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): python3 scripts/backlinks_auth.py --check moz --json
3. Bing Webmaster (free signup): python3 scripts/backlinks_auth.py --check bing --json
4. Common Crawl (always available): Domain-level graph with PageRank
5. Verification Crawler (always available): Checks if known backlinks still exist

Run python3 scripts/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: python3 scripts/moz_api.py metrics <url> --json → Domain Authority, Page Authority, Spam Score, linking root domains, external links.

Common Crawl: python3 scripts/commoncrawl_graph.py <domain> --json → in-degree (referring domain count), PageRank, harmonic centrality.

Scoring:

2. Anchor Text Distribution#

DataForSEO: dataforseo_backlinks_anchors

Moz API: python3 scripts/moz_api.py anchors <url> --json

Bing Webmaster: python3 scripts/bing_webmaster.py links <url> --json (extract anchor text from link details)

Healthy distribution benchmarks:

Flag if exact-match anchors exceed 15% -- this is a Google Penguin risk signal.

3. Referring Domain Quality#

DataForSEO: dataforseo_backlinks_referring_domains

Moz API: python3 scripts/moz_api.py domains <url> --json → domains with DA scores

Common Crawl: python3 scripts/commoncrawl_graph.py <domain> --json → top referring domains (domain-level, no authority scores)

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: Spam Score from python3 scripts/moz_api.py metrics <url> --json (1-17% scale, >11% = high risk)

Verification Crawler: python3 scripts/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 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: python3 scripts/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 (unique!): python3 scripts/bing_webmaster.py compare <url1> <url2> --json — the only free tool with built-in competitor comparison

Moz API: Compare DA/PA between domains via python3 scripts/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 python3 scripts/verify_backlinks.py

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:

Data sufficiency gate: Count how many of the 7 factors have at least one data source available.

• 4+ factors with data: Produce a numeric 0-100 score (redistribute missing weights proportionally)
• Fewer than 4 factors: Do NOT produce a numeric score. Instead display:

  Backlink Health Score: INSUFFICIENT DATA (X/7 factors scored)

  Show individual factor scores that ARE available with their source and confidence. Recommend: "Configure Moz API (free) for a scoreable profile. Run /seo backlinks setup"

When only CC is available, cap maximum score at 70/100. A numeric score with fewer than 4 data sources is misleading — it implies poor health when the reality is we simply lack data.

Output Format#

Backlink Health Score: XX/100 (or INSUFFICIENT DATA)#

Critical Issues (fix immediately)#

High Priority (fix within 1 month)#

Medium Priority (ongoing improvement)#

Link Building Opportunities (top 10)#

Error Handling#

Fallback cascade:

1. DataForSEO available? → Use as primary (confidence: 1.0)
2. Moz configured? → Use for DA/PA/spam/anchors (confidence: 0.85)
3. Bing configured? → Use for links/competitor comparison (confidence: 0.70)
4. Always: Common Crawl for domain-level metrics (confidence: 0.50)
5. Always: Verification crawler for known link checks (confidence: 0.95)
6. Nothing works? → "Run /seo backlinks setup to configure free APIs"

Pre-Delivery Review (MANDATORY)#

Before presenting any backlink analysis to the user, run this checklist internally. Do NOT skip this step. Fix any issues found before showing the report.

Fact-Check Every Claim#

• Schema claims: Did parse_html return @type for each block? If any @type is missing, re-check — it may use @graph wrapper (valid JSON-LD, not malformed).
• "link_removed" findings: Is the page JS-rendered? If unverifiable_js, say so — never report a JS-rendered page as "link removed" (that's a false negative).
• H1 findings: Are any H1s in the h1_suspicious list? If so, note they are likely counters/stats, not semantic headings.
• Reciprocal links: If site A links to site B AND B links back to A, flag it as a reciprocal link pattern. Check outbound links against verified inbound sources.
• Health score: Are 4+ of 7 factors scored? If not, report INSUFFICIENT DATA — never show a misleading numeric score.

