content-creator

Files (7)

• SKILL.md
• content_calendar_template.md · assets/
• brand_guidelines.md · references/
• content_frameworks.md · references/
• social_media_optimization.md · references/
• brand_voice_analyzer.py · scripts/
• seo_optimizer.py · scripts/

SKILL.md (first lines)

# Content Creator

Professional-grade brand voice analysis, SEO optimization, and platform-specific content frameworks.

## Keywords

content creation, blog posts, SEO, brand voice, social media, content calendar, marketing content, content strategy, content marketing, brand consistency, content optimization, social media marketing, content planning, blog writing, content frameworks, brand guidelines, social media strategy

## Quick Start

### For Brand Voice Development

1. Run `scripts/brand_voice_analyzer.py` on existing content to establish baseline
2. Review `references/brand_guidelines.md` to select voice attributes
3. Apply chosen voice consistently across all content

### For Blog Content Creation

1. Choose template from `references/content_frameworks.md`
2. Research keywords for topic
3. Write content following template structure
4. Run `scripts/seo_optimizer.py [file] [primary-keyword]` to optimize
5. Apply recommendations before publishing

### For Social Media Content

1. Review platform best practices in `references/social_media_optimization.md`
2. Use appropriate template from `references/content_frameworks.md`
3. Optimize based on platform-specific guidelines
4. Schedule using `assets/content_calendar_template.md`

## Core Workflows

### Establishing Brand Voice (First Time Setup)

When creating content for a new brand or client:

1. **Analyze Existing Content** (if available)
   ```bash
   python scripts/brand_voice_analyzer.py existing_content.txt
   ```
2. **Define Voice Attributes**
   - Review brand personality archetypes in `references/brand_guidelines.md`
   - Select primary and secondary archetypes
   - Choose 3-5 tone attributes
   - Document in brand guidelines

3. **Create Voice Sample**
   - Write 3 sample pieces in chosen voice
   - Test consistency using analyzer
   - Refine based on results

### Creating SEO-Optimized Blog Posts

1. **Keyword Research**
   - Identify primary keyword (search volume 500-5000/month)
   - Find 3-5 secondary keywords
   - List 10-15 LSI keywords

2. **Content Structure**
   - Use blog template from `references/content_frameworks.md`
   - Include keyword in title, first paragraph, and 2-3 H2s
   - Aim for 1,500-2,500 words for comprehensive coverage

3. **Optimization Check**

   ```bash
   python scripts/seo_optimizer.py blog_post.md "primary keyword" "secondary,keywords,list"
   ```

4. **Apply SEO Recommendations**
   - Adjust keyword density to 1-3%
   - Ensure proper heading structure
   - Add internal and external links
   - Optimize meta description

### Social Media Content Creation

1. **Platform Selection**
   - Identify primary platforms based on audience
   - Review platform-specific guidelines in `references/social_media_optimization.md`

2. **Content Adaptation**
   - Start with blog post or core message
   - Use repurposing matrix from `references/content_frameworks.md`
   - Adapt for each platform following templates

3. **Optimization Checklist**
   - Platform-appropriate length
   - Optimal posting time
   - Correct image dimensions
   - Platform-specific hashtags
   - Engagement elements (polls, questions)

### Content Calendar Planning

1. **Monthly Planning**
   - Copy `assets/content_calendar_template.md`
   - Set monthly goals and KPIs
   - Identify key campaigns/themes

2. **Weekly Distribution**
   - Follow 40/25/25/10 content pillar ratio
   - Balance platforms throughout week
   - Align with optimal posting times

3. **Batch Creation**
   - Create all weekly content in one session
   - Maintain consistent voice across pieces
   - Prepare all visual assets together

## Key Scripts

### brand_voice_analyzer.py

Analyzes text content for voice characteristics, readability, and consistency.

**Usage**: `python scripts/brand_voice_analyzer.py <file> [json|text]`

From nimeshgurung/artifact-hub-collections, MIT.

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