seo-backlinks-profile
SkillDev toolsFull backlink profile for a domain — referring domains, anchor text distribution, authority distribution, IP and subnet diversity, growth/decay trend, toxic-candidate flagging. Distinct from `seo-backlink-gap` (which is gap-vs-competitor only). Produces a profile health score and reviewable disavow candidate list (never auto-disavow). Use when the user asks "backlink profile", "link profile audit", "anchor distribution", "toxic links", "disavow candidates", or "backlink health".
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the seo-backlinks-profile skill
What this skill tells your AI
The instructions your AI receives, as published by seranking/seo-skills in skills/seo-backlinks-profile/SKILL.md and read by ahel’s review.
Example output: examples/seo-backlinks-profile-stripe-com-20260514/PROFILE.md
Backlinks Profile
A complete backlink profile audit for a domain. Surfaces composition (where do links come from?), quality (what's the authority distribution?), diversity (concentrated in a few IPs/subnets, or spread out?), trajectory (growing or decaying?), and risk (which links look manipulative?). Output includes a health score and a reviewable disavow-candidate list — never an auto-disavow.
Single-source by design
This skill consults only the SE Ranking backlink index. We don't blend Ahrefs / Moz / Majestic / DataForSEO / Common Crawl into the same report. That's a deliberate choice, not a limitation:
- Internally consistent metrics. Authority scores, anchor counts, and refdomain totals are computed against a single crawl. Multi-source blends produce numbers that look authoritative but actually average across crawls with different sampling, different freshness, and different definitions of "backlink" — the resulting ratios (e.g. dofollow %, anchor distribution) are noise.
- Reproducible health scores. The 100-point health score in this report can be re-run a quarter later against the same source and the deltas are meaningful. With multi-source blends, a score drift can mean anything: source A reweighted, source B refreshed, source C changed its toxic heuristic.
- No data-source independence to model. Any "do these sources agree?" question is unanswerable without a second backlink graph; we don't pretend to answer it. If you need cross-source confirmation (e.g. before legal disavow, before a high-stakes outreach campaign), pair this profile with a manual spot-check against Ahrefs/Majestic — that's a research task, not a skill output.
If your workflow specifically requires multi-source blending (large agencies, link-builders billing on link counts), this skill is the wrong tool — use a vendor that aggregates multiple indexes. For everyone else, single-source produces the more honest report.
Prerequisites
- SE Ranking MCP server connected.
- User provides: a target domain.
- Claude's
WebFetchtool optional (for spot-checking flagged toxic candidates). mcp__firecrawl-mcp__firecrawl_scrapeoptional (for the new step 8b — link-source verification).
Process
-
Validate target & preflight. See
skills/seo-firecrawl/references/preflight.mdfor the canonical 3-stage preflight (credit balance, Firecrawl availability, Google APIs). Skill-specific notes:- Normalise domain before continuing.
- Estimated SE Ranking cost for this skill: moderate (full-profile run; no per-keyword multiplier).
- Firecrawl: optional. When
--verify-sourcesis passed, step 8b (link-source verification) scrapes top-20 referring domains' linking pages to verify each link is still present and whatrelit carries (dofollow / nofollow / sponsored / UGC), ~20 Firecrawl credits per run. Default off; pass--no-firecrawlto skip even if available. - Google APIs: not used.
-
Profile summary
DATA_getBacklinksSummary- Total backlinks, total referring domains, dofollow/nofollow ratio, link-type distribution (text / image / form / frame), growth velocity over the last 30/90 days.
-
Referring domains
DATA_getBacklinksRefDomains- Top N referring domains by authority. Pull authority score, link count per domain, domain TLD, country.
-
Anchor distribution
DATA_getBacklinksAnchors- Top anchor texts by frequency.
- Classify each anchor: branded (contains brand name), exact-match commercial (the target's primary commercial keyword), partial-match, generic ("click here", "read more", "this page"), naked URL, image-alt-derived.
