SKILL.md
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):
claude-seo run backlinks_auth.py --check moz --json
- Bing Webmaster (free signup):
claude-seo run 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 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 setupto add free Moz and Bing API keys for richer data"
Quick Reference
| Command | Purpose |
|---|---|
/seo backlinks | Full backlink profile analysis (uses all available sources) |
/seo backlinks gap | Competitor backlink gap analysis |
/seo backlinks toxic | Toxic link detection and disavow recommendations |
/seo backlinks new | New and lost backlinks (DataForSEO only) |
/seo backlinks verify --links | 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: claude-seo run moz_api.py metrics <url> --json → Domain Authority, Page Authority, Spam Score, linking root domains, external links.
Common Crawl: claude-seo run commoncrawl_graph.py <domain> --json → PageRank, harmonic centrality, and low-confidence rank/presence data.
Scoring:
| Metric | Good | Warning | Critical | ||||
|---|---|---|---|---|---|---|---|
| Referring domains | >100 | 20-100 | 60% | 40-60% | 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: claude-seo run moz_api.py anchors <url> --json
Bing Webmaster: claude-seo run 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% |
| Partial match keyword | 5-15% | >25% |
| Long-tail / natural | 5-15% | N/A |
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-seo run moz_api.py domains <url> --json → domains with DA scores
Common Crawl: 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-seo run moz_api.py metrics <url> --json (source-label the value; apply thresholds only if verified against current Moz docs)
Verification Crawler: 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-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-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-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-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:
| Factor | Weight | Sources (preference order) | Confidence |
|---|---|---|---|
| Referring domain count | 20% | DataForSEO > Moz | 1.0 / 0.85 |
| 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, do not produce a numeric score; report low-confidence rank/presence data only.
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 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_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)