The project's README from github.com/TheCraigHewitt/seomachine. As one markdown file: README.md.
A specialized Claude Code workspace for creating long-form, SEO-optimized blog content for any business. This system helps you research, write, analyze, and optimize content that ranks well and serves your target audience.
SEO Machine is built on Claude Code and provides:
/research, /write, /rewrite, /analyze-existing, /optimize, /performance-review, /publish-draft, /article, /priorities, plus specialized research and landing page commandsgit clone https://github.com/TheCraigHewitt/seomachine.git
cd seomachine
Planning to contribute? Fork this repo first, then clone your fork instead:
git clone https://github.com/<your-username>/seomachine.git
pip install -r data_sources/requirements.txt
This installs:
claude-code .
Customize Context Files (Important!):
All context files are provided as templates. Fill them out with your company's information:
context/brand-voice.md - Define your brand voice and messaging (see examples/castos/ for reference)context/writing-examples.md - Add 3-5 exemplary blog posts from your sitecontext/features.md - List your product/service features and benefitscontext/internal-links-map.md - Map your key pages for internal linkingcontext/style-guide.md - Fill in your style preferencescontext/target-keywords.md - Add your keyword research and topic clusterscontext/competitor-analysis.md - Add competitor analysis and insightscontext/seo-guidelines.md - Review and adjust SEO requirementsQuick Start: Check out examples/castos/ to see a complete real-world example of all context files filled out for a podcast hosting SaaS company.
Before running Docker, configure data_sources/config/.env with your credentials.
docker-compose build
docker-compose run seomachine bash
Content directories are mounted as volumes, so files in topics/, research/, drafts/, published/, output/, rewrites/, context/, and credentials/ persist on your host.
/research [topic]
What it does:
/research/ directoryExample:
/research content marketing strategies for B2B SaaS
/write [topic or research brief]
What it does:
context/brand-voice.md/drafts/ directoryExample:
/write content marketing strategies for B2B SaaS
Agent Auto-Execution: After writing, these agents automatically analyze the content:
/optimize [article file]
What it does:
Example:
/optimize drafts/content-marketing-strategies-2025-10-29.md
/analyze-existing [URL or file path]
What it does:
/research/ directoryExamples:
/analyze-existing https://yoursite.com/blog/marketing-guide
/analyze-existing published/marketing-guide-2024-01-15.md
/rewrite [topic or analysis file]
What it does:
/rewrites/ directoryExample:
/rewrite marketing guide
/research [topic]Comprehensive keyword and competitive research for new content.
Output: Research brief in /research/brief-[topic]-[date].md
Includes:
/write [topic]Create long-form SEO-optimized article (2000-3000+ words).
Output: Article in /drafts/[topic]-[date].md
Includes:
Auto-Triggers:
/rewrite [topic]Update and improve existing content.
Output: Updated article in /rewrites/[topic]-rewrite-[date].md
Includes:
/analyze-existing [URL or file]Analyze existing blog posts for improvement opportunities.
Output: Analysis report in /research/analysis-[topic]-[date].md
Includes:
/optimize [file]Final SEO optimization pass before publishing.
Output: Optimization report in /drafts/optimization-report-[topic]-[date].md
Includes:
/publish-draft [file]Publish article to WordPress via REST API with Yoast SEO metadata.
/article [topic]Simplified article creation workflow.
/prioritiesContent prioritization matrix using analytics data to identify highest-impact content tasks.
/scrub [file]Remove AI watermarks and patterns from content (em-dashes, filler phrases, robotic patterns).
| Command | Description |
|---|---|
/research-serp [keyword] |
SERP analysis for a target keyword |
/research-gaps |
Competitor content gap analysis |
/research-trending |
Trending topic opportunities |
/research-performance |
Performance-based content priorities |
/research-topics |
Topic cluster research |
| Command | Description |
|---|---|
/landing-write [topic] |
Create conversion-optimized landing page |
/landing-audit [file] |
Audit landing page for CRO issues |
/landing-research [topic] |
Research competitors and positioning |
/landing-competitor [URL] |
Deep competitor landing page analysis |
/landing-publish [file] |
Publish landing page to WordPress |
Specialized agents that automatically analyze content and provide expert recommendations.
