| name | seo-content |
| description | Content topical authority and gap analysis powered by the DataForSEO Labs API. Clusters a domain's ranked keywords into topics, identifies strong vs weak vs missing topic clusters versus competitors, and returns a Content Score (0-100) plus the highest-leverage content opportunities to write next. |
| 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.
SEO Content Authority Skill
Powered by: DataForSEO API — Labs ranked_keywords + Labs competitors_domain + Labs domain_intersection.
Cost: ~$0.05 per run.
Run
Pull what the target ranks for, plus the top competitor's ranked keywords:
~/.claude/skills/seo/scripts/domain_overview.py ranked --target <domain> --limit 200
~/.claude/skills/seo/scripts/domain_overview.py competitors --target <domain> --limit 5
~/.claude/skills/seo/scripts/domain_overview.py content_gap --you <domain> --competitors <c1> <c2> <c3>
Topic clustering
Group keywords into topical clusters using common stems / shared head terms.
Don't be too granular — aim for 8-15 clusters max for a typical site.
Example clusters for an SEO tool site:
- "keyword research" (head: keyword)
- "rank tracking" (head: rank, ranking)
- "backlinks" (head: backlink, link building)
- "site audit" (head: audit, technical)
- ...
For each cluster, classify it
| Status | Definition |
|---|
| Strong | 5+ keywords ranking top 10, total est. traffic > 100/mo |
| Building | Some keywords top 30, none top 10 yet |
| Weak | Keywords ranking but all below position 30 |
| Missing | Competitors rank, you don't (from content_gap) |
Content Score (0-100)
content_score = round(
50 * (strong_clusters / total_clusters) +
25 * (1 - missing_clusters / total_clusters) +
25 * (avg_position_top_quartile_score)
)
Highest-leverage content moves
Surface the top 5 specific articles to write next. Pick from the
"Missing" and "Building" clusters, prioritizing keywords with:
- Search volume > 200/mo
- Difficulty < competitor's domain rank
- Commercial or transactional intent
For each, suggest: working title, target keyword, related keywords to include,
estimated word count.
Return JSON shape
{
"content_score": 64,
"strong_topics": [{"cluster": "...", "keywords": 12, "avg_position": 5.2}],
"weak_topics": [{"cluster": "...", "keywords": 18, "avg_position": 42.1}],
"missing_topics": [{"cluster": "...", "competitor": "...", "keyword_count": 24}],
"content_recommendations": [
{"title": "...", "target_keyword": "...", "volume": 880, "difficulty": 22, "intent": "commercial"}
]
}