Analyzes a site's backlink profile, anchor text, toxic links, competitor gaps and disavow candidates, using whichever link data sources are configured.
Install the "seo-backlinks" agent skill from https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-backlinks into .claude/skills/seo-backlinks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seo-backlinks", then confirm the skill loads.
Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
skills CLI
$ npx skills add AgriciDaniel/claude-seo --skill seo-backlinks -a codex
Project install goes to .agents/skills/; add -g for ~/.codex/skills/.
Install the "seo-backlinks" agent skill from https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-backlinks into .agents/skills/seo-backlinks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seo-backlinks", then confirm the skill loads.
Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add AgriciDaniel/claude-seo --skill seo-backlinks -a cursor
Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.
Install the "seo-backlinks" agent skill from https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-backlinks into .cursor/skills/seo-backlinks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seo-backlinks", then confirm the skill loads.
Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
skills CLI
$ npx skills add AgriciDaniel/claude-seo --skill seo-backlinks -a gemini-cli
Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.
Install the "seo-backlinks" agent skill from https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-backlinks into .gemini/skills/seo-backlinks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seo-backlinks", then confirm the skill loads.
Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
skills CLI
$ npx skills add AgriciDaniel/claude-seo --skill seo-backlinks -a github-copilot
Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.
Install the "seo-backlinks" agent skill from https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-backlinks into .github/skills/seo-backlinks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seo-backlinks", then confirm the skill loads.
GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
skills CLI
$ npx skills add AgriciDaniel/claude-seo --skill seo-backlinks -a opencode
OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
Install the "seo-backlinks" agent skill from https://github.com/AgriciDaniel/claude-seo/tree/main/skills/seo-backlinks into .opencode/skills/seo-backlinks/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "seo-backlinks", then confirm the skill loads.
OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
Skill name
seo-backlinks
GitHub stars
19k
Token cost
~3.8k tokens
SKILL.md length
1,766 words
Files
2
Skills in repo
33
Repo updated
First seen
Licence
MIT
At a glance
Analyzes a site's backlink profile, anchor text, toxic links, competitor gaps and disavow candidates, using whichever link data sources are configured.
Works in 7 steps: Profile Overview → Anchor Text Distribution → Referring Domain Quality → …
Reviewing a site's backlink profile and anchor text distribution
SKILL.md covers Source Detection, Quick Reference, Analysis Framework and Backlink Health Score, plus 5 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Before analysis the agent checks which data sources are available: the DataForSEO MCP, the Moz API, Bing Webmaster, Keywords Everywhere, Common Crawl domain-level metrics and a verification crawler that confirms known backlinks still exist. The last two always work, so a report can still be produced from Common Crawl alone, with a suggestion to add free Moz and Bing keys.
The analysis has seven sections, each listing its data sources in order of preference, starting with a profile overview of backlinks, referring domains and authority scores. Slash commands cover the full profile, competitor backlink gaps, toxic link detection with disavow recommendations, new and lost links (DataForSEO only), verification of a list of known links, and setup help for the free APIs. Keywords Everywhere gives only domain-level figures, so it is a fallback when Moz is not configured.
When your agent uses it
Reviewing a site's backlink profile and anchor text distribution
Finding links worth disavowing
Comparing backlinks with a competitor to find gaps
Checking whether known backlinks still exist
Example prompts
“Analyze the backlink profile of https://example.com and flag toxic links.”
“Run a backlink gap analysis between example.com and example.org.”
“Check whether the links listed in links.txt still point to our site.”
“Show me how to set up the free backlink APIs.”
Requirements
Optional Moz, Bing Webmaster or Keywords Everywhere API keys
Backlink Profile Analysis loads about 3.8k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 1,766 words of instructions outside code blocks.
Always· name and description, kept in context so the agent knows when to use it
~45
When it runs· the whole SKILL.md, loaded when a task matches
~3.8k
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.
Download SKILL.mdSave it as .claude/skills/seo-backlinks/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
seo-backlinks
description
Analyze a site's backlink profile, anchors, toxic signals, competitors, gaps, and disavow candidates. Use only when links or referring domains are the requested focus.
Keywords Everywhere:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run keywordseverywhere_api.py rank <domain> --json → 0-10 Open PageRank (open_page_rank), a global rank, and a referring-domain count (referring_domains), per the current API; no anchors or individual links. Use as a fallback when Moz isn't configured; do not use in place of Moz when both are available.
