ads-google▌
agricidaniel/claude-ads · updated Apr 8, 2026
Negative Keyword Rules (critical: bad negatives kill campaigns):
Google Ads Deep Analysis
Process
- Collect Google Ads account data (export, Change History, Search Terms Report)
- Validate: confirm data covers ≥30 days and includes Search Terms Report before proceeding
- Read
ads/references/google-audit.mdfor full 74-check audit - Read
ads/references/benchmarks.mdfor Google-specific benchmarks - Read
ads/references/scoring-system.mdfor weighted scoring - Evaluate all applicable checks as PASS, WARNING, or FAIL
- Validate: confirm all 74 checks evaluated before calculating score
- Calculate Google Ads Health Score (0-100)
- 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.jsonor 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★28 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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