Backlink Profile Analysis
Source Detection
Before analysis, detect available data sources:
- DataForSEO MCP (premium): Check if
dataforseo_backlinks_summarytool is available - Moz API (free signup):
python scripts/backlinks_auth.py --check moz --json - Bing Webmaster (free signup):
python scripts/backlinks_auth.py --check bing --json - Common Crawl (always available): Domain-level graph with PageRank
- Verification Crawler (always available): Checks if known backlinks still exist
Run python 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 setupto add free Moz and Bing API keys for richer data"
Quick Reference
| Command | Purpose |
|---|---|
/seo backlinks <url> | Full backlink profile analysis (uses all available sources) |
/seo backlinks gap <url1> <url2> | Competitor backlink gap analysis |
/seo backlinks toxic <url> | Toxic link detection and disavow recommendations |
/seo backlinks new <url> | New and lost backlinks (DataForSEO only) |
/seo backlinks verify <url> --links <file> | Verify known backlinks still exist |
/seo backlinks setup | Show setup instructions for free backlink APIs |
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: python scripts/moz_api.py metrics <url> --json → Domain Authority, Page Authority, Spam Score, linking root domains, external links.
Common Crawl: python scripts/commoncrawl_graph.py <domain> --json → in-degree (referring domain count), PageRank, harmonic centrality.
Scoring:
| Metric | Good | Warning | Critical |
|---|---|---|---|
| Referring domains | >100 | 20-100 | <20 |
| Follow ratio | >60% | 40-60% | <40% |
| Domain diversity | No single domain >5% | 1 domain >10% | 1 domain >25% |
| Trend | Growing or stable | Slow decline | Rapid decline (>20%/quarter) |
2. Anchor Text Distribution
DataForSEO: dataforseo_backlinks_anchors
Moz API: python scripts/moz_api.py anchors <url> --json
Bing Webmaster: python scripts/bing_webmaster.py links <url> --json (extract anchor text from link details)
Healthy distribution benchmarks:
| Anchor Type | Target Range | Over-Optimization Signal |
|---|---|---|
| Branded (company/domain name) | 30-50% | <15% |
| URL/naked link | 15-25% | N/A |
| Generic ("click here", "learn more") | 10-20% | N/A |
| Exact match keyword | 3-10% | >15% |
| Partial match keyword | 5-15% | >25% |
| Long-tail / natural | 5-15% | N/A |
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: python scripts/moz_api.py domains <url> --json → domains with DA scores
Common Crawl: python 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 python scripts/moz_api.py metrics <url> --json (1-17% scale, >11% = high risk)
Verification Crawler: python 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: python 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!): python 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 python 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 python 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:
| Factor | Weight | Sources (preference order) | Confidence |
|---|---|---|---|
| Referring domain count | 20% | DataForSEO > Moz > CC in-degree | 1.0 / 0.85 / 0.50 |
| Domain quality distribution | 20% | DataForSEO > Moz DA distribution | 1.0 / 0.85 |
| Anchor text naturalness | 15% | DataForSEO > Moz > Bing anchors | 1.0 / 0.85 / 0.70 |
| Toxic link ratio | 20% | DataForSEO > Moz spam score | 1.0 / 0.85 |
| Link velocity trend | 10% | DataForSEO only | 1.0 |
| Follow/nofollow ratio | 5% | DataForSEO > Bing details | 1.0 / 0.70 |
| Geographic relevance | 10% | DataForSEO > Bing country | 1.0 / 0.70 |
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)
| Section | Status | Score | Data Source |
|---|---|---|---|
| Profile Overview | pass/warn/fail | XX/100 | Moz (0.85) |
| Anchor Distribution | pass/warn/fail | XX/100 | Moz (0.85) |
| Referring Domain Quality | pass/warn/fail | XX/100 | CC (0.50) |
| Toxic Links | pass/warn/fail | XX/100 | Moz Spam (0.85) |
| Top Pages | info | N/A | Moz (0.85) |
| Link Velocity | pass/warn/fail | XX/100 | DataForSEO only |
Critical Issues (fix immediately)
High Priority (fix within 1 month)
Medium Priority (ongoing improvement)
Link Building Opportunities (top 10)
Error Handling
| Error | Cause | Resolution |
|---|---|---|
| No sources configured | No API keys, no DataForSEO | Run /seo backlinks setup |
| Moz rate limit | Free tier: 1 req/10s | Wait 10 seconds, retry. Built into script. |
| Bing site not verified | Site not verified in Bing | Verify at https://www.bing.com/webmasters |
| CC download timeout | Large graph file, slow connection | Use --timeout 180 flag |
| DataForSEO unavailable | Extension not installed | Run ./extensions/dataforseo/install.sh |
| No backlink data returned | Domain too new or very small | Note: small sites may have <10 backlinks |
Fallback cascade:
- DataForSEO available? → Use as primary (confidence: 1.0)
- Moz configured? → Use for DA/PA/spam/anchors (confidence: 0.85)
- Bing configured? → Use for links/competitor comparison (confidence: 0.70)
- Always: Common Crawl for domain-level metrics (confidence: 0.50)
- Always: Verification crawler for known link checks (confidence: 0.95)
- Nothing works? → "Run
/seo backlinks setupto 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
@typefor each block? If any@typeis missing, re-check — it may use@graphwrapper (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_suspiciouslist? 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(notlink_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)