seo-backlinks

Before analysis, detect available data sources: Run python scripts/backlinks_auth.py --check --json to detect all sources at once. If no sources are configured beyond the always-available tier: Produce all 7 sections below. Each section lists data sources in preference order. DataForSEO: dataforseo_backlinks_summary → total backlinks, referring domains, domain rank, follow ratio, trend. Moz API: python scripts/moz_api.py metrics --json → Domain Authority, Page Authority, Spam Score, linking root domains, external links. Common Crawl: python scripts/commoncrawl_graph.py --json → in-degree (referring domain count), PageRank, harmonic centrality. Scoring: DataForSEO: dataforseo_backlinks_anchors Moz API: python scripts/moz_api.py anchors --json Bing Webmaster: python scripts/bing_webmaster.py links --json (extract anchor text from link details) Healthy distribution benchmarks: Flag if exact-match anchors exceed 15% -- this is a Google Penguin risk signal. DataForSEO: dataforseo_backlinks_referring_domains Moz API: python scripts/moz_api.py domains --json → domains with DA scores Common Crawl: python scripts/commoncrawl_graph.py --json → top referring domains (domain-level, no authority scores) Analyze: DataForSEO: dataforseo_backlinks_bulk_spam_score + toxic patterns from reference Moz API: Spam Score from python scripts/moz_api.py metrics --json (1-17% scale, >11% = high risk)...