ads-google

agricidaniel/claude-ads · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/agricidaniel/claude-ads --skill ads-google
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summary

Negative Keyword Rules (critical: bad negatives kill campaigns):

skill.md

Google Ads Deep Analysis

Process

  1. Collect Google Ads account data (export, Change History, Search Terms Report)
  2. Validate: confirm data covers ≥30 days and includes Search Terms Report before proceeding
  3. Read ads/references/google-audit.md for full 74-check audit
  4. Read ads/references/benchmarks.md for Google-specific benchmarks
  5. Read ads/references/scoring-system.md for weighted scoring
  6. Evaluate all applicable checks as PASS, WARNING, or FAIL
  7. Validate: confirm all 74 checks evaluated before calculating score
  8. Calculate Google Ads Health Score (0-100)
  9. Generate findings report with action plan

What to Analyze

Conversion Tracking (25% weight)

  • Google tag (gtag.js) installed and firing on all pages
  • Enhanced Conversions active (hashed first-party data)
  • Consent Mode v2 implemented (required for EU/EEA)
  • Conversion actions mapped correctly (primary vs secondary)
  • Offline conversion import configured (for lead gen)
  • Server-side tagging via GTM (recommended for accuracy)
  • Attribution model: data-driven preferred (last-click as fallback only)
  • Conversion lag analysis (are conversions still trickling in?)

Wasted Spend (20% weight)

  • Search Terms Report reviewed (last 30 days minimum)
  • Negative keyword coverage adequate (shared lists + campaign-level)
  • Display placement audit (exclude low-quality sites)
  • Invalid click rate within norms (<10%)
  • Broad Match only used with Smart Bidding (NEVER without it)
  • Brand/non-brand campaigns separated
  • Geographic targeting precise (no wasted international spend)

Negative Keyword Rules (critical: bad negatives kill campaigns):

  • NEVER suggest Broad Match negatives unless explicitly justified; they block too broadly
  • Default to Exact Match [keyword] for specific irrelevant queries
  • Use Phrase Match "keyword" for irrelevant intent patterns
  • Source negatives from actual Search Terms Report irrelevant queries, NOT guesses
  • Group into themed lists: Informational (how-to, DIY, what is), Job-seeker (jobs, careers, salary), Competitor (only if intentionally excluded), Free-intent (free, crack, torrent)
  • Recommend Shared Negative Lists at the account level, not just campaign-level
  • Review existing negatives for over-blocking (are any negatives accidentally blocking converting queries?)

Account Structure (15% weight)

  • Campaign-level organization follows business logic
  • Ad groups themed tightly (15-20 keywords max per group)
  • RSA ad groups have ≥3 active ads
  • PMax campaigns structured correctly (asset groups, signals)
  • SKAGs evaluated (migrate to themed groups if present)
  • Campaign labels/naming conventions consistent

Keywords (15% weight)

  • Match type strategy appropriate (Exact → Phrase → Broad progression)
  • Quality Score distribution (aim ≥7 average)
  • Low QS keywords flagged (<5 = FAIL, 5-6 = WARNING)
  • Keyword cannibalization check (same keywords in multiple campaigns)
  • Impression share tracked for top keywords
  • Keyword bid adjustments set for devices/locations/audiences

Ads (15% weight)

  • RSA: ≥8 unique headlines, ≥3 descriptions per ad group
  • RSA: ad strength "Good" or "Excellent" (not "Poor" or "Average")
  • Pin usage minimal and strategic (over-pinning reduces RSA flexibility)
  • Ad extensions: sitelinks (≥4), callouts (≥4), structured snippets, image
  • Dynamic keyword insertion used appropriately
  • Ad copy includes CTA, value proposition, differentiators

Settings (10% weight)

  • Bid strategy appropriate for campaign maturity and goals
  • Budget pacing: no campaigns limited by budget (unless intentional)
  • Ad schedule aligned with business hours/conversion patterns
  • Device bid adjustments set based on performance data
  • Location targeting: "Presence" not "Presence or Interest"
  • Network settings: Search Partners reviewed, Display opt-out for Search

GAQL & Data Accuracy

Before analyzing data, read ads/references/gaql-notes.md for known GAQL field incompatibilities, deduplication patterns, and filter scope best practices. Key rules:

