Backlink Quality Assessment 反向連結品質評估
Released已發布Evaluate backlink quality using Domain Authority, Domain Rating, and trust metrics. Use this skill when the user needs to assess link profile health, identify toxic backlinks, or plan link building strategy — even if they say 'check my backlinks', 'link building', or 'domain authority analysis'.
演算法技能：Backlink Quality Assessment 分析與應用。
Overview概述
Backlink analysis evaluates incoming links by quality metrics (DA/DR, relevance, anchor text diversity, toxicity) to assess a site's off-page SEO strength. Quality assessment is heuristic-based using third-party metrics (Moz DA, Ahrefs DR) as PageRank proxies.
When to Use使用時機
Trigger conditions:
- Auditing a site's backlink profile for SEO health
- Identifying and disavowing toxic or spammy links
- Planning link building strategy based on competitor analysis
When NOT to use:
- When optimizing on-page content (use content SEO)
- When computing actual PageRank from raw link graphs (use PageRank algorithm)
Algorithm 演算法
IRON LAW: Backlink QUALITY Outweighs Quantity
One link from a high-authority, topically relevant domain is worth
more than hundreds from low-quality sites. Evaluate every link on:
1. Authority (DA/DR of linking domain)
2. Relevance (topical match between linking and target pages)
3. Placement (editorial in-content > footer/sidebar)
4. Anchor text (natural diversity > exact-match keyword stuffing)
Phase 1: Input Validation
Export backlink data from Ahrefs, Moz, or Search Console. Required fields: referring domain, DA/DR, anchor text, link type (dofollow/nofollow), first seen date. Gate: Complete backlink export with authority metrics.
Phase 2: Core Algorithm
- Deduplicate by referring domain (one link per domain for analysis)
- Score each link: authority (0-100) × relevance (0-1) × placement weight
- Flag toxic links: DA < 10, irrelevant foreign language, link farm patterns, PBN indicators
- Compute profile metrics: total referring domains, DR distribution, anchor text diversity index
Phase 3: Verification
Cross-reference flagged toxic links against known spam databases. Verify anchor text distribution follows natural pattern (branded > URL > keyword > misc). Gate: Toxic links identified, anchor profile analyzed.
Phase 4: Output
Return profile assessment with link quality distribution and action items.
Output Format輸出格式
{
"profile": {"referring_domains": 450, "avg_dr": 35, "toxic_count": 23, "anchor_diversity": 0.78},
"actions": [{"type": "disavow", "domains": ["spam1.com"], "reason": "link farm pattern"}],
"metadata": {"tool": "ahrefs", "export_date": "2025-01-15"}
}
Examples範例
Sample I/O
Input: 500 backlinks, 200 referring domains Expected: Distribution: 15% DR 60+, 40% DR 20-59, 45% DR 0-19. Flag 23 toxic domains for disavow.
Edge Cases
| Input | Expected | Why |
|---|---|---|
| All links from one domain | Low profile diversity | Single-source dependency is risky |
| 90% exact-match anchors | Anchor text penalty risk | Unnatural anchor pattern |
| Zero backlinks | Focus on content first | Can't optimize what doesn't exist |
Gotchas注意事項
- DA/DR are third-party estimates: They approximate PageRank but are NOT Google metrics. Two tools often disagree on the same domain's authority.
- Nofollow still matters: Google treats nofollow as a "hint." A nofollow link from a DR 90 site still has SEO value, just less than dofollow.
- Disavow carefully: Google's disavow tool is a last resort. Disavowing legitimate links harms your own profile. Only disavow clearly toxic/spammy links.
- Anchor text manipulation: Exact-match anchor text used to be a ranking factor; now it's a spam signal. Natural profiles have mostly branded and URL anchors.
- Temporal patterns: Sudden spikes in backlinks (e.g., 100 links in one day) trigger spam filters. Natural link acquisition is gradual.
References參考資料
- For link toxicity scoring methodology, see
references/toxicity-scoring.md - For competitor backlink gap analysis, see
references/competitor-gap.md