Batch Content Factory

SKILL.md

---
name: batch-content-factory
description: Multi-platform content production line. Automates the entire workflow from topic research to content creation. Suitable for self-media operators producing high-quality content in bulk, content team collaboration, and brand content matrix management.
---

# 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

```bash
python scripts/content_factory_tool.py write --platform wechat --topic 'AI Trends'
```

### Scenario 2: Plan Next Week's Content Publishing Calendar

```bash
python scripts/content_factory_tool.py calendar --plan next-week
```

### Scenario 3: Optimize Article SEO

```bash
python scripts/content_factory_tool.py seo --file article.md
```

## Prerequisites

```bash
pip install requests jinja2 markdown
```

## Output Format

Reports generated by the content factory adopt the following format:

```markdown
# 📊 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](https://contentmarketinginstitute.com/developing-a-strategy/)
- [Content Factory Agent Full Use Case](https://github.com/hesamsheikh/awesome-openclaw-usecases/blob/main/usecases/content-factory.md)

## 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`