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Agent skill

SEO Ads

by seranking in seranking/seo-skills

Paid-search competitive landscape for a domain or keyword. An agent skill from seranking/seo-skills.

MITAuto-check passedMarketing & SEO

Install SEO Ads

skills CLI
$ npx skills add seranking/seo-skills --skill seo-ads -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install seranking/seo-skills seo-ads --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/seranking/seo-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/seo-ads .claude/skills/seo-ads && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
seo-ads
GitHub stars
160
Token cost
~2.1k tokens
SKILL.md length
625 words
Files
1
Skills in repo
32
Repo updated
First seen
Licence
MIT

At a glance

Paid-search competitive landscape for a domain or keyword. An agent skill from seranking/seo-skills.

  • Works in 9 steps: Validate input & preflight → Domain mode DATA_getDomainAdsByDomain → Keyword mode DATA_getDomainAdsByKeyword → …
  • The user asks paid search analysis
  • SKILL.md covers Prerequisites, Process, Output format and Tips
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

SEO Ads is an agent skill from seranking/seo-skills. Paid-search competitive landscape for a domain or keyword. Pulls SE Ranking's PPC data — domain ad keyword footprint, ad copy patterns, who else bids on the same keywords, SERP shopping/ad-pack visibility — and produces a competitive ads brief plus a recommended bid-keyword shortlist. Use when the user asks "paid search analysis", "competitor ads", "PPC competitive", "ad copy intelligence", "shopping pack", "who bids on this keyword", or "paid keyword footprint".

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Copywriting and Paid advertising. The repository describes itself as: Claude SEO Skills — production Claude Agent Skills for the SE Ranking MCP server. Content briefs, AI Search share of voice, audits, backlink gaps, keyword clusters, schema… The licence is MIT.

When your agent uses it

  • The user asks paid search analysis
  • PPC competitive
  • Ad copy intelligence
  • Who bids on this keyword

Example prompts

  • “paid search analysis”
  • “competitor ads”
  • “PPC competitive”
  • “/seo-ads”

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Validate input & preflight
  2. Domain mode DATA_getDomainAdsByDomain
  3. Keyword mode DATA_getDomainAdsByKeyword
  4. Intent enrichment DATA_getKeywordQuestions
  5. SERP ad/shopping presence DATA_getSerpResults
  6. Ad copy pattern analysis
  7. Paid-keyword gap (domain mode) DATA_getDomainKeywords with type: 'adv'
  8. Recommended bid-keyword shortlist
  9. Synthesise ADS.md

What it can do on your machine

Read from SKILL.md and the folder at commit fd6d140. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

SEO Ads loads about 2.1k tokens when it runs. Until then it costs about 119 tokens; SKILL.md has 625 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~119
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from seranking/seo-skills at commit fd6d140, republished under its MIT licence (© seranking). 625 words, ~2,053 tokens.

Download SKILL.mdSave it as .claude/skills/seo-ads/SKILL.md (or your agent's skills folder).
name
seo-ads
description
Paid-search competitive landscape for a domain or keyword. Pulls SE Ranking's PPC data — domain ad keyword footprint, ad copy patterns, who else bids on the same keywords, SERP shopping/ad-pack visibility — and produces a competitive ads brief plus a recommended bid-keyword shortlist. Use when the user asks "paid search analysis", "competitor ads", "PPC competitive", "ad copy intelligence", "shopping pack", "who bids on this keyword", or "paid keyword footprint".

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

  1. 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.

  2. 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).

  3. 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.

  4. 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).

  5. 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.
    • Capture which advertisers occupy those slots.

  6. Ad copy pattern analysis

    • Cluster ad headlines + descriptions by recurring patterns.
    • Identify: USP language used by leaders, pricing/discount mentions, audience segmentation, CTA verbs.
    • Highlight outliers (advertisers doing something different).

  7. Paid-keyword gap (domain mode) DATA_getDomainKeywords with type: 'adv'

    • Pull the user's domain's paid keywords using the type: 'adv' switch.
    • For each top competitor (from step 2 or DATA_getDomainCompetitors with type: 'adv'): pull their paid keywords with type: 'adv'.
    • Diff: paid keywords competitors bid on that the user's domain doesn't.
    • This becomes the highest-leverage portion of the bid-keyword shortlist (step 8).
    • Skip in keyword mode (no domain to gap against).

