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 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:

   • Normalise domain before continuing.
   • Estimated SE Ranking cost for this skill: moderate (full-profile run; no per-keyword multiplier).
   • 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.
   • Google APIs: not used.

2. 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.

3. Referring domains DATA_getBacklinksRefDomains

   • Top N referring domains by authority. Pull authority score, link count per domain, domain TLD, country.

4. 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.

5. Authority distribution DATA_getBacklinksAuthority and DATA_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.

6. 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).

7. 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.

8. 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-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.

9. 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_score and triggers (which heuristic rules fired).
   • Never auto-disavow. Output is a reviewable list, not an action.

10. 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 |