| name | seo-backlinks |
| description | Backlink profile audit via the DataForSEO Backlinks API. Returns total backlinks, referring domains, dofollow ratio, top anchors with over-optimization flags, top referring domains by authority, and a toxicity assessment with an Authority Score (0-100). |
| allowed-tools | ["Bash","Write"] |
Phase 0: Credential Preflight (REQUIRED — run BEFORE anything else)
Before running any of the steps below, always invoke the shared preflight check:
~/.claude/skills/seo/scripts/preflight.sh
If exit code is 0: credentials are configured — proceed with the rest of this skill silently.
If exit code is 2: the script prints the DataForSEO setup wizard to stdout. STOP, display that wizard to the user verbatim, and wait for them to paste credentials in this format:
login: their_email@example.com
password: their_api_password_here
When they reply:
- Parse
login: and password: from their message.
- Write them to
~/.claude/skills/seo/.env:
DATAFORSEO_LOGIN=<login>
DATAFORSEO_PASSWORD=<password>
chmod 600 ~/.claude/skills/seo/.env- Run a verification call:
~/.claude/skills/seo/scripts/keyword_research.py volume "test"
- If verification succeeds (real JSON returned): tell the user "✅ Credentials verified. Running your command now..." and proceed with the original request.
- If status
40104 — Please verify your account: tell the user to verify their account at https://app.dataforseo.com/, then say "continue" to retry.
- If any other auth error: ask them to double-check the API password (the long alphanumeric string from https://app.dataforseo.com/api-access — not their account login password).
Never echo credentials back to the user, never include them in tool output, and never commit them.
Backlink Audit Skill
Powered by: DataForSEO API — Backlinks summary + referring_domains + anchors + domain_intersection.
Cost: ~$0.03-0.05 per run.
Run
Three calls, parallel:
~/.claude/skills/seo/scripts/backlinks.py summary --target <domain>
~/.claude/skills/seo/scripts/backlinks.py refdomains --target <domain> --limit 100
~/.claude/skills/seo/scripts/backlinks.py anchors --target <domain> --limit 50
What to evaluate
Volume & freshness
- Total backlinks, total referring domains
- New backlinks in last 30/90 days
- Lost backlinks in last 30/90 days
- Trend: growing, stable, declining
Quality
- Dofollow ratio (50-80% is healthy; >95% looks artificial)
- Domain rank distribution of referring sites
(mostly low-rank domains = weak profile)
- TLD distribution (.edu / .gov / .org weight more)
- IP / subnet diversity (PBN red flag if all same C-class)
Anchor text
- Top 10 anchors by frequency
- Branded anchor share — should be 40-60% for a healthy profile
- <30% looks unnatural
-
80% means few topical links
- Exact-match anchor share — should be < 10%
-
20% = over-optimization, manual penalty risk
Toxicity flags
- High share of links from low-rank domains (rank < 50)
- Sudden spike in backlinks (possible negative SEO)
- Anchor text patterns suggesting paid links
- Adult / gambling / pharma TLDs in referring domains
Authority Score (0-100)
| Signal | Weight |
|---|
| log10(referring_domains) scaled to 0-30 | 30% |
| Domain rank percentile | 25% |
| Anchor naturalness (penalty for >20% exact-match) | 15% |
| Dofollow ratio in healthy band (50-80%) | 10% |
| TLD/IP diversity | 10% |
| Toxicity penalty (negative) | up to -10% |
Return JSON shape
{
"authority_score": 68,
"backlink_summary": {
"backlinks": 12345, "referring_domains": 432,
"dofollow_pct": 67, "broken_backlinks": 12,
"new_30d": 18, "lost_30d": 5
},
"top_referrers": [{"domain": "...", "rank": 612, "backlinks": 24, "dofollow": true}],
"anchor_distribution": {
