batch-content-factory（批次内容工厂）

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

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

• Content Marketing Institute Strategy Guide
• Content Factory Agent Full Use Case

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