Agent skill

SEO Backlinks Profile

by seranking in seranking/seo-skills

Full backlink profile for a domain — referring domains, anchor text distribution, authority distribution, IP and subnet diversity, growth/decay trend, toxic-candidate flagging.

MITAuto-check passedMarketing & SEO

Install SEO Backlinks Profile

skills CLI
$ npx skills add seranking/seo-skills --skill seo-backlinks-profile -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install seranking/seo-skills seo-backlinks-profile --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/seranking/seo-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/seo-backlinks-profile .claude/skills/seo-backlinks-profile && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-backlinks-profile
GitHub stars
161
Token cost
~3k tokens
SKILL.md length
1,029 words
Files
1
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

Full backlink profile for a domain — referring domains, anchor text distribution, authority distribution, IP and subnet diversity, growth/decay trend, toxic-candidate flagging.

  • Works in 8 steps: Validate target & preflight. See… → Profile summary DATA_getBacklinksSummary → Referring domains… → …
  • The user asks backlink profile
  • SKILL.md covers Single-source by design, Prerequisites, Process and Output format, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

SEO Backlinks Profile is an agent skill from seranking/seo-skills. Full 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".

Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Link building. The repository describes itself as: Claude SEO Skills — production Claude Agent Skills for the SE Ranking MCP server. Content briefs, AI Search share of voice, audits, backlink gaps, keyword clusters, schema… The licence is MIT.

When your agent uses it

  • The user asks backlink profile
  • Link profile audit
  • Anchor distribution
  • Disavow candidates

Example prompts

  • “backlink profile”
  • “link profile audit”
  • “anchor distribution”
  • “/seo-backlinks-profile”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Validate target & preflight. See skills/seo-firecrawl/references/preflight.md for the canonical 3-stage preflight (credit balance…
  2. Profile summary DATA_getBacklinksSummary
  3. Referring domains DATA_getBacklinksRefDomains
  4. Anchor distribution DATA_getBacklinksAnchors
  5. Authority distribution DATA_getBacklinksAuthority and DATA_getDistributionOfDomainAuthority
  6. IP and subnet diversity DATA_getReferringIps, DATA_getReferringIpsCount, DATA_getReferringSubnetsCount
  7. Growth / decay trend DATA_getNewLostBacklinksCount, DATA_getNewLostRefDomainsCount
  8. Lost links list DATA_listNewLostBacklinks, DATA_listNewLostReferringDomains

What it can do on your machine

Read from SKILL.md and the folder at commit fd6d140. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Backlinks Profile loads about 3k tokens when it runs. Until then it costs about 126 tokens; SKILL.md has 1,029 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~126
When it runs · the whole SKILL.md, loaded when a task matches
~3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from seranking/seo-skills at commit fd6d140, republished under its MIT licence (© seranking). 1,029 words, ~2,996 tokens.

Download SKILL.mdSave it as .claude/skills/seo-backlinks-profile/SKILL.md (or your agent's skills folder).
name
seo-backlinks-profile
description
Full 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".

Example output: examples/seo-backlinks-profile-stripe-com-20260514/PROFILE.md

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.
Show full SKILL.md (293 more words)Show less
  1. 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.
  2. 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:

markdown
# 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.

© seranking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/seo-backlinks-profile of seranking/seo-skills.

Open the folder on GitHubat commit fd6d140

Compare with similar skills

SEO Backlinks Profile next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

SEO Backlinks Profile compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
SEO Backlinks Profile this skillseranking/seo-skills161—~3kAutomated safety check: PassMIT
FLOW SEO FrameworkAgriciDaniel/claude-seo19k2 repos~1.4kAutomated safety check: PassMIT
SEO DataforseoAgriciDaniel/codex-seo7992 repos~4.6kAutomated safety check: PassMIT
Backlink CheckRyze-AI-Adgent/open-seo-mcp-skills4.7k—~515Automated safety check: PassMIT
Beyondseobeyondtahir/beyondseo161—~4.3kAutomated safety check: PassMIT
Webobsidianxnohat/webobsidian268—~2.1kAutomated safety check: PassMIT

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Categories

Questions about SEO Backlinks Profile

What does SEO Backlinks Profile do?

Full backlink profile for a domain — referring domains, anchor text distribution, authority distribution, IP and subnet diversity, growth/decay trend, toxic-candidate flagging. SEO Backlinks Profile is an agent skill from seranking/seo-skills. Full backlink profile for a domain — referring domains, anchor text distribution, authority distribution, IP and subnet diversity, growth/decay trend, toxic-candidate flagging.

When should I use SEO Backlinks Profile?

SEO Backlinks Profile fits situations like: the user asks backlink profile; link profile audit; anchor distribution; disavow candidates.

How do I install SEO Backlinks Profile in Claude Code?

Run `npx skills add seranking/seo-skills --skill seo-backlinks-profile -a claude-code`. Or copy the skill folder (skills/seo-backlinks-profile in seranking/seo-skills) into .claude/skills/seo-backlinks-profile in your project. Claude Code loads it when a task matches its description.

How do I install SEO Backlinks Profile in Codex?

Run `npx skills add seranking/seo-skills --skill seo-backlinks-profile -a codex`. Or copy the skill folder (skills/seo-backlinks-profile in seranking/seo-skills) into .agents/skills/seo-backlinks-profile in your project. Codex loads it when a task matches its description.

Can I use SEO Backlinks Profile in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seranking/seo-skills --skill seo-backlinks-profile -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-backlinks-profile, .gemini/skills/seo-backlinks-profile, .github/skills/seo-backlinks-profile and .opencode/skills/seo-backlinks-profile in your project.

What does SEO Backlinks Profile need to run?

SKILL.md names no scripts, command-line tools or credentials: SEO Backlinks Profile is instructions for the agent only.

Does SEO Backlinks Profile access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Backlinks Profile safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Backlinks Profile use?

SEO Backlinks Profile is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Backlinks Profile use?

About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to SEO Backlinks Profile?

Skills that share tags, products or a category with SEO Backlinks Profile: FLOW SEO Framework (AgriciDaniel/claude-seo, 19k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 799 stars), Backlink Check (Ryze-AI-Adgent/open-seo-mcp-skills, 4.7k stars) and Beyondseo (beyondtahir/beyondseo, 161 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Backlinks Profile?

seranking (a GitHub organization) maintains it in seranking/seo-skills, which has 161 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 25, 2026.

Source: seranking/seo-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.