Common Crawl:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run commoncrawl_graph.py <domain> --json → PageRank, harmonic centrality, and low-confidence rank/presence data.
Scoring:
Metric
Good
Warning
Critical
Referring domains
>100
20-100
<20
Follow ratio
>60%
40-60%
<40%
Domain diversity
No single domain >5%
1 domain >10%
1 domain >25%
Trend
Growing or stable
Slow decline
Rapid decline (>20%/quarter)
2. Anchor Text Distribution
DataForSEO:backlinks_anchors
Moz API:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py anchors <url> --json
Bing Webmaster:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run bing_webmaster.py links <url> --json (extract anchor text from link details)
Healthy distribution benchmarks:
Anchor Type
Target Range
Over-Optimization Signal
Branded (company/domain name)
30-50%
<15%
URL/naked link
15-25%
N/A
Generic ("click here", "learn more")
10-20%
N/A
Exact match keyword
3-10%
>15%
Partial match keyword
5-15%
>25%
Long-tail / natural
5-15%
N/A
Flag if exact-match anchors exceed 15% as a review heuristic; it may indicate unnatural or link-spam patterns.
3. Referring Domain Quality
DataForSEO:backlinks_referring_domains
Moz API:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py domains <url> --json → domains with DA scores
Common Crawl:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run commoncrawl_graph.py <domain> --json → domain-level rank/presence data, no verified referring-domain counts
Country distribution: Match target market. 80%+ from irrelevant countries = PBN signal
Domain rank distribution: Healthy profiles have links from all authority tiers
Follow/nofollow per domain: Sites that only nofollow = limited SEO value
4. Toxic Link Detection
DataForSEO:backlinks_bulk_spam_score + toxic patterns from reference
Moz API: Raw vendor spam_score from "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py metrics <url> --json (source-label the value; apply thresholds only if verified against current Moz docs)
Verification Crawler:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run verify_backlinks.py --target <url> --links <file> --json (verify suspicious links still exist)
High-risk indicators (flag immediately):
Links from known PBN (Private Blog Network) domains
Unnatural anchor text patterns (100% exact match from a domain)
Links from penalized or deindexed domains
Mass directory submissions (50+ directory links)
Link farms (sites with 10K+ outbound links per page)
Paid link patterns (footer/sidebar links across all pages of a domain)
Medium-risk indicators (review manually):
Links from unrelated niches
Reciprocal link patterns
Links from thin content pages (<100 words)
Excessive links from a single domain (>50 backlinks from 1 domain)
Load ../seo/references/backlink-quality.md for the full 30 toxic patterns and disavow criteria.
5. Top Pages by Backlinks
DataForSEO:backlinks_backlinks with target type "page"
Moz API:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py pages <domain> --json
Find:
Which pages attract the most backlinks
Pages with high-authority links (link magnets)
Pages with zero backlinks (internal linking opportunities)
404 pages with backlinks (redirect opportunities to reclaim link equity)
6. Competitor Gap Analysis
DataForSEO:backlinks_referring_domains for both domains, then compare
Bing Webmaster:"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run bing_webmaster.py compare <url1> <url2> --json
only when both properties are registered and accessible to the same Bing API
account. For arbitrary competitors, use DataForSEO, Moz, or Common Crawl.
Moz API: Compare DA/PA between domains via "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run moz_api.py metrics <url> --json for each
Output:
Domains linking to competitor but NOT to target = link building opportunities
Domains linking to both = validate existing relationships
Domains linking only to target = competitive advantage
Top 20 link building opportunities with domain authority
7. New and Lost Backlinks
DataForSEO only:backlinks_backlinks with date filters for 30/60/90 day changes
Verification Crawler: For known links, verify current status with "${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run verify_backlinks.py --target <url> --links <file> --json
Note: Free sources cannot track new/lost links over time. If this section is requested without DataForSEO, inform the user: "Link velocity tracking requires the DataForSEO extension. Free sources provide point-in-time snapshots only."
Red flags:
Sudden spike in new links (possible negative SEO attack)
Sudden loss of many links (site penalty or content removal)
Declining velocity over 3+ months (content not attracting links)
Backlink Health Score
Calculate a 0-100 score. When mixing sources, apply confidence weighting:
Factor
Weight
Sources (preference order)
Confidence
Referring domain count
20%
DataForSEO > Moz
1.0 / 0.85
Domain quality distribution
20%
DataForSEO > Moz DA distribution
1.0 / 0.85
Anchor text naturalness
15%
DataForSEO > Moz > Bing anchors
1.0 / 0.85 / 0.70
Toxic link ratio
20%
DataForSEO > Moz spam score
1.0 / 0.85
Link velocity trend
10%
DataForSEO only
1.0
Follow/nofollow ratio
5%
DataForSEO > Bing details
1.0 / 0.70
Geographic relevance
10%
DataForSEO > Bing country
1.0 / 0.70
Data sufficiency gate: Count how many of the 7 factors have at least one data source available.
