Google Ads Keyword Strategy

Google Ads Keyword Strategy is a skill for Claude Code, Codex from zubair-trabzada/ai-ads-claude. It costs 45 tokens per session (4,775 once invoked), scanned A, original, MIT.

A planning tool for Google Ads, the service that shows paid listings in Google search results. It groups search terms by what people intend to do, recommends matching rules and exclusions, estimates cost-per-click ranges, and lays out campaigns and ads.

In plain words
What is it for?
Use it to research keywords, organize ad groups, choose match types, create negative-keyword lists, improve Quality Score, and draft headlines and descriptions.
Why use it?
It turns a large list of possible search terms into an organized campaign plan and helps avoid paying for irrelevant searches.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to research keywords, organize ad groups, choose match types, create negative-keyword lists, improve Quality Score, and draft headlines and descriptions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/zubair-trabzada/ai-ads-claude/ads-keywords
Install

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.

Any agent
npx skills add zubair-trabzada/ai-ads-claude --skill ads-keywords
Clone the repo
git clone --depth 1 https://github.com/zubair-trabzada/ai-ads-claude

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for Google Ads Keyword Strategy

README.md
[![agentmods](https://agentmods.dev/badge/skills/zubair-trabzada/ai-ads-claude/ads-keywords/github.svg)](https://agentmods.dev/skills/zubair-trabzada/ai-ads-claude/ads-keywords)
Your own site
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-ads-claude/ads-keywords"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-ads-claude/ads-keywords/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.

agentmods 80×15 button for Google Ads Keyword Strategy

Your own site · 80×15
<a href="https://agentmods.dev/skills/zubair-trabzada/ai-ads-claude/ads-keywords"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-ads-claude/ads-keywords.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,775 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.04775
Opus 5 $0.00023 $0.02388
Sonnet 5 $0.00009 $0.00955
Haiku 4.5 $0.00005 $0.00477

Measured 13d ago against content hash 8df36dbd0faa, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

Google Ads Keyword Strategy 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 13d 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.

skills/ads-keywords/SKILL.md · 457 lines

How it starts

The opening of the file, as written. The whole thing — 457 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Skill Purpose

Build a complete, implementation-ready Google Ads keyword strategy from scratch. This skill maps search intent across the entire buyer journey, organizes keywords into tightly themed ad groups, recommends match types, builds comprehensive negative keyword lists, estimates CPC ranges by cluster, provides Quality Score optimization tips, and outputs a campaign structure with headline and description suggestions for every ad group. The output is detailed enough that an ad buyer can build the campaigns in Google Ads Manager without additional research.

When to Use

  • User runs /ads keywords <url>
  • User asks for Google Ads keyword research, keyword strategy, or search campaign planning
  • Called as a subagent from /ads strategy (the main orchestrator)
  • User wants to launch or improve Google search campaigns
  • User needs keyword grouping, negative keywords, or ad group architecture

Input Requirements

  • Required: A business URL to analyze
  • Optional: Target location/geography, monthly budget, existing Google Ads data, specific products/services to focus on, competitor URLs

How to Execute

Step 1: Business & Market Intelligence

Fetch the business URL using WebFetch and extract:

Data Point Where to Find
Business name Page title, logo, about page
Industry/category Services, products, positioning
Products/services offered Product pages, service pages, pricing page
Geographic focus Service areas, locations, shipping scope
Price positioning Pricing page, product prices, "starting at" text
Current SEO keywords Meta titles, H1s, page URLs, blog topics
Value proposition Hero section, tagline, about page
Competitor names "Why choose us" sections, comparison pages
Customer language Testimonials, reviews, FAQ content

Run keyword research searches:

WebSearch: "[Business type]" Google Ads keywords
WebSearch: "[Industry]" high intent keywords
WebSearch: "[Product/service]" search terms people use
WebSearch: "[Business Name]" competitors Google Ads
WebSearch: "[Industry]" average CPC Google Ads 2025
WebSearch: site:[competitor URL] (to understand competitor positioning)

Read the full file on GitHub · 457 lines

Changes

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.

  1. 13d ago First seen · 457 lines · 45 tokens per session scan A 8df36dbd0faa

Subscribe to this mod's changes

Google Ads Keyword Strategy is a skill published in the GitHub repository zubair-trabzada/ai-ads-claude (246 stars, last pushed 5mo ago), licensed MIT. It adds 45 tokens to every session and 4,775 once invoked, about $0.0002 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens