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 seranking/seo-skills --skill seo-subdomaingit clone --depth 1 https://github.com/seranking/seo-skillsWrote 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/seranking/seo-skills/seo-subdomain)<a href="https://agentmods.dev/skills/seranking/seo-skills/seo-subdomain"><img src="https://agentmods.dev/badge/skills/seranking/seo-skills/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/seranking/seo-skills/seo-subdomain"><img src="https://agentmods.dev/badge/skills/seranking/seo-skills/seo-subdomain.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.02046 |
| Opus 5 | $0.00044 | $0.01023 |
| Sonnet 5 | $0.00018 | $0.00409 |
| Haiku 4.5 | $0.00009 | $0.00205 |
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 11d 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
- SE Ranking 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.). DATA_getCreditBalance— surface remaining credits. Subdomain analysis is N × ~5 calls; cost scales with subdomain count.
- Normalise root domain (no protocol, no
-
Discover subdomains
DATA_getDomainSubdomains- 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
DATA_getDomainOverviewWorldwide- For each subdomain in scope: domain authority, traffic estimate, organic + paid keyword counts, top regions.
- This establishes a baseline for cross-subdomain comparison.
-
Per-subdomain top keywords
DATA_getDomainKeywords- 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".
-
Per-subdomain competitors
DATA_getDomainCompetitors- For each subdomain: top organic competitors by
common_keywords. - Surface: do different subdomains have different competitor sets? (Sign of legitimately separate scopes.) Do they share competitors? (Sign of redundant scopes.)
- For each subdomain: top organic competitors by
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.
- 11d ago First seen · 145 lines · 89 tokens per session scan A fb20d46ba8ef
seo-subdomain is a skill published in the GitHub repository seranking/seo-skills (139 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 2,046 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 2026-08-30.
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