Verify Data Source Labels#

• Every metric in the report has a source label (e.g., "Parsed (0.95)", "CC (0.50)")
• Every "not found" result distinguishes between "not crawled" vs "below threshold" vs "error"
• Social media pages flagged as unverifiable_js (not link_removed)

Cross-Check Consistency#

• Platform detection matches actual signals (check for wp-content, shopify CDN, etc.)
• Referring domain count in summary matches the actual verified links list
• No claim is presented without a data source backing it

If ANY check fails, fix the finding before presenting. Never present inferred data as fact.

Post-Analysis#

After completing any backlink analysis command, always offer: "Generate a professional PDF report? Use /seo google report"

Reference Documentation#

Load on demand (do NOT load at startup):

• skills/seo/references/backlink-quality.md -- Detailed toxic link patterns and scoring methodology (shared reference, load when analyzing toxic links or spam scores)
• skills/seo/references/free-backlink-sources.md -- Source comparison, confidence weighting, setup guides (shared reference, load when configuring free backlink APIs)

Supporting file: LICENSE.txt#

MIT License - see repository root LICENSE file for complete terms.

Copyright (c) 2026 AgriciDaniel
https://github.com/AgriciDaniel/claude-seo

Supporting file: skills/seo/references/backlink-quality.md#

Backlink Quality Scoring Methodology#

Toxic Link Indicators (30 Patterns)#

Definite Spam (auto-flag)#

1. Link from domain with 10,000+ outbound links per page
2. Link from domain with no indexed pages in Google
3. Link from domain registered <30 days ago with 100+ outbound links
4. Exact-match anchor text from 5+ unrelated domains
5. Links from doorway pages (thin content, keyword-stuffed)
6. Links from hacked sites (pharma/casino injections)
7. Links from known link networks (check against known PBN lists)
8. Footer/sidebar site-wide links from unrelated domains
9. Links from auto-generated content (spun articles)
10. Links from domains with manual Google penalties

Likely Spam (manual review)#

11. Links from domains with >90% outbound link ratio
12. Foreign-language domains linking to English content (and vice versa)
13. Links from expired/auctioned domains repurposed for link building
14. Links from pages with >50 outbound links
15. Links from sites with no real traffic (parked domains)
16. Reciprocal link patterns across 10+ domains
17. Links from Web 2.0 properties with thin content
18. Links from article directories (EzineArticles, ArticleBase)
19. Links from low-quality guest post networks
20. Links from unrelated niches (e.g., pet site linking to SaaS)

Potentially Problematic (monitor)#

21. Links from social bookmarking sites at scale
22. Links from forum profiles (not discussions)
23. Links from press release syndication networks
24. Links from coupon/deal aggregators
25. Links from generic directories (not industry-specific)
26. Links with hidden/invisible anchor text
27. Links from pages with cloaked content
28. Links from sites with thin affiliate content
29. Links from comment sections without editorial context
30. Links from nofollow-only domains (limited SEO value)

Anchor Text Ratio Benchmarks by Industry#

Link Velocity Red Flags#

Disavow Recommendations#

When to disavow:

• Domain has received a manual penalty from Google
• Clear evidence of negative SEO attack
• Toxic link ratio exceeds 10% of total profile
• Specific domains identified as PBN or link farms

When NOT to disavow:

• Low-quality links that Google likely ignores anyway
• Nofollow links (already devalued by Google)
• Links from legitimate but low-authority sites
• Small number of spam links (<2% of profile)

Disavow file format:

# Toxic domains identified by Claude SEO backlink analysis
# Date: YYYY-MM-DD
# Total domains disavowed: X
domain:spamsite1.com
domain:linkfarm2.net
domain:pbn-network3.xyz

Supporting file: skills/seo/references/free-backlink-sources.md#

Free Backlink Data Sources#

Reference for the seo-backlinks skill. Loaded on demand when analyzing backlinks with free sources.

