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The Content Analyzer agent runs comprehensive analysis on completed articles using 5 specialized Python modules to provide actionable, data-driven insights.

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What It Analyzes

The Content Analyzer examines:
  • Search intent - Whether content matches what searchers want
  • Keyword optimization - Density, distribution, stuffing risk
  • Content length - How you compare to top 10 SERP competitors
  • Readability - Flesch scores, grade level, sentence structure
  • SEO quality - Comprehensive 0-100 score across 6 categories

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Analysis Modules

The agent uses Python modules located in data_sources/modules/:

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1. Search Intent Analyzer

search_intent_analyzer.py Analyzes: Query intent classification Determines:
  • Primary intent (informational, navigational, transactional, commercial)
  • Secondary intent if applicable
  • Confidence percentages
  • Whether content aligns with intent
Example Output: 
Primary Intent: Informational (87% confidence)
Secondary Intent: Commercial (13%)
Alignment: ✓ Content matches informational intent
Gap: Missing comparison table for commercial intent

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2. Keyword Analyzer

keyword_analyzer.py Analyzes: Keyword density, distribution, clustering Checks:
  • Primary keyword density (target: 1.0-2.0%)
  • Secondary keyword coverage
  • Keyword placement in critical locations (H1, first 100 words, H2s)
  • Keyword stuffing risk (none/low/medium/high)
  • Topic clusters detected
  • LSI keyword presence
Example Output: 
{
  'primary_keyword': {
    'keyword': 'podcast hosting',
    'density': 1.4,
    'status': 'optimal',
    'occurrences': 23,
    'stuffing_risk': 'none'
  },
  'placements': {
    'in_h1': True,
    'in_first_100_words': True,
    'in_h2_count': 3,
    'in_conclusion': True
  }
}

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3. Content Length Comparator

content_length_comparator.py Analyzes: Word count vs top SERP competitors Compares:
  • Your word count vs median competitor length
  • Your position in percentile distribution
  • Gap to optimal length
  • Competitor range (min-max)
Example Output: 
Your Word Count: 2,100 words
Median Competitor: 2,850 words
75th Percentile: 3,200 words
Your Position: 35th percentile
Gap to Optimal: +750 words needed
Status: Below competitive threshold

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4. Readability Scorer

readability_scorer.py Analyzes: Content readability and comprehension level Calculates:
  • Flesch Reading Ease (0-100, higher = easier)
  • Flesch-Kincaid Grade Level
  • Average sentence length
  • Average paragraph length
  • Passive voice percentage
  • Complex word percentage
  • Long sentence count
Example Output: 
Flesch Reading Ease: 62 (Standard - 8th-9th grade)
Flesch-Kincaid Grade: 8.5
Average Sentence Length: 18 words (Good)
Passive Voice: 12% (Excellent - target <20%)
Long Sentences (25+ words): 8 (Monitor)
Very Long Sentences (35+ words): 2 (Revise)

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5. SEO Quality Rater

seo_quality_rater.py Analyzes: Overall SEO health across 6 categories Scores (0-100):
  • Content Quality
  • Keyword Optimization
  • Meta Elements
  • Structure
  • Links
  • Readability
Reports:
  • Critical issues (must fix before publishing)
  • Warnings (should fix)
  • Suggestions (nice to have)
Example Output: 
Overall SEO Score: 78/100 (Good)

Category Scores:
- Content Quality: 85/100 ✓
- Keyword Optimization: 72/100 ⚠
- Meta Elements: 65/100 ⚠
- Structure: 90/100 ✓
- Links: 70/100 ⚠
- Readability: 82/100 ✓

Critical Issues:
- Meta description exceeds 160 characters
- Only 2 internal links (need 3-5)

Warnings:
- Primary keyword density at 0.8% (target 1-2%)
- No keyword in conclusion

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How It Works

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1. Content Extraction

The agent extracts from the article:
  • Full content text
  • Meta title and description
  • Primary keyword
  • Secondary keywords
  • Target URL or SERP data

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2. Module Execution

Runs all 5 modules in sequence: 
from data_sources.modules.search_intent_analyzer import analyze_intent
from data_sources.modules.keyword_analyzer import analyze_keywords
from data_sources.modules.content_length_comparator import compare_content_length
from data_sources.modules.readability_scorer import score_readability
from data_sources.modules.seo_quality_rater import rate_seo_quality

# Execute analysis
intent_result = analyze_intent(keyword, serp_features, top_results)
keyword_result = analyze_keywords(content, primary_keyword, secondary_keywords)
length_result = compare_content_length(keyword, word_count, serp_results)
readability_result = score_readability(content)
seo_result = rate_seo_quality(content, meta_title, meta_description, ...)

