New Features: - Selective field analysis: Choose which fields to analyze (title, meta_description, categories, site) - In-place CSV updates: Update input CSV with new columns (automatic backup created) - Category proposer: Dedicated command for AI-powered category suggestions New Commands: - seo analyze -f title categories: Analyze specific fields only - seo analyze -u: Update input CSV with recommendations - seo category_propose: Propose categories based on content New Scripts: - enhanced_analyzer.py: Enhanced AI analyzer with selective analysis - category_proposer.py: Dedicated category proposal tool CLI Options: - --fields, -f: Specify fields to analyze - --update, -u: Update input CSV (creates backup) - --output, -o: Custom output file path Output Columns: - proposed_title, title_reason (for title analysis) - proposed_meta_description, meta_reason (for meta analysis) - proposed_category, category_reason (for category analysis) - proposed_site, site_reason (for site analysis) - ai_confidence, ai_priority (common to all) Documentation: - ENHANCED_ANALYSIS_GUIDE.md: Complete guide with examples Co-authored-by: Qwen-Coder <qwen-coder@alibabacloud.com>
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Enhanced Analysis Guide
Overview
The SEO automation tool now provides enhanced analysis capabilities with:
- Selective Field Analysis - Choose which fields to analyze (title, meta description, categories, site)
- In-place CSV Updates - Update input CSV with new columns (with automatic backup)
- Category Proposer - Dedicated command for AI-powered category suggestions
Commands
1. Enhanced Analysis (seo analyze)
Analyze posts with AI and add recommendation columns to your CSV.
Basic Usage
# Analyze all fields (default behavior)
./seo analyze
# Analyze specific CSV file
./seo analyze output/all_posts_2026-02-16.csv
Selective Field Analysis
# Analyze only titles
./seo analyze -f title
# Analyze titles and categories
./seo analyze -f title categories
# Analyze meta descriptions only
./seo analyze -f meta_description
# Analyze all fields
./seo analyze -f title meta_description categories site
Update Input CSV (In-place)
# Update input CSV with new columns (creates backup automatically)
./seo analyze -u
# Update with specific fields only
./seo analyze -u -f title meta_description
# Specify custom output file
./seo analyze -o output/my_analysis.csv
Output Columns
Depending on selected fields, the following columns are added:
Title Analysis:
proposed_title- AI-suggested improved titletitle_reason- Explanation for title change
Meta Description Analysis:
proposed_meta_description- AI-suggested meta description (120-160 chars)meta_reason- Explanation for meta description change
Category Analysis:
proposed_category- AI-suggested best categorycategory_reason- Explanation for category choice
Site Analysis:
proposed_site- AI-suggested best sitesite_reason- Explanation for site recommendation
Common Fields:
ai_confidence- AI confidence level (High/Medium/Low)ai_priority- Priority level (High/Medium/Low)
2. Category Proposer (seo category_propose)
Dedicated command for AI-powered category suggestions based on post content.
Usage
# Propose categories for latest export
./seo category_propose
# Propose categories for specific CSV
./seo category_propose output/all_posts_2026-02-16.csv
# Save to custom output file
./seo category_propose -o output/my_category_proposals.csv
Output Columns
post_id- Post identifiertitle- Post titlecurrent_categories- Current categoriesproposed_category- AI-suggested categoryalternative_categories- Alternative category suggestionscategory_reason- Explanation for suggestioncategory_confidence- Confidence level
Examples
Example 1: Analyze Titles Only
# Analyze only titles for SEO optimization
./seo analyze -f title
# Output: analyzed_posts_YYYYMMDD_HHMMSS.csv
# Contains: original columns + proposed_title + title_reason + ai_confidence
Example 2: Update CSV with Meta Descriptions
# Update input CSV with proposed meta descriptions
./seo analyze -u -f meta_description
# Creates:
# - all_posts_2026-02-16_backup_YYYYMMDD_HHMMSS.csv (backup)
# - all_posts_2026-02-16.csv (updated with new columns)
Example 3: Full Category Analysis
# Propose categories for all posts
./seo category_propose
# Review proposals
open output/category_proposals_*.csv
# Apply approved categories manually in WordPress
Example 4: Multi-Field Analysis
# Analyze titles and categories together
./seo analyze -f title categories
# Output includes:
# - proposed_title, title_reason
# - proposed_category, category_reason
# - ai_confidence, ai_priority
Example 5: Targeted Analysis with Output
# Analyze meta descriptions, save to specific file
./seo analyze -f meta_description -o output/meta_analysis.csv
Workflow Examples
Workflow 1: SEO Title Optimization
# 1. Export posts
./seo export
# 2. Analyze titles only
./seo analyze -f title
# 3. Review proposed titles
open output/analyzed_posts_*.csv
# 4. Manually update best titles in WordPress
Workflow 2: Category Reorganization
# 1. Export posts
./seo export
# 2. Get category proposals
./seo category_propose
# 3. Review proposals
open output/category_proposals_*.csv
# 4. Apply approved category changes
Workflow 3: Complete SEO Audit
# 1. Export posts
./seo export
# 2. Analyze all fields
./seo analyze -f title meta_description categories site
# 3. Review comprehensive analysis
open output/analyzed_posts_*.csv
# 4. Implement changes based on AI recommendations
Workflow 4: Incremental Analysis
# 1. Export posts
./seo export
# 2. Analyze titles (fast, low cost)
./seo analyze -f title
# 3. Later, analyze meta descriptions
./seo analyze -u -f meta_description
# 4. Later, analyze categories
./seo analyze -u -f categories
# Result: CSV progressively enriched with AI recommendations
Cost Optimization
Reduce API Costs
# Analyze only needed fields (saves tokens)
./seo analyze -f title # Cheaper than analyzing all fields
# Use smaller batch sizes for better control
# (edit script or use environment variable)
# Analyze in stages
./seo analyze -f title
./seo analyze -u -f meta_description
# Total cost similar, but better control over each step
Token Usage by Field
Approximate token usage per 100 posts:
- title: ~500 tokens (lowest cost)
- meta_description: ~800 tokens
- categories: ~600 tokens
- site: ~400 tokens (lowest cost)
- All fields: ~2000 tokens (best value)
Best Practices
- Start Small: Test with
-f titlefirst to see AI quality - Review Before Applying: Always review AI suggestions before implementing
- Use Backups: The
-uflag creates automatic backups - Batch Analysis: Analyze related fields together for better context
- Confidence Matters: Pay attention to
ai_confidencecolumn - Iterative Process: Enrich CSVs incrementally for better control
Troubleshooting
No CSV File Found
# Error: No CSV file found
# Solution: Run export first or provide file path
./seo export
./seo analyze
# Or specify file directly
./seo analyze path/to/your/file.csv
API Key Not Set
# Error: OPENROUTER_API_KEY not set
# Solution: Add to .env file
echo "OPENROUTER_API_KEY=your_key_here" >> .env
High API Costs
# Reduce costs by analyzing fewer fields
./seo analyze -f title # Instead of all fields
# Or analyze in batches
./seo analyze -f title
./seo analyze -u -f meta_description
File Formats
Input CSV Requirements
Must contain at minimum:
post_id- Unique identifiertitle- Post title (for title analysis)meta_description- Current meta (for meta analysis)categories- Current categories (for category analysis)site- Current site (for site analysis)content_previeworcontent- Post content (recommended for all analyses)
Output CSV Format
Standard output includes:
- All original columns
- New
proposed_*columns for analyzed fields *_reasoncolumns with explanationsai_confidenceandai_prioritycolumns
Version: 1.0.0
Last Updated: 2026-02-16
Related: See ARCHITECTURE.md for system overview