seo-backlinks-profile

Example output: [examples/seo-backlinks-profile-stripe-com-20260514/PROFILE.md](../../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 WebFetch tool optional (for spot-checking flagged toxic candidates).
• mcp__firecrawl-mcp__firecrawl_scrape optional (for the new step 8b — link-source verification).

Process

1. Validate target & preflight. See skills/seo-firecrawl/references/preflight.md for the canonical 3-stage preflight (credit balance, Firecrawl availability, Google APIs). Skill-specific notes:
2. Normalise domain before continuing.
3. Estimated SE Ranking cost for this skill: moderate (full-profile run; no per-keyword multiplier).
4. Firecrawl: optional. When --verify-sources is passed, step 8b (link-source verification) scrapes top-20 referring domains' linking pages to verify each link is still present and what rel it carries (dofollow / nofollow / sponsored / UGC), ~20 Firecrawl credits per run. Default off; pass --no-firecrawl to skip even if available.
5. Google APIs: not used.

1. Profile summary DATA_getBacklinksSummary
2. Total backlinks, total referring domains, dofollow/nofollow ratio, link-type distribution (text / image / form / frame), growth velocity over the last 30/90 days.

1. Referring domains DATA_getBacklinksRefDomains
2. Top N referring domains by authority. Pull authority score, link count per domain, domain TLD, country.

1. Anchor distribution DATA_getBacklinksAnchors
2. Top anchor texts by frequency.
3. 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.

1. Authority distribution DATA_getBacklinksAuthority and DATA_getDistributionOfDomainAuthority
2. Histogram of referring-domain authority: how many DA 0-9, 10-19, 20-29, etc.
3. A healthy profile has a long tail; an unhealthy profile is concentrated at DA<10.

1. IP and subnet diversity DATA_getReferringIps, DATA_getReferringIpsCount, DATA_getReferringSubnetsCount
2. Total unique IPs hosting referring domains.
3. Total unique /24 subnets.
4. Compute concentration ratio: referring_domains / unique_subnets. Healthy: ~3–10. Unhealthy: many domains share few subnets (PBN signal).

1. Growth / decay trend DATA_getNewLostBacklinksCount, DATA_getNewLostRefDomainsCount
2. Net new backlinks per month (last 6 months).
3. Net new referring domains per month.
4. Velocity changes — sharp spikes or sharp losses both deserve flags.

1. Lost links list DATA_listNewLostBacklinks, DATA_listNewLostReferringDomains
2. Sample recent losses. Are any high-authority losses?

8b. Optional: live link-source verification mcp__firecrawl-mcp__firecrawl_scrape

• Triggered only when --verify-sources is 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 html for <a href> matching the target domain. Capture: link still present (true/false/page-404), rel attribute (dofollow if 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).
• rel attribute differs from what SE Ranking flagged.
• Source page returns non-200.
• Feeds into step 9: a verified-gone link or rel=nofollow discovered 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.

1. Toxic candidate detection (heuristic — see Tips for the rules)
2. Apply the toxic heuristic to the referring-domain list.
3. Flag candidates. Each row gets a risk_score and triggers (which heuristic rules fired).
4. Never auto-disavow. Output is a reviewable list, not an action.

1. 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-sources is 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, .work historically; 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-gap for prospecting (gap analysis vs competitors).
• Pair with seo-drift to track profile composition over time.