SEO Backlinks

Backlink Profile Analysis

Source Detection

Before analysis, detect available data sources:

1. DataForSEO MCP (premium): Check if dataforseo_backlinks_summary tool is available
2. Moz API (free signup): "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run backlinks_auth.py --check moz --json
3. Bing Webmaster (free signup): "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run backlinks_auth.py --check bing --json
4. Keywords Everywhere (free signup, single-metric): "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run backlinks_auth.py --check keywordseverywhere --json
5. Common Crawl (always available): Domain-level graph with PageRank
6. Verification Crawler (always available): Checks if known backlinks still exist

Run "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run backlinks_auth.py --check --json to detect all sources at once.

If no sources are configured beyond the always-available tier:

• Still produce a report using Common Crawl domain metrics
• Suggest: "Run /seo backlinks setup to add free Moz and Bing API keys for richer data"

Quick Reference

Analysis Framework

Produce all 7 sections below. Each section lists data sources in preference order.

1. Profile Overview

DataForSEO: dataforseo_backlinks_summary → total backlinks, referring domains, domain rank, follow ratio, trend.

Moz API: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py metrics <url> --json → Domain Authority, Page Authority, Spam Score, linking root domains, external links.

Keywords Everywhere: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run keywordseverywhere_api.py rank <domain> --json → 0-10 domain rank only (no link counts). Use as a fallback when Moz isn't configured; do not use in place of Moz when both are available.

Common Crawl: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run commoncrawl_graph.py <domain> --json → PageRank, harmonic centrality, and low-confidence rank/presence data.

Scoring:

2. Anchor Text Distribution

DataForSEO: dataforseo_backlinks_anchors

Moz API: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py anchors <url> --json

Bing Webmaster: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run bing_webmaster.py links <url> --json (extract anchor text from link details)

Healthy distribution benchmarks:

Flag if exact-match anchors exceed 15% as a review heuristic; it may indicate unnatural or link-spam patterns.

3. Referring Domain Quality

DataForSEO: dataforseo_backlinks_referring_domains

Moz API: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py domains <url> --json → domains with DA scores

Common Crawl: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run commoncrawl_graph.py <domain> --json → domain-level rank/presence data, no verified referring-domain counts

Analyze:

• TLD distribution: .edu, .gov, .org = high authority. Excessive .xyz, .info = low quality
• Country distribution: Match target market. 80%+ from irrelevant countries = PBN signal
• Domain rank distribution: Healthy profiles have links from all authority tiers
• Follow/nofollow per domain: Sites that only nofollow = limited SEO value

4. Toxic Link Detection

DataForSEO: dataforseo_backlinks_bulk_spam_score + toxic patterns from reference

Moz API: Raw vendor spam_score from "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py metrics <url> --json (source-label the value; apply thresholds only if verified against current Moz docs)

Verification Crawler: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run verify_backlinks.py --target <url> --links <file> --json (verify suspicious links still exist)

High-risk indicators (flag immediately):

• Links from known PBN (Private Blog Network) domains
• Unnatural anchor text patterns (100% exact match from a domain)
• Links from penalized or deindexed domains
• Mass directory submissions (50+ directory links)
• Link farms (sites with 10K+ outbound links per page)
• Paid link patterns (footer/sidebar links across all pages of a domain)

Medium-risk indicators (review manually):

• Links from unrelated niches
• Reciprocal link patterns
• Links from thin content pages (<100 words)
• Excessive links from a single domain (>50 backlinks from 1 domain)

Load ../seo/references/backlink-quality.md for the full 30 toxic patterns and disavow criteria.

5. Top Pages by Backlinks

DataForSEO: dataforseo_backlinks_backlinks with target type "page"

Moz API: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py pages <domain> --json

Find:

• Which pages attract the most backlinks
• Pages with high-authority links (link magnets)
• Pages with zero backlinks (internal linking opportunities)
• 404 pages with backlinks (redirect opportunities to reclaim link equity)

6. Competitor Gap Analysis

DataForSEO: dataforseo_backlinks_referring_domains for both domains, then compare

Bing Webmaster: "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run bing_webmaster.py compare <url1> <url2> --json only when both properties are registered and accessible to the same Bing API account. For arbitrary competitors, use DataForSEO, Moz, or Common Crawl.

Moz API: Compare DA/PA between domains via "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py metrics <url> --json for each

Output:

• Domains linking to competitor but NOT to target = link building opportunities
• Domains linking to both = validate existing relationships
• Domains linking only to target = competitive advantage
• Top 20 link building opportunities with domain authority

7. New and Lost Backlinks

DataForSEO only: dataforseo_backlinks_backlinks with date filters for 30/60/90 day changes

Verification Crawler: For known links, verify current status with "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run verify_backlinks.py --target <url> --links <file> --json

Note: Free sources cannot track new/lost links over time. If this section is requested without DataForSEO, inform the user: "Link velocity tracking requires the DataForSEO extension. Free sources provide point-in-time snapshots only."

Red flags:

• Sudden spike in new links (possible negative SEO attack)
• Sudden loss of many links (site penalty or content removal)
• Declining velocity over 3+ months (content not attracting links)

Backlink Health Score

Calculate a 0-100 score. When mixing sources, apply confidence weighting: