blog-cannibalization

# Blog Cannibalization - Keyword Overlap Detection

Detect when multiple blog posts compete for the same search keywords. Two modes:
local-only analysis (default) and DataForSEO API mode for SERP-level data.

## Two Modes

| Mode | Flag | Cost | Data Source |
|------|------|------|-------------|
| Local | (default) | Free | File content analysis via Grep/Read |
| API | `--api` | ~$0.01/call | DataForSEO Page Intersection + Ranked Keywords |

Local mode works without any API keys. API mode requires DataForSEO credentials
set as environment variables: `DATAFORSEO_LOGIN` and `DATAFORSEO_PASSWORD`.

## Local Mode Workflow

### Step 1: Scan Blog Files

Use Glob to find all content files in the target directory:
- Patterns: `**/*.md`, `**/*.mdx`, `**/*.html`
- Skip files in `node_modules/`, `.git/`, `drafts/`

### Step 2: Extract Primary Keywords

For each file, read and extract keyword signals from:
- **Title tag** or H1 heading (highest weight)
- **H2 headings** (medium weight)
- **First paragraph** (supporting signal)
- **Meta description** if present in frontmatter

Primary keyword extraction method:
1. Tokenize title and H1 into 1-gram, 2-gram, and 3-gram phrases
2. Score each phrase by frequency across title + H2s + first paragraph
3. Select the top-scoring 2-3 word phrase as the primary keyword
4. Record secondary keywords from H2 headings

### Step 3: Cluster by Similarity

Group posts into clusters using these matching rules (in priority order):

1. **Exact match** - identical primary keyword across 2+ posts
2. **Stem match** - same root word (e.g., "optimize" vs "optimization")
3. **Semantic overlap** - Claude determines that two keywords target the same
   search intent (e.g., "best CRM software" vs "top CRM tools 2026")
4. **Subset match** - one keyword contains another (e.g., "email marketing"
   vs "email marketing for startups")

### Step 4: Score and Flag

For each cluster with 2+ posts, assess severity and generate a recommendation.

### Step 5: Output Report

Display the results table and per-cluster recommendations.

## API Mode Workflow (DataForSEO)

Requires the `--api` flag. Uses WebFetch to call DataForSEO endpoints.

### Endpoints Used

**Page Intersection** - find keywords where multiple URLs rank:
```
POST https://api.dataforseo.com/v3/dataforseo_labs/google/page_intersection/live
Authorization: Basic <base64(login:password)>

{
  "pages": {
    "1": "https://example.com/post-a",
    "2": "https://example.com/post-b"
  },
  "language_code": "en",
  "location_code": 2840
}
```
Cost: ~$0.01 per call. Returns overlapping keywords with position, volume, CPC.

**Ranked Keywords** - get all keywords a single URL ranks for:
```
POST https://api.dataforseo.com/v3/dataforseo_labs/google/ranked_keywords/live

{
  "target": "https://example.com/post-a",
  "language_code": "en",
  "location_code": 2840
}
```

### API Analysis Steps

1. Collect all published URLs from the user (or sitemap)
2. Run Ranked Keywords for each URL to build keyword profiles
3. Run Page Intersection for URL pairs that share keyword clusters
4. Calculate severity using the formula below
5. Output enriched report with search volume and position data

## Severity Scoring

Four severity levels based on overlap signals:

| Level | Criteria | Action Urgency |
|-------|----------|----------------|
| Critical | Same exact keyword, both pages in top 20 | Immediate |
| High | Same keyword cluster, one page outranks the other | This week |
| Medium | Related keywords with partial SERP overlap | This month |
| Low | Semantic similarity but different confirmed intents | Monitor |

### Severity Formula (API Mode)

```
severity_score = overlap_count x avg_search_volume x (1 / position_gap)
```

Where:
- `overlap_count` = number of shared ranking keywords
- `avg_search_volume` = mean monthly volume of shared keywords
- `position_gap` = absolute difference in average ranking position (min 1)

Higher score = more urgent cannibalization problem.

### Severity Heuristic (Local Mode)

Without SERP data, use a simplified scoring:
- **Critical**: Exact primary keyword match between posts
- **High**: Stem match on primary keyword, or 3+ shared H2 keywords
- **Medium**: Semantic overlap on primary keyword
- **Low**: Subset match only, or shared secondary keywords

## Output Format

### Summary Table

```
| Post A | Post B | Shared Keywords | Severity | Recommendation |
|--------|--------|-----------------|----------|----------------|
| /best-crm-tools | /top-crm-software | best crm, crm tools, crm software | Critical | MERGE |
| /email-tips | /email-marketing-guide | email marketing | High | DIFFERENTIATE |
| /seo-basics | /seo-for-beginners | seo basics, beginner seo | Critical | CANONICAL |
| /react-hooks | /react-state-mgmt | react, state | Low | NO ACTION |
```

### Per-Cluster Detail

For each flagged cluster, provide:
- Both post titles and URLs
- Full list of overlapping keywords (with volume if API mode)
- Which post is stronger (more comprehensive, better structured)
- Specific recommendation with rationale

## Recommendations

Four possible actions for each cannibalization cluster:

### MERGE
When both pages are thin or cover the same intent with similar depth.
- Combine the best content from both into one comprehensive post
- 301 redirect the weaker URL to the merged post
- Preserve all internal links pointing to either URL

### DIFFERENTIATE
When pages serve different intents but keyword targeting overlaps.
- Shift the primary keyword of the weaker post to a related long-tail
- Update the title, H1, and meta description to reflect the new focus
- Add internal links between the two posts to signal distinct topics

### CANONICAL
When one post is clearly the authority and the other is a lesser duplicate.
- Add `rel="canonical"` on the weaker page pointing to the authority
- Consider noindexing the weaker page if it adds no unique value
- Link from the weaker page to the authority page

### NO ACTION
When intent is genui