4+ factors with data: Produce a numeric 0-100 score (redistribute missing weights proportionally)
Fewer than 4 factors: Do NOT produce a numeric score. Instead display:
Backlink Health Score: INSUFFICIENT DATA (X/7 factors scored)
Show individual factor scores that ARE available with their source and confidence.
Recommend: "Configure Moz API (free) for a scoreable profile. Run /seo backlinks setup"
Show full SKILL.md (743 more words)Show less
MUST NOT: score what you did not measure
When Common Crawl is the only available source, you MUST NOT produce a numeric
score of any kind -- not a health score, not a per-factor score, not an
"approximate" or "estimated" figure. Common Crawl supplies rank and presence
signals only. Report low-confidence rank/presence data and the literal string
Not Assessed in place of every number.
A finding written with source: not-assessed MUST NOT carry a numeric score.
A numeric score with fewer than 4 data sources is misleading: it implies poor
health when the reality is that we simply lack data.
Validation gate (required, not optional)
This rule has been stated in this skill before and was violated anyway, so it is
now checkable. Before writing any backlink output, run the validator:
bash
"${CLAUDE_PLUGIN_ROOT}/scripts/claude-seo" run validate_backlink_report.py --report <report>.json --json
Pass the sources you actually collected (cc_data, moz_data, bing_data,
dataforseo_data, scoring_factors, and your findings list). The
source_score_consistency check fails the report with status: FAIL when:
a numeric score is present but no scoreable source (Moz, Bing, or DataForSEO)
supplied data -- i.e. the Common-Crawl-only case, and
any finding marked source: not-assessed carries a numeric score, value,
or health_score.
If the validator returns status: FAIL, do not present the report. Fix the
findings -- replace the offending numbers with Not Assessed -- and re-run until
it passes.
Output Format
Backlink Health Score: XX/100 (or INSUFFICIENT DATA)
DataForSEO available? → Use as primary (confidence: 1.0)
Moz configured? → Use for DA/PA/spam/anchors (confidence: 0.85)
Bing configured? → Use for registered-property links and comparison only
when both properties are accessible (confidence: 0.70)
Moz not configured but Keywords Everywhere is? → Use for a Profile Overview
rank-only fallback (confidence: 0.60; single metric, no link counts/anchors)
Always: Common Crawl for domain-level metrics (confidence: 0.50)
Always: Verification crawler for known link checks (confidence: 0.95)
Before presenting any backlink analysis to the user, run this checklist internally.
Do NOT skip this step. Fix any issues found before showing the report.
Fact-Check Every Claim
Schema claims: Did parse_html return @type for each block? If any @type is missing,
re-check, it may use @graph wrapper (valid JSON-LD, not malformed).
"link_removed" findings: Is the page JS-rendered? If unverifiable_js, say so, never
report a JS-rendered page as "link removed" (that's a false negative).
H1 findings: Are any H1s in the h1_suspicious list? If so, note they are likely
counters/stats, not semantic headings.
Reciprocal links: If site A links to site B AND B links back to A, flag it as a
reciprocal link pattern. Check outbound links against verified inbound sources.
Health score: Are 4+ of 7 factors scored? If not, report INSUFFICIENT DATA, never
show a misleading numeric score.
Verify Data Source Labels
Every metric in the report has a source label (e.g., "Parsed (0.95)", "CC (0.50)")
Every "not found" result distinguishes between "not crawled" vs "below threshold" vs "error"
Social media pages flagged as unverifiable_js (not link_removed)
Cross-Check Consistency
Platform detection matches actual signals (check for wp-content, shopify CDN, etc.)
Referring domain count in summary matches the actual verified links list
No claim is presented without a data source backing it
If ANY check fails, fix the finding before presenting. Never present inferred data as fact.
Post-Analysis
After completing any backlink analysis command, always offer:
"Generate a professional PDF report? Use /seo google report"
Reference Documentation
Load on demand (do NOT load at startup):
${CLAUDE_PLUGIN_ROOT}/skills/seo/references/backlink-quality.md -- Detailed toxic link patterns and scoring methodology (shared reference, load when analyzing toxic links or spam scores)
Backlink Profile Analysis 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.