  8. Recommended bid-keyword shortlist

    • For domain mode: paid-keyword gap from step 7 + adjacent question-intent variants.
    • For keyword mode: question-intent and long-tail variants that are likely cheaper than the head term.
    • Each row: keyword, est. CPC, est. volume, who else bids, why-recommended.

  9. Synthesise ADS.md

Show full SKILL.md (222 more words)Show less

Output format

Create a folder seo-ads-{target-slug}-{YYYYMMDD}/ with:

seo-ads-{target-slug}-{YYYYMMDD}/
├── ADS.md                              (synthesised brief — primary deliverable; inlines paid footprint, bidding landscape, SERP ad/shopping pack, ad copy patterns, paid keyword gap)
├── recommended-keywords.csv            (bid-keyword shortlist — load-bearing CSV the PPC team pastes into bid tooling)
└── evidence/
    ├── 01-paid-footprint.md           (domain mode: brand's paid keywords — raw step output)
    ├── 02-bidding-landscape.md        (keyword mode: advertisers on the keyword — raw step output)
    ├── 03-question-variants.md        (DATA_getKeywordQuestions enrichment)
    ├── 04-serp-ad-shopping-pack.md    (SERP feature inventory per keyword)
    ├── 05-ad-copy-patterns.md         (clustered headline/description patterns)
    └── 06-paid-keyword-gap.md         (domain mode: type='adv' diff vs competitors)

Step files 01, 02, 04, 05, 06 are inlined as sections in ADS.md; the copies in evidence/ preserve the raw step outputs for reproducibility.

ADS.md follows this shape:

markdown
# Paid-Search Intelligence: {target}

> Snapshot dated {YYYY-MM-DD} · Country: {country} · Mode: {domain | keyword}

## Footprint summary
- Paid keywords: {n}
- Estimated paid traffic: {n}/mo
- Average CPC: ${n}
- SERP slots covered: {n} of top-4 above organic across {n} target keywords

## Top 10 paid keywords (domain mode)

| Keyword | Volume | CPC | Position | Ad copy excerpt |
|---|---|---|---|---|
| {kw} | {n} | ${n} | {pos} | "{headline} — {snippet}" |
| ...

## Bidding landscape (keyword mode — for "{keyword}")

| Advertiser | Position | Ad copy excerpt | URL |
|---|---|---|---|
| {domain} | {pos} | "{headline} — {snippet}" | {url} |
| ...

## Ad copy patterns (top patterns observed)

1. **Pricing-led:** "{N}% off — start at ${X}/mo" — used by {n} advertisers.
2. **Outcome-led:** "Get {specific outcome} in {time}" — used by {n}.
3. **Trust-led:** "Trusted by {n} {audience}" — used by {n}.
4. ...

## SERP feature inventory

| Keyword | Top ads | Shopping pack | PAA | Image pack |
|---|---|---|---|---|
| {kw} | {advertiser list} | {✓/✗} | {✓/✗} | {✓/✗} |
| ...

## Recommended bid-keyword shortlist

See `recommended-keywords.csv`. Top 10:

| Keyword | Volume | Est. CPC | Why |
|---|---|---|---|
| {kw} | {n} | ${n} | Question-intent variant; competitor X bids on head term but not this. |
| ...

## Constraints / caveats
- CPC and volume estimates are directional. Actual costs depend on Quality Score, time of day, audience, etc.
- {Note any ad-copy that's clearly seasonal / promotional and may not represent steady-state.}

## Recommended next step
Cross-reference these paid keywords with `seo-keyword-cluster` output to find under-served paid clusters. For organic content opportunities corresponding to these paid keywords, run `seo-keyword-niche`.

recommended-keywords.csv columns: keyword,volume,cpc_estimate,position_target,intent,competitor_count,why_recommended

