Batch Content Factory
Overview
An automated content creation workflow that supports multi-platform content generation, SEO-optimized writing, and content calendar management. Suitable for bulk content production across platforms such as WeChat Official Accounts, Zhihu, Xiaohongshu, and Twitter.
Trigger Keywords
Content creation, copywriting, content creation, copywriting.
Core Capabilities
Capability 1: Multi-Platform Content Generation
Supports content generation for platforms such as WeChat Official Accounts / Zhihu / Xiaohongshu / Twitter, adjusting content style and format according to the characteristics of each platform.
Capability 2: SEO-Optimized Writing
Automatically inserts keywords and meta descriptions to optimize content visibility in search engines.
Capability 3: Content Calendar Management
Plans weekly publishing schedules and manages content release cadence.
Command List
| Command | Description | Usage |
|---|---|---|
write | Generate content | python scripts/content_factory_tool.py write [parameters] |
calendar | Manage publishing calendar | python scripts/content_factory_tool.py calendar [parameters] |
seo | SEO optimization | python scripts/content_factory_tool.py seo [parameters] |
Usage Workflow
Scenario 1: Generate an AI Trends WeChat Official Account Article
python scripts/content_factory_tool.py write --platform wechat --topic 'AI Trends'
Scenario 2: Plan Next Week's Content Publishing Calendar
python scripts/content_factory_tool.py calendar --plan next-week
Scenario 3: Optimize Article SEO
python scripts/content_factory_tool.py seo --file article.md
Prerequisites
pip install requests jinja2 markdown
Output Format
Reports generated by the content factory adopt the following format:
# 📊 Content Factory Report
**Generated on**: YYYY-MM-DD HH:MM
## Key Findings
1. [Key finding 1]
2. [Key finding 2]
3. [Key finding 3]
## Data Overview
| Metric | Value | Trend | Rating |
|--------|-------|-------|--------|
| Metric A | XXX | ↑ | ⭐⭐⭐⭐ |
| Metric B | YYY | → | ⭐⭐⭐ |
## Detailed Analysis
[Multi-dimensional analysis content based on actual data]
## Actionable Recommendations
| Priority | Recommendation | Expected Outcome |
|----------|----------------|------------------|
| 🔴 High | [Specific recommendation] | [Quantified expectation] |
| 🟡 Medium | [Specific recommendation] | [Quantified expectation] |
| 🟢 Low | [Specific recommendation] | [Quantified expectation] |
References
Notes
- All analyses are based on actual data obtained by the script; data is not fabricated
- Missing data fields are marked "Data Unavailable" rather than guessed
- It is recommended to combine with human judgment; AI analysis is for reference only
- Please install Python dependencies before first use:
pip install requests jinja2 markdown