="https://example.com"
)
print(content)

多平台内容适配

from src.classes.ContentAdapter import ContentAdapter

# 创建适配器
adapter = ContentAdapter()

# 原始内容
original = """
人工智能正在改变内容创作的方式。
从文本生成到视频制作，AI 工具让创作者能够更高效地生产高质量内容。
"""

# 适配到不同平台
twitter_version = adapter.adapt_for_platform(original, "twitter")
linkedin_version = adapter.adapt_for_platform(original, "linkedin")
instagram_version = adapter.adapt_for_platform(original, "instagram")

print("Twitter:", twitter_version)
print("LinkedIn:", linkedin_version)
print("Instagram:", instagram_version)

最佳实践

内容质量控制

1. 人工审核：自动生成的内容必须经过人工审核
2. 品牌一致性：保持品牌语调和风格统一
3. 平台适配：针对不同平台优化内容格式
4. 合规检查：确保内容符合平台规则和法律法规

发布频率建议

平台	建议频率	最佳时段
Twitter/X	3-5次/天	9:00, 12:00, 18:00
LinkedIn	1-2次/天	8:00, 17:00
Instagram	1-3次/天	11:00, 14:00, 20:00

内容类型搭配

• 教育内容 (40%)：教程、技巧、知识分享
• 娱乐内容 (30%)：轻松话题、互动内容
• 推广内容 (20%)：产品、服务、活动
• 社区内容 (10%)：用户故事、互动问答

故障排查

依赖问题

# 重新安装依赖
pip install -r requirements.txt --force-reinstall

# 检查 Python 版本
python --version  # 需要 3.12+

API 限制

• 监控 API 调用频率
• 实现指数退避重试机制
• 准备备用 API 密钥

内容生成失败

• 检查 API 密钥配置
• 简化输入提示词
• 查看详细错误日志

免责声明

本工具仅供学习和内容创作辅助使用：

• 遵守各平台的使用条款
• 尊重知识产权和版权
• 不得用于生成垃圾信息或滥用平台
• 用户对生成内容的使用负全部责任

许可证

本项目基于 AGPL-3.0 许可证开源。使用本 Skill 即表示你同意遵守相关许可条款。

相关资源

• 项目文档
• 开发路线图
• 贡献指南