Skill: openlark/batch-content-factory (version 1.0.0)

--- 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`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)