Source Comparison#

Confidence Weighting#

When merging data from multiple sources, apply confidence weights to each metric:

Composite formula:

weighted_score = Σ(source_score × confidence × factor_weight) / Σ(confidence × factor_weight)

When only Common Crawl is available, cap the maximum health score at 70/100 and note "limited to domain-level metrics" in the report.

Source Details#

Moz API (Tier 1)#

• Endpoint: https://api.moz.com/jsonrpc (JSON-RPC 2.0)
• Free tier: 2,500 rows/month, 1 request per 10 seconds (verify current limits at https://moz.com/products/api (opens in a new tab) — free tier limits may change)
• Signup: https://moz.com/products/api (opens in a new tab) (credit card required, not charged)
• Data: Domain Authority (0-100), Page Authority, Spam Score (1-17%), link counts, referring domains, anchor text distribution
• Script: scripts/moz_api.py
• Commands: metrics, domains, anchors, pages
• Blind spots: No link velocity, no toxic link patterns beyond Spam Score, 3-day update lag, smaller index than Ahrefs/Semrush

Bing Webmaster Tools (Tier 2)#

• Endpoint: https://ssl.bing.com/webmaster/api.svc/json/
• Free tier: Unlimited for verified sites
• Signup: https://www.bing.com/webmasters (opens in a new tab) (Microsoft account)
• Unique feature: Competitor backlink comparison (no other free tool offers this)
• Data: Inbound links with anchor text, source URL, discovery date
• Script: scripts/bing_webmaster.py
• Commands: links, counts, compare
• Blind spots: Only Bing-indexed pages (~15% of web), verified sites only, no authority metrics, no spam scoring

Common Crawl Web Graph (Always Available)#

• Data source: s3://commoncrawl/projects/hyperlinkgraph/
• Releases: Quarterly (e.g., cc-main-2025-18)
• No auth needed: Public data, free to download
• Data: Domain-level in-degree, PageRank, harmonic centrality, referring domains
• Script: scripts/commoncrawl_graph.py
• Cache: ~/.cache/claude-seo/commoncrawl/ (90-day TTL)
• Blind spots: No anchor text, no page-level data, monthly/quarterly freshness, domain-level only (e.g., "nytimes.com links to example.com" but not which page)

Verification Crawler (Always Available)#

• No auth needed: Uses existing fetch_page.py + parse_html.py
• Data: Binary verification (link exists/lost/moved), anchor text, rel attributes
• Script: scripts/verify_backlinks.py
• Input: JSON file with [{"source_url": "..."}] entries
• Polite crawling: 1-second delay between requests to same domain
• Best for: Checking if known backlinks still exist, monitoring link health

When to Recommend DataForSEO Upgrade#

Suggest the paid DataForSEO extension when:

• User needs toxic link detection beyond Moz's basic Spam Score
• User needs competitor gap analysis at scale (Bing only compares verified sites)
• User needs link velocity trends (new/lost links over time)
• User needs real-time data (free sources update monthly at best)
• User manages multiple client sites (free tier limits are per-account)
• User needs disavow file generation with confidence scoring

Data Quality Reality Check#

• Commercial tools index 35-45 trillion links across 500M+ referring domains
• Free sources combined capture 20-40% of raw backlink data
• But 60-70% of actionable intelligence since highest-authority links appear in free samples
• For sites with <500 backlinks, free sources can capture 50%+ of the meaningful profile
• Referring domain count matters more than raw backlink count for SEO
• Top 50-100 referring domains capture the majority of link authority

Five Systematic Biases in Free Data#

1. Popularity bias: Free tools crawl popular sites more, underrepresenting niche sites
2. Truncation bias: All free tools cap at 100-1,000 links, hiding the long tail
3. Own-site restriction: GSC and Ahrefs Webmaster Tools only work for verified properties
4. Missing quality metrics: Raw CC data lacks authority/toxicity scores
5. Freshness lag: Free sources update monthly at best vs. minutes for commercial