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-adsgit 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-ads)<a href="https://agentmods.dev/skills/seranking/seo-skills/seo-ads"><img src="https://agentmods.dev/badge/skills/seranking/seo-skills/seo-ads/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-ads"><img src="https://agentmods.dev/badge/skills/seranking/seo-skills/seo-ads.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 | $0.00102 | $0.02052 |
| Opus 5 | $0.00051 | $0.01026 |
| Sonnet 5 | $0.00020 | $0.00410 |
| Haiku 4.5 | $0.00010 | $0.00205 |
Grade A, and why
seo-ads 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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Example output: examples/seo-ads-hostinger-com-20260514/ADS.md
Paid-Search Intelligence (Ads)
Map a domain's paid-search footprint and the competitive landscape around its target keywords. Output: a brief on what the brand is bidding on, who else bids on the same terms, ad-copy patterns the leading competitors use, SERP ad+shopping presence per keyword, and a recommended bid-keyword shortlist.
Prerequisites
- SE Ranking MCP server connected.
- User provides: (a) a target domain OR a target keyword (skill detects which), (b) target country (default
us).
Process
-
Validate input & preflight
- Determine: domain mode (analyse a brand's paid footprint) or keyword mode (analyse the bidding landscape for one keyword).
DATA_getCreditBalance— surface remaining credits.
-
Domain mode
DATA_getDomainAdsByDomain- Pull paid keywords the target domain bids on.
- For each: keyword, search volume, CPC, position, ad copy (title + description), URL.
- Sort by traffic-weighted score (
volume × CTR-by-paid-position × bid-share).
-
Keyword mode
DATA_getDomainAdsByKeyword- Pull all domains bidding on the target keyword.
- For each: domain, ad position, ad copy, URL.
- Surface the top 10 advertisers + their copy patterns.
-
Intent enrichment
DATA_getKeywordQuestions- For the keyword(s) in scope, pull related questions.
- Identifies question-phrased intent variants worth bidding on (often cheaper, higher conversion).
-
SERP ad/shopping presence
DATA_getSerpResults- For top 5 keywords (domain mode) or the target keyword (keyword mode):
- Use SERP-feature filters to detect ad-pack composition:
tads(top ads above organic),bads(bottom ads below organic),sads(shopping ads / Google Shopping pack),mads(mobile/map-pack ads). - Top SERP ad slots (positions 1-4 above organic, 1-3 below).
- Shopping pack presence (carousel of product cards).
- Image pack, local pack — these displace ad inventory.
- Use SERP-feature filters to detect ad-pack composition:
- Capture which advertisers occupy those slots.
- For top 5 keywords (domain mode) or the target keyword (keyword mode):
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 · 153 lines · 102 tokens per session scan A 213cbb8a2dc4
seo-ads is a skill published in the GitHub repository seranking/seo-skills (139 stars, last pushed 2mo ago), licensed MIT. It adds 102 tokens to every session and 2,052 once invoked, about $0.0005 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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