Backlink Profile Analysis compared with similar skills
Skill
Stars
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Tokens
Auto-check
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Repo updated
Backlink Profile Analysis this skillAgriciDaniel/claude-seo
Compares two domains side by side with DataForSEO data on traffic, keywords, backlinks, referring domains and keyword overlap, then states which has the stronger position.
Run a competitive SEO analysis comparing the user's site to chosen competitors across SERP overlap, content depth, backlink profiles, technical posture, and brand presence.
Audits, validates and generates hreflang tags for multi-language and multi-region sites in HTML, HTTP headers or XML sitemaps, flagging common code and return-tag mistakes.
Pulls real Google data for SEO work: Search Console, PageSpeed Insights, CrUX field data, the Indexing API and GA4 organic traffic, through /seo google commands.
Clusters keywords by how much their search results overlap and designs a hub-and-spoke content plan with an internal link matrix and an interactive cluster map.
Builds research-backed SEO content briefs with competitor scoring, per-section word counts and page-type templates, for new pages or improving existing ones.
Brings the FLOW framework's stage-specific SEO prompts into the agent, from keyword discovery through backlinks, on-page work and conversion to local SEO, loaded on demand.
Analyzes a site's backlink profile, anchor text, toxic links, competitor gaps and disavow candidates, using whichever link data sources are configured. Before analysis the agent checks which data sources are available: the DataForSEO MCP, the Moz API, Bing Webmaster, Keywords Everywhere, Common Crawl domain-level metrics and a verification crawler that confirms known backlinks still exist. The last two always work, so a report can still be produced from Common Crawl alone, with a suggestion to add free Moz and Bing keys.
When should I use Backlink Profile Analysis?
Backlink Profile Analysis fits situations like: reviewing a site's backlink profile and anchor text distribution; finding links worth disavowing; comparing backlinks with a competitor to find gaps; checking whether known backlinks still exist.
How do I install Backlink Profile Analysis in Claude Code?
Run `npx skills add AgriciDaniel/claude-seo --skill seo-backlinks -a claude-code`. Or copy the skill folder (skills/seo-backlinks in AgriciDaniel/claude-seo) into .claude/skills/seo-backlinks in your project. Claude Code loads it when a task matches its description.
How do I install Backlink Profile Analysis in Codex?
Run `npx skills add AgriciDaniel/claude-seo --skill seo-backlinks -a codex`. Or copy the skill folder (skills/seo-backlinks in AgriciDaniel/claude-seo) into .agents/skills/seo-backlinks in your project. Codex loads it when a task matches its description.
Can I use Backlink Profile Analysis 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 AgriciDaniel/claude-seo --skill seo-backlinks -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, .gemini/skills/seo-backlinks, .github/skills/seo-backlinks and .opencode/skills/seo-backlinks in your project.
What does Backlink Profile Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Backlink Profile Analysis is instructions for the agent only. Our summary lists: Optional Moz, Bing Webmaster or Keywords Everywhere API keys; Optional DataForSEO extension for premium data. Compatibility (from SKILL.md): Free: Common Crawl + verify always available. Optional: Moz API, Bing Webmaster, Keywords Everywhere (free signup). Premium: DataForSEO extension..
Does Backlink Profile Analysis access the network?
SKILL.md names 1 domain. As links in the text: bing.com. This is read from the text; nothing was executed.
Is Backlink Profile Analysis 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 Backlink Profile Analysis use?
Backlink Profile Analysis is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Backlink Profile Analysis use?
About 3.8k tokens (SKILL.md is roughly 15k 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 Backlink Profile Analysis?
Skills that share tags, products or a category with Backlink Profile Analysis: DataForSEO SEO Toolkit (zubair-trabzada/dataforseo-claude, 164 stars), SEO Domain Comparison (zubair-trabzada/dataforseo-claude, 164 stars), SEO Competitor (rampstackco/claude-skills, 941 stars) and Pp Ahrefs (mvanhorn/printing-press-library, 2.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Backlink Profile Analysis?
AgriciDaniel (a GitHub user) maintains it in AgriciDaniel/claude-seo, which has 18,574 GitHub stars. The repository holds 33 skills in this directory. The repository was last updated on October 4, 2026.
Source: AgriciDaniel/claude-seo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