Tips

  • Respect rate limit. Domain mode: ~3–5 calls. Keyword mode: ~3 calls. Plus a few SERP queries.
  • Cost: ~10–20 credits typical for domain mode; ~5–10 for keyword mode.
  • CPC estimates lag. SE Ranking's CPC data is not real-time auction data; treat as ±30% directional.
  • Ad copy often reveals competitor positioning before product launches do — periodic review (quarterly) catches strategic shifts.
  • Question-intent variants often have lower CPC and higher conversion than head terms. The shortlist in step 8 prioritises these.
  • Pair with seo-keyword-niche for organic content opportunities derived from paid keyword research.
  • Pair with seo-competitor-pages if the bidding landscape reveals "X vs Y" / "alternatives" intent — those keywords convert best as comparison pages, not paid ads.
  • Ads data via shared DATA_ tools* — beyond the dedicated DATA_getDomainAdsByDomain / DATA_getDomainAdsByKeyword, the type: 'adv' enum switch on DATA_getDomainKeywords, DATA_getDomainKeywordsComparison, DATA_getDomainCompetitors, DATA_getDomainPages, and similar tools surfaces the paid view of the same data structures. Combine with the tads/bads/sads/mads SERP-feature filters and the CPC filter on SERP queries to map paid landscape comprehensively.
  • Don't recommend paid keywords without context. The shortlist is a starting point for the PPC team, not an autopilot.

© seranking, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/seo-ads of seranking/seo-skills.

Open the folder on GitHubat commit fd6d140

Compare with similar skills

SEO Ads next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

SEO Ads compared with similar skills
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SEO Ads this skillseranking/seo-skills160—~2.1kAutomated safety check: PassMIT
Ad CreativeLeoYeAI/openclaw-marketing-skills1k8 repos~3.4kAutomated safety check: PassCustom licence
Marketing OsYuzzyuk/marketing-os538—~2.5kAutomated safety check: PassMIT
Ad Creativecoreyhaines31/marketingskills54k—~6.3kAutomated safety check: PassMIT
Meta Ad Builderkrusemediallc/arcads-claude-code1.6k—~1.7kAutomated safety check: NotesMIT
Hook MethodologyDV0x/creative-ad-agent119—~3.1kAutomated safety check: PassMIT

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Categories

Questions about SEO Ads

What does SEO Ads do?

Paid-search competitive landscape for a domain or keyword. An agent skill from seranking/seo-skills. SEO Ads is an agent skill from seranking/seo-skills. Paid-search competitive landscape for a domain or keyword.

When should I use SEO Ads?

SEO Ads fits situations like: the user asks paid search analysis; PPC competitive; ad copy intelligence; who bids on this keyword.

How do I install SEO Ads in Claude Code?

Run `npx skills add seranking/seo-skills --skill seo-ads -a claude-code`. Or copy the skill folder (skills/seo-ads in seranking/seo-skills) into .claude/skills/seo-ads in your project. Claude Code loads it when a task matches its description.

How do I install SEO Ads in Codex?

Run `npx skills add seranking/seo-skills --skill seo-ads -a codex`. Or copy the skill folder (skills/seo-ads in seranking/seo-skills) into .agents/skills/seo-ads in your project. Codex loads it when a task matches its description.

Can I use SEO Ads in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add seranking/seo-skills --skill seo-ads -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/seo-ads, .gemini/skills/seo-ads, .github/skills/seo-ads and .opencode/skills/seo-ads in your project.

What does SEO Ads need to run?

SKILL.md names no scripts, command-line tools or credentials: SEO Ads is instructions for the agent only.

Does SEO Ads access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is SEO Ads safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does SEO Ads use?

SEO Ads is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does SEO Ads use?

About 2.1k tokens (SKILL.md is roughly 8.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to SEO Ads?

Skills that share tags, products or a category with SEO Ads: Ad Creative (LeoYeAI/openclaw-marketing-skills, 1k stars), Marketing Os (Yuzzyuk/marketing-os, 538 stars), Ad Creative (coreyhaines31/marketingskills, 54k stars) and Meta Ad Builder (krusemediallc/arcads-claude-code, 1.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains SEO Ads?

seranking (a GitHub organization) maintains it in seranking/seo-skills, which has 160 GitHub stars. The repository holds 32 skills in this directory. The repository was last updated on June 25, 2026.

Source: seranking/seo-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.