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3. Report Generation

Synthesizes all results into comprehensive report with:
  • Executive summary
  • Individual module findings
  • Priority action plan
  • Publishing checklist

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Output Format

The agent generates a structured report: 
# Content Analysis Report: [Article Title]

**Overall Assessment**: Good
**Publishing Ready**: Yes, with minor revisions

---

## 1. Search Intent Analysis
Primary Intent: Informational
Alignment: ✓ Strong match
Recommendations: [specific suggestions]

## 2. Keyword Optimization
Density: 1.4% ✓ Optimal
Critical Placements: 4/5 ✓
Recommendations: [specific additions]

## 3. Content Length Analysis
Your Count: 2,100 words
Status: Below competitive (need +750 words)
Recommendations: [sections to expand]

## 4. Readability Analysis
Score: 62/100 (8th-9th grade) ✓
Recommendations: [sentence improvements]

## 5. SEO Quality Rating
Score: 78/100 (Good)
Critical Issues: [must fix]
Warnings: [should fix]

## 6. Priority Action Plan
### Critical (Do First)
1. [Most important fix with location]
2. [Second priority]

### High Priority (Do Next)
1. [Important improvement]

## 8. Publishing Checklist
- [x] Word count competitive
- [ ] Keyword density 1-2%
- [ ] 3-5 internal links

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When It Runs

The Content Analyzer runs when you:
  • Use /analyze-existing [URL] command
  • Manually invoke with @content-analyzer
  • Run comprehensive content audits
It does not run automatically after /write (that uses SEO Optimizer instead).

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Integration with Other Agents

The Content Analyzer provides the data foundation for:
  • SEO Optimizer - Uses keyword and structure insights
  • Keyword Mapper - Builds on density analysis
  • Editor - Addresses readability findings
  • Meta Creator - Informed by intent analysis

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Use Cases

Audit existing content: Analyze published articles to find improvement opportunities Pre-publish quality check: Run comprehensive analysis before publishing Competitor benchmarking: Compare your content to top-ranking pages Content refresh decisions: Identify which articles need updates Performance diagnosis: Understand why content isn’t ranking

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Example Analysis

For an article on “How to Start a Podcast”: 
Content Analysis Report

1. Search Intent: Informational ✓
   - Content provides step-by-step guide (matches intent)
   - Missing: Equipment comparison (commercial sub-intent)

2. Keyword Optimization: 72/100
   - Density: 1.2% ✓
   - Missing from: Conclusion, 2 H2 headings
   - Add 3 instances in sections 4, 6, and conclusion

3. Content Length: Too Short
   - Your count: 1,800 words
   - Median competitor: 2,900 words
   - Recommendation: Add 1,000+ words covering equipment details

4. Readability: 85/100 ✓
   - Grade level: 8.2 (optimal)
   - 3 sentences over 35 words (simplify)

5. SEO Quality: 78/100
   - Critical: Meta description 175 chars (trim to 160)
   - Warning: Only 2 internal links (add 2-3 more)

Priority Actions:
1. Trim meta description by 15 characters
2. Add internal links to hosting comparison and equipment guide
3. Expand equipment section by 600 words
4. Add keyword to H2 in section 4 and conclusion

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Technical Requirements

The Python modules require: 
pip install -r data_sources/requirements.txt
API credentials in data_sources/config/.env for:
  • DataForSEO (for SERP data)
  • Optional: Google Search Console (for ranking data)

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Best Practices

Run before publishing: Use as final quality gate Focus on critical issues: Fix must-have items before nice-to-haves Compare to competitors: Use length and intent data to understand gaps Track scores over time: Monitor SEO quality scores to measure improvement Combine with performance data: Use with Performance Agent for complete picture

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Next Steps

SEO Optimizer

Learn about on-page optimization analysis

Keyword Mapper

Deep dive into keyword distribution mapping

Performance

Prioritize content work with analytics data

Editor

Improve readability and human voice

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