  • Deduplicate keywords by (ad_group_id + keyword_text + match_type) before any analysis
  • Only analyze ENABLED campaigns and ad groups (exclude paused/removed)
  • Filter to keywords with impressions > 0 for theme coherence checks (G03)
  • Apply legacy BMM heuristic: BROAD + Manual CPC = legacy BMM, not intentional broad (G17)
  • Only flag wasted spend on terms with >$10 spend AND 0 conversions (G16)
  • Count shared negative keyword lists alongside campaign-level negatives (G14/G15)

Google Ads MCP Integration (Optional)

For automated data collection, connect the Google Ads MCP server:

  • Tools available: search (GAQL queries), list_accessible_customers
  • Setup: Configure in .mcp.json or Claude Code MCP settings
  • Customer ID: Extract from CLAUDE.md under Accounts > Google Ads, or ask the user
  • Fallback: If MCP is not configured, fall back to manual data export (the default workflow)

When MCP is available, use it to pull Search Terms Reports, keyword data, conversion actions, and campaign structure automatically instead of requiring manual exports.

PMax Deep Dive

If Performance Max campaigns exist, additionally evaluate:

  • Asset group diversity (text, images, video, feeds)
  • Audience signals configured (custom segments, lists, demographics)
  • URL expansion settings reviewed (opt-out of irrelevant pages)
  • Brand exclusions applied (prevent cannibalizing brand search)
  • Search themes utilized (2024 feature)
  • Final URL expansion: enabled or disabled with justification
  • Insights tab reviewed (search categories, audience segments)

AI Max for Search (2026)

If AI Max for Search is available/active:

  • Broad Match + AI Max integration evaluated
  • Auto-generated headline performance monitored
  • Search term categories reviewed for relevance
  • Budget impact assessed (AI Max can shift spend)

Key Thresholds

Metric Pass Warning Fail
Quality Score (avg) ≥7 5-6 <5
CTR (Search) ≥6.66% 3-6.66% <3%
CVR (Search) ≥7.52% 3-7.52% <3%
CPC (Search) ≤$5.26 $5.26-8.00 >$8.00
Wasted Spend <10% 10-20% >20%
Ad Strength Good+ Average Poor
Invalid Clicks <5% 5-10% >10%

Output

Google Ads Health Score

Google Ads Health Score: XX/100 (Grade: X)

Conversion Tracking: XX/100  ████████░░  (25%)
Wasted Spend:        XX/100  ██████████  (20%)
Account Structure:   XX/100  ███████░░░  (15%)
Keywords:            XX/100  █████░░░░░  (15%)
Ads:                 XX/100  ████████░░  (15%)
Settings:            XX/100  ██████████  (10%)

Deliverables

  • GOOGLE-ADS-REPORT.md: Full 74-check findings with pass/warning/fail
  • Wasted spend estimate (monthly $ value)
  • Quick Wins sorted by impact
  • PMax-specific recommendations (if applicable)
  • Keyword health matrix with QS, CTR, CVR per keyword group
how to use ads-google

How to use ads-google on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add ads-google
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/agricidaniel/claude-ads --skill ads-google

The skills CLI fetches ads-google from GitHub repository agricidaniel/claude-ads and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/ads-google

Reload or restart Cursor to activate ads-google. Access the skill through slash commands (e.g., /ads-google) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.628 reviews
  • Chen Gupta· Dec 24, 2024

    We added ads-google from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Dhruvi Jain· Dec 20, 2024

    ads-google has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Charlotte Menon· Dec 20, 2024

    Solid pick for teams standardizing on skills: ads-google is focused, and the summary matches what you get after install.

  • Daniel Abbas· Nov 15, 2024

    ads-google fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Oshnikdeep· Nov 11, 2024

    Keeps context tight: ads-google is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Nikhil Desai· Nov 11, 2024

    Registry listing for ads-google matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Diya Diallo· Oct 6, 2024

    ads-google has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Oct 2, 2024

    We added ads-google from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Ishan Malhotra· Oct 2, 2024

    Useful defaults in ads-google — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diya Harris· Sep 13, 2024

    Solid pick for teams standardizing on skills: ads-google is focused, and the summary matches what you get after install.

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