Purpose: Comprehensive, data-driven content analysis using 5 specialized modules
Analyzes:
Output:
Powered by:
search_intent_analyzer.py - Search intent detectionkeyword_analyzer.py - Keyword density, clustering, LSI keywordscontent_length_comparator.py - SERP competitor analysisreadability_scorer.py - Multiple readability metricsseo_quality_rater.py - Comprehensive SEO scoringPurpose: On-page SEO analysis and optimization recommendations
Analyzes:
Output: SEO score (0-100) with specific improvement recommendations
Purpose: Generate high-converting meta titles and descriptions
Creates:
Output: Multiple options with recommendation and reasoning
Purpose: Strategic internal linking recommendations
Provides:
References: context/internal-links-map.md
Purpose: Keyword placement and integration analysis
Analyzes:
Output: Distribution map, gap analysis, specific revision suggestions
Purpose: Transform technically accurate content into human-sounding, engaging articles
Analyzes:
Provides:
Output: Editorial report with specific improvements to make content sound human
Purpose: Data-driven content prioritization using real analytics
Analyzes:
Provides:
Output: Comprehensive performance report with actionable priorities
Purpose: Generate high-converting headline variations and A/B testing recommendations
Provides:
Purpose: Conversion rate optimization analysis for landing pages
Analyzes:
Purpose: Comprehensive landing page optimization recommendations
Provides:
SEO Machine includes 26 marketing skills accessible as slash commands:
| Category | Skills |
|---|---|
| Copywriting | /copywriting, /copy-editing |
| CRO | /page-cro, /form-cro, /signup-flow-cro, /onboarding-cro, /popup-cro, /paywall-upgrade-cro |
| Strategy | /content-strategy, /pricing-strategy, /launch-strategy, /marketing-ideas |
| Channels | /email-sequence, /social-content, /paid-ads |
| SEO | /seo-audit, /schema-markup, /programmatic-seo, /competitor-alternatives |
| Analytics | /analytics-tracking, /ab-test-setup |
| Other | /referral-program, /free-tool-strategy, /marketing-psychology |
SEO Machine integrates with real-time data sources to inform content strategy:
Google Analytics 4:
Google Search Console:
DataForSEO:
SEO Machine includes 5 specialized Python modules for comprehensive content analysis:
Search Intent Analyzer (search_intent_analyzer.py):
Keyword Analyzer (keyword_analyzer.py):
SEO Quality Rater (seo_quality_rater.py):
Content Length Comparator (content_length_comparator.py):
Readability Scorer (readability_scorer.py):
All modules can be used directly in Python or through the Content Analyzer agent.
Six Python modules for landing page conversion optimization:
above_fold_analyzer.py - Above-the-fold content analysis (headline, value prop, CTA, trust)cta_analyzer.py - CTA effectiveness scoring (quality, distribution, goal alignment)trust_signal_analyzer.py - Trust signal detection (testimonials, social proof, risk reversals)landing_page_scorer.py - Overall landing page scoring (0-100 with category breakdowns)landing_performance.py - Landing page performance tracking via GA4/GSCcro_checker.py - CRO best practices checklist validationopportunity_scorer.py - 8-factor opportunity scoring for content prioritizationcontent_scorer.py - 5-dimension content quality scoring (humanity, specificity, structure, SEO, readability)engagement_analyzer.py - Content engagement pattern analysiscompetitor_gap_analyzer.py - Competitive content gap identificationarticle_planner.py - Data-driven article planningsection_writer.py - Section-level content guidancesocial_research_aggregator.py - Social media research aggregationRun from repo root:
# Content research
python3 research_quick_wins.py
python3 research_competitor_gaps.py
python3 research_performance_matrix.py
python3 research_priorities_comprehensive.py
python3 research_serp_analysis.py
python3 research_topic_clusters.py
python3 research_trending.py
# SEO analysis (config-driven - set up config/competitors.json first)
python3 seo_baseline_analysis.py
python3 seo_bofu_rankings.py
python3 seo_competitor_analysis.py
# Test API connectivity
python3 test_dataforseo.py
Note: SEO analysis scripts load competitor lists and keywords from config/competitors.json. Copy config/competitors.example.json and customize for your business.
Publishing uses the WordPress REST API with a custom MU-plugin that exposes Yoast SEO fields.
Setup:
wordpress/seo-machine-yoast-rest.php as an MU-plugin on your WordPress sitewordpress/functions-snippet.php to your theme's functions.php.env:WP_URL=https://yoursite.com
WP_USERNAME=your_username
WP_APP_PASSWORD=your_application_password
See wordpress/README.md for detailed setup instructions.
See data_sources/README.md for analytics setup instructions.
seomachine/
├── .claude/
│ ├── commands/ # Custom workflow commands
│ │ ├── analyze-existing.md
│ │ ├── research.md
│ │ ├── write.md
│ │ ├── rewrite.md
│ │ ├── optimize.md
│ │ ├── scrub.md
│ │ ├── performance-review.md
│ │ ├── publish-draft.md
│ │ ├── article.md
│ │ ├── priorities.md
│ │ ├── research-serp.md
│ │ ├── research-gaps.md
│ │ ├── research-trending.md
│ │ ├── research-performance.md
│ │ ├── research-topics.md
│ │ ├── landing-write.md
│ │ ├── landing-audit.md
│ │ ├── landing-research.md
│ │ ├── landing-competitor.md
│ │ └── landing-publish.md
│ ├── agents/ # Specialized analysis agents
│ │ ├── content-analyzer.md
│ │ ├── seo-optimizer.md
│ │ ├── meta-creator.md
│ │ ├── internal-linker.md
│ │ ├── keyword-mapper.md
│ │ ├── editor.md
│ │ ├── performance.md
│ │ ├── headline-generator.md
│ │ ├── cro-analyst.md
│ │ └── landing-page-optimizer.md
│ └── skills/ # 26 marketing skills
├── data_sources/ # Analytics integrations
│ ├── modules/ # Python analysis modules
│ │ ├── google_analytics.py
│ │ ├── google_search_console.py
│ │ ├── dataforseo.py
│ │ ├── data_aggregator.py
│ │ ├── search_intent_analyzer.py
│