-
Authority distribution
DATA_getBacklinksAuthorityandDATA_getDistributionOfDomainAuthority- Histogram of referring-domain authority: how many DA 0-9, 10-19, 20-29, etc.
- A healthy profile has a long tail; an unhealthy profile is concentrated at DA<10.
-
IP and subnet diversity
DATA_getReferringIps,DATA_getReferringIpsCount,DATA_getReferringSubnetsCount- Total unique IPs hosting referring domains.
- Total unique /24 subnets.
- Compute concentration ratio:
referring_domains / unique_subnets. Healthy: ~3–10. Unhealthy: many domains share few subnets (PBN signal).
-
Growth / decay trend
DATA_getNewLostBacklinksCount,DATA_getNewLostRefDomainsCount- Net new backlinks per month (last 6 months).
- Net new referring domains per month.
- Velocity changes — sharp spikes or sharp losses both deserve flags.
-
Lost links list
DATA_listNewLostBacklinks,DATA_listNewLostReferringDomains- Sample recent losses. Are any high-authority losses?
8b. Optional: live link-source verification mcp__firecrawl-mcp__firecrawl_scrape
- Triggered only when
--verify-sourcesis passed (default off — credit-conscious). - For the top 20 referring domains by authority (from step 3), pick the highest-authority linking page per domain. Scrape each (20 Firecrawl credits typical).
- For each scrape, parse the returned
htmlfor<a href>matching the target domain. Capture: link still present (true/false/page-404),relattribute (dofollowif absent or empty, else the literal value:nofollow,ugc,sponsored, or combinations), surrounding context (anchor text + 50 chars before/after). - Surface mismatches against the SE Ranking-reported state in
evidence/08b-source-verification.md:- Link gone — SE Ranking still reports it as live (lag/error).
relattribute differs from what SE Ranking flagged.- Source page returns non-200.
- Feeds into step 9: a verified-gone link or
rel=nofollowdiscovered post-hoc upgrades the toxic-candidate signal for that referring domain. - If Firecrawl unavailable (or flag not passed): skip entirely. SE Ranking's flagged state remains the source of truth — the skill's "Single-source by design" framing already explains why that's a deliberate trade-off.
-
Toxic candidate detection (heuristic — see Tips for the rules)
- Apply the toxic heuristic to the referring-domain list.
- Flag candidates. Each row gets a
risk_scoreandtriggers(which heuristic rules fired). - Never auto-disavow. Output is a reviewable list, not an action.
-
Synthesise
PROFILE.md
Output format
Create a folder seo-backlinks-profile-{target-slug}-{YYYYMMDD}/ with:
seo-backlinks-profile-{target-slug}-{YYYYMMDD}/
├── PROFILE.md (synthesised report — primary deliverable; inlines summary, authority distribution, diversity, trend)
├── 02-referring-domains.md (top N with authority — load-bearing reference for outreach/audit)
├── 03-anchors.md (anchor distribution + classification — load-bearing reference)
├── disavow-candidates.csv (toxic-flagged rows for review — load-bearing CSV)
└── evidence/
├── 01-summary.md (DATA_getBacklinksSummary top-line — raw step output)
├── 04-authority-distribution.md (histogram — raw step output)
├── 05-diversity.md (IPs + subnets + concentration — raw step output)
├── 06-trend.md (last 6 months new/lost — raw step output)
├── 07-losses-sample.md (recent lost backlinks)
└── 08b-source-verification.md (only if --verify-sources ran: live link + rel attribute checks for top-20 sources)
Step files 01, 04, 05, 06 are inlined as sections in PROFILE.md; the copies in evidence/ preserve raw step output for reproducibility. 02-referring-domains.md, 03-anchors.md, and disavow-candidates.csv stay at top level — outreach/audit teams consult them directly.
