Audit Content Library

Analyze WordPress XML, CMS JSON, or CSV exports to reveal publishing trends, author contributions, topic distribution, and content opportunities.

Step 1: Detect and Parse Export File

Read export file ($1):

Auto-detect format (XML/JSON/CSV) unless --format specified
Validate file structure
Count total items (posts, pages, etc.)

Report to user:

## 📁 Content Export Detected

**File:** $1
**Format:** [WordPress XML / JSON / CSV]
**Items found:** [number] posts/pages
**Date range:** [earliest] to [latest]
**File size:** [size]

Would you like to proceed with analysis?

Wait for user confirmation.

Step 2: Parse Content Data

Use data-parser agent to extract:

For all formats:

Post titles
Publication dates
Authors
Categories/tags
Post length (word count)
Status (published/draft)
URLs/slugs

Format-specific:

WordPress XML:

<item>
    <title>Post Title</title>
    <pubDate>Date</pubDate>
    <dc:creator>Author</dc:creator>
    <category>Category</category>
    <content:encoded>Body content</content:encoded>
</item>

JSON:

{
  "title": "Post Title",
  "date": "2024-01-15",
  "author": "Name",
  "categories": ["cat1", "cat2"],
  "content": "Body..."
}

CSV:

title,date,author,category,word_count
"Post Title","2024-01-15","Author","Category",1500

Progress report:

🔄 Parsing content...
- ✅ Posts extracted: [number]
- ✅ Authors identified: [number]
- ✅ Date range: [range]
- ✅ Categories: [number]

Step 3: Analyze Publishing Trends

Use publishing-analyzer agent to calculate:

Publishing Cadence:

Posts per month (last 6, 12, 24 months)
Publishing frequency trends (increasing/decreasing)
Seasonal patterns
Content velocity

Present to user:

## 📊 Publishing Trends

### Overall Stats
- Total posts: [number]
- Active period: [months/years]
- Average: [X] posts/month
- Trend: [Increasing 15% / Stable / Decreasing 10%]

### Recent Performance (Last 6 months)
- [Month]: [count] posts
- [Month]: [count] posts
[etc...]

### Publishing Patterns
- Peak month: [month] ([count] posts)
- Lowest month: [month] ([count] posts)
- Most active day: [day of week]

Would you like to continue with author and topic analysis?

Wait for user approval.

Step 4: Author Contribution Breakdown

Use publishing-analyzer agent to:

Calculate per author:

Total posts
Percentage of total content
Publishing frequency
Average post length
Active period (first to last post)

Present breakdown:

## ✍️ Author Contributions

**Total authors:** [number]

### Top Contributors

#### 1. [Author Name]
- **Posts:** [number] ([percentage]% of total)
- **Avg length:** [words] words
- **Active:** [date range]
- **Cadence:** [X] posts/month

#### 2. [Author Name]
[Same format...]

---

### Long-tail Contributors
- [number] authors with 1-5 posts ([percentage]% of total)

Continue to topic analysis?

Step 5: Topic & Category Analysis

Use topic-classifier agent to:

Analyze categories/tags:

Distribution by category
Most/least covered topics
Topic combinations
Content gaps

Present analysis:

## 🏷️ Topic Distribution

### By Category
1. [Category 1]: [count] posts ([percentage]%)
2. [Category 2]: [count] posts ([percentage]%)
[etc...]

### Topic Insights
- **Most covered:** [topic] ([count] posts)
- **Underserved:** [topics with <5 posts]
- **Emerging:** [topics showing growth]

### Content Opportunities
- [Gap 1]: Only [X] posts, could expand
- [Gap 2]: [Related topics] covered, but [specific angle] missing

Proceed to generate report?

Step 6: Generate Reports

Ask user for output preference:

📊 Report Format

Choose output format:
1. Terminal view (ASCII charts) - Quick review
2. Markdown file - For documentation
3. HTML report - Interactive charts (recommended)
4. All formats

Which would you like?

Terminal View (ASCII Charts)

Publishing Trends (Last 12 Months)
═══════════════════════════════════
Jan 2024  ████████░░ 12 posts
Feb 2024  ██████░░░░  9 posts
Mar 2024  ███████████ 15 posts
[etc...]

Top Authors
═══════════════════════════════════
Alice Smith    ████████████████ 45 posts (35%)
Bob Johnson    ██████████░░░░░░ 28 posts (22%)
[etc...]

Markdown Report

Save to reports/[filename]-audit.md:

# Content Audit Report

**Analyzed:** [date]
**Source:** [filename]
**Period:** [date range]

## Executive Summary
[Key findings]

## Metrics
[Full breakdowns]

HTML Report (with Charts)

Use visualization-generator agent to create:

Line chart: Publishing trends
Bar chart: Author contributions
Pie chart: Topic distribution
Interactive data tables

Save to reports/[filename]-audit.html

Step 7: Deliver Results

Report completion:

## ✅ Content Audit Complete!

**Analysis period:** [date range]
**Total content:** [number] posts
**Authors:** [number]
**Categories:** [number]

### Key Findings
- [Finding 1]
- [Finding 2]
- [Finding 3]

### Reports Generated
- Terminal summary: [displayed above]
- Markdown: reports/[name]-audit.md
- HTML: reports/[name]-audit.html (open in browser)

### Recommended Actions
1. [Action based on findings]
2. [Action based on findings]
3. [Action based on findings]

**Next steps:**
- Use `/publishing-trends` for deeper time-series analysis
- Use `/topic-analysis` to explore specific categories

Usage Examples

# WordPress export
/audit-content wordpress-export.xml --output-html

# JSON export from headless CMS
/audit-content content-export.json

# CSV from analytics
/audit-content content-metrics.csv --format csv

# With specific output format
/audit-content export.xml --format wordpress --output markdown

Supported Formats

Format	Auto-detect	Notes
WordPress XML	✅	Standard WP export
JSON	✅	Any CMS JSON with title/date/author fields
CSV	✅	Must have title,date,author columns minimum
Custom	Specify with --format	Provide field mapping

Tips for Best Results

Export Best Practices

WordPress:

Tools → Export → All content
Download XML file
Run audit

Headless CMS:

Export with all metadata (author, dates, categories)
Include content body for word count analysis
JSON or CSV format preferred

Analytics Export:

Include title, publish date, author, URL
CSV works well for this

Data Quality

✅ Ensure export includes:

Publication dates (for trend analysis)
Author names (for contribution breakdown)
Categories/tags (for topic analysis)
Content/word count (for depth analysis)

❌ Watch out for:

Drafts mixed with published (can filter)
Inconsistent date formats
Missing author attribution
Incomplete exports (verify date range)