Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add amirjahfar1/automate-seo-with-claude --skill seo-subdomaingit clone --depth 1 https://github.com/amirjahfar1/automate-seo-with-claudeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/amirjahfar1/automate-seo-with-claude/seo-subdomain)<a href="https://agentmods.dev/skills/amirjahfar1/automate-seo-with-claude/seo-subdomain"><img src="https://agentmods.dev/badge/skills/amirjahfar1/automate-seo-with-claude/seo-subdomain/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/amirjahfar1/automate-seo-with-claude/seo-subdomain"><img src="https://agentmods.dev/badge/skills/amirjahfar1/automate-seo-with-claude/seo-subdomain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00089 | $0.02170 |
| Opus 5 | $0.00044 | $0.01085 |
| Sonnet 5 | $0.00018 | $0.00434 |
| Haiku 4.5 | $0.00009 | $0.00217 |
Grade A, and why
seo-subdomain scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Example output: examples/seo-subdomain-notion-so-20260514/SUBDOMAINS.md
Subdomain Analysis
Map a domain's subdomain ecosystem. Which subdomains exist, what each ranks for, where they overlap, and whether the structure is healthy or fragmented. Output: an ownership map (which topic is owned by which subdomain), a fragmentation report, and recommendations for consolidate / split / leave alone.
Prerequisites
- DataForSEO MCP server connected.
- User provides: a target root domain (e.g.
example.com). The skill discovers subdomains automatically. - Optional:
--limit Nto cap the number of subdomains analysed (default: top 10 by ranked keyword count).
Process
-
Validate & preflight
- Normalise root domain (no protocol, no
www.). - Cost note: DataForSEO bills per call; subdomain analysis is N × ~5 calls and scales with subdomain count. Use the documented
limit/ceilingparams (and--limit) to cap.
- Normalise root domain (no protocol, no
-
Discover subdomains
mcp__dataforseo__dataforseo_labs_google_subdomains- List all subdomains of the root domain.
- For each: keyword count, traffic estimate, backlinks count.
- Sort by ranked-keyword count descending.
- Apply
--limit(default top 10).
-
Per-subdomain overview
mcp__dataforseo__dataforseo_labs_google_domain_rank_overview- For each subdomain in scope: domain rank, traffic estimate, organic + paid keyword counts, top regions.
- This establishes a baseline for cross-subdomain comparison.
-
Per-subdomain top keywords
mcp__dataforseo__dataforseo_labs_google_ranked_keywords- For each subdomain: top 100 organic keywords with positions, intent, traffic.
- Cluster keywords by topic. This skill's grouping is a lightweight per-subdomain ownership map, not a content plan — token-grouping by head term + intent is sufficient here. (For full content-cluster planning use
seo-keyword-cluster, which now clusters by SERP overlap, not text similarity.) - Each subdomain gets a list of "owned topics" (clusters where it dominates) and "minor topics".
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 145 lines · 89 tokens per session scan A c2c6267aed4e
seo-subdomain is a skill published in the GitHub repository amirjahfar1/automate-seo-with-claude (2 stars, last pushed 3mo ago), licensed MIT. It adds 89 tokens to every session and 2,170 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
seo-site-audit-pro
Flagship comprehensive SEO audit combining Ahrefs and GSC data in sequential waves with checkpoint saves. Use when user says "site audit pro", "full audit", "comprehensive audit", "audit with live data", "deep audit", "pro audit", "complete SEO audit", "run a full site audit", or "audit everything for this domain".…
seo-content
Content quality and E-E-A-T analysis with AI citation readiness assessment. Enhanced with live Ahrefs (actual keyword rankings, positions) and GSC (search query performance) data to validate static E-E-A-T analysis with real user behavior. Use when user says "content quality", "E-E-A-T", "content analysis"…
seo-core-web-vitals
Dedicated Core Web Vitals deep-dive: pull field data (CrUX / PageSpeed Insights), fall back to Lighthouse lab data, score LCP, INP, and CLS against Google's thresholds at the 75th percentile, and run per-metric diagnosis playbooks with concrete fixes. Use when user says "core web vitals", "CWV", "LCP", "INP", "CLS"…
seo-geo
Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. GEO analysis enriched with Ahrefs Brand Radar AI visibility data when available. Includes brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring…
seo-lighthouse-audit
Run a Lighthouse audit against any URL via the local Lighthouse CLI or the PageSpeed Insights API fallback, parse category scores and failed audits, and map every failed audit ID to its official Chrome docs page plus a one-line fix. Use when user says "lighthouse", "lighthouse audit", "run lighthouse", "lighthouse…
seo-llms-txt
Generate, validate, or audit llms.txt files for AI search visibility. Crawls site structure, generates spec-compliant Markdown index for LLMs. Use when user says "llms.txt", "llm txt", "AI crawlers", "generate llms", "LLM file", "AI readability file".