PROFILE.md follows this shape:
# Backlinks Profile: {domain}
> Snapshot dated {YYYY-MM-DD}
## Health score: **{n}/100**
| Dimension | Score | Notes |
|---|---|---|
| Authority distribution | {n}/20 | {comment} |
| Anchor diversity | {n}/20 | {comment} |
| IP/subnet diversity | {n}/20 | {comment} |
| Growth trajectory | {n}/20 | {comment} |
| Toxic candidate ratio | {n}/20 | {comment} |
## Top-line numbers
| Metric | Value |
|---|---|
| Backlinks | {n} |
| Referring domains | {n} |
| Dofollow / nofollow | {n}% / {n}% |
| Unique IPs | {n} |
| Unique subnets | {n} |
| Domain : subnet ratio | {ratio} |
| New ref-domains last 30d | {n} |
| Lost ref-domains last 30d | {n} |
| Toxic candidates flagged | {n} ({% of total}) |
## Authority distribution
| DA bucket | Domains | % |
|---|---|---|
| 70+ | {n} | {%} |
| 50–69 | {n} | {%} |
| 30–49 | {n} | {%} |
| 10–29 | {n} | {%} |
| 0–9 | {n} | {%} |
## Anchor distribution
| Class | Count | % | Healthy range | Status |
|---|---|---|---|---|
| Branded | {n} | {%} | 30–60% | {✓/⚠} |
| Generic | {n} | {%} | 15–30% | {✓/⚠} |
| Naked URL | {n} | {%} | 10–25% | {✓/⚠} |
| Partial-match | {n} | {%} | 10–20% | {✓/⚠} |
| Exact-match commercial | {n} | {%} | <5% | {✓/⚠ over-optimised} |
| Image-alt-derived | {n} | {%} | <10% | {✓/⚠} |
## Trend (last 6 months)
| Month | New backlinks | Lost backlinks | Net |
|---|---|---|---|
| {M-5} | {n} | {n} | {n} |
| {M-4} | {n} | {n} | {n} |
| ... |
## Toxic candidates ({n} flagged)
See `disavow-candidates.csv`. Top 10 by risk_score:
| Domain | Authority | Triggers | Risk |
|---|---|---|---|
| {domain} | {DA} | {DA<10, sitewide>5, exact-match-anchor} | High |
| ... |
**⚠ NEVER AUTO-DISAVOW.** Hand this list to a human for review. Disavow a domain only after confirming the link is manipulative AND the domain is not delivering referral traffic AND removal requests have failed.
## Recommended next steps
1. {Action}
2. {Action}
3. {Action}
disavow-candidates.csv columns: domain,authority,backlinks_count,sitewide_links,top_anchor,anchor_class,risk_score,triggers,sample_url
Tips
- Respect rate limit. The endpoints in steps 2–8 are ~15 calls; pace sequentially.
- Cost: ~25–40 SE Ranking credits typical for a full profile run. Optional step 8b adds 20 Firecrawl credits when
--verify-sourcesis passed (one scrape per top-20 source domain). - Toxic heuristic rules (any 2+ triggers = candidate):
- Authority < 10 (low-trust source).
- Sitewide link count > 5 (footer/sidebar links across many pages — manipulation signal).
- Exact-match commercial anchor on >50% of links from this domain.
- Hosted in known link-farm subnet (when unique IPs / unique subnets ratio is heavily concentrated).
- Domain name is a non-pronounceable string of characters (very strong PBN signal).
- TLD is in the high-spam list (
.xyz,.click,.workhistorically; verify against current spam-domain reports).
- Healthy anchor distribution: branded should be the largest class (30–60%); exact-match commercial should be small (<5%) — over-optimised commercial anchors trigger Penguin-era penalties.
- Healthy growth: steady 10–20% YoY referring-domain growth is the goal. Sharp spikes (>50% in a month) often indicate paid links and trigger algorithmic suspicion.
- Disavow conservatively. Removing links via outreach is preferred. Disavow only as a last resort; never disavow domains that send referral traffic.
- Pair with
seo-backlink-gapfor prospecting (gap analysis vs competitors). - Pair with
seo-driftto track profile composition over time.
Signals
- GitHub stars
- 142
- Forks
- 34
- Last commit
- Jun 2026
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seo-backlinks-profile- Source
- github.com/seranking/seo-skills