name: google-ads-audit description: Deep Google Ads account audit — keywords, quality scores, budget pacing, search terms version: "1.0.0" author: Cogny AI requires: cogny-mcp platforms: [google-ads] user-invocable: true argument-hint: "[full|keywords|budget|quality|search-terms]" allowed-tools:

• mcp__cogny__google_ads__*
• mcp__cogny__create_finding
• WebFetch
• WebSearch

Google Ads Audit

Comprehensive Google Ads account audit using live data via Cogny's MCP server.

Requires: Cogny Agent subscription ($9/mo) — Sign up

Prerequisites Check

Before starting, verify you have Google Ads MCP tools available. If mcp__cogny__google_ads__tool_execute_gaql is not available:

This skill requires Cogny's Google Ads MCP server.

1. Sign up at https://cogny.com/agent
2. Connect your Google Ads account
3. Add your API key to .mcp.json
4. Restart Claude Code

See the README for setup instructions.

Usage

/google-ads-audit — full account audit /google-ads-audit keywords — keyword performance only /google-ads-audit budget — budget pacing only /google-ads-audit quality — quality scores only /google-ads-audit search-terms — search term analysis only

Full Audit Steps

1. Account Discovery

google_ads__tool_list_accessible_accounts

Identify the account and confirm access.

2. Campaign Overview (last 30 days)

SELECT campaign.name, campaign.status, campaign.bidding_strategy_type,
  campaign_budget.amount_micros, metrics.cost_micros, metrics.conversions,
  metrics.clicks, metrics.impressions, metrics.conversions_value
FROM campaign
WHERE segments.date DURING LAST_30_DAYS
ORDER BY metrics.cost_micros DESC

3. Keyword Performance

SELECT ad_group_criterion.keyword.text, ad_group_criterion.keyword.match_type,
  ad_group_criterion.quality_info.quality_score, campaign.name,
  metrics.cost_micros, metrics.conversions, metrics.clicks, metrics.impressions
FROM keyword_view
WHERE segments.date DURING LAST_30_DAYS AND metrics.cost_micros > 0
ORDER BY metrics.cost_micros DESC LIMIT 50

Flag: QS < 4, zero conversions with high spend, broad match bleeding

4. Search Term Analysis

SELECT search_term_view.search_term, search_term_view.status, campaign.name,
  metrics.cost_micros, metrics.conversions, metrics.clicks
FROM search_term_view
WHERE segments.date DURING LAST_30_DAYS AND metrics.cost_micros > 0
ORDER BY metrics.cost_micros DESC LIMIT 30

Flag: irrelevant terms, high-spend zero-conversion terms, missing negatives

5. Budget Pacing

SELECT campaign.name, campaign_budget.amount_micros, metrics.cost_micros,
  metrics.impressions
FROM campaign
WHERE segments.date DURING LAST_7_DAYS AND campaign.status = 'ENABLED'

Calculate: daily budget vs daily spend ratio per campaign

6. Quality Score Distribution

SELECT ad_group_criterion.quality_info.quality_score,
  ad_group_criterion.quality_info.creative_quality_score,
  ad_group_criterion.quality_info.search_predicted_ctr,
  ad_group_criterion.quality_info.post_click_quality_score,
  ad_group_criterion.keyword.text, campaign.name
FROM keyword_view
WHERE ad_group_criterion.quality_info.quality_score IS NOT NULL
ORDER BY ad_group_criterion.quality_info.quality_score ASC

7. Report findings

Use create_finding for each actionable issue found. Include specific data, estimated impact, and recommended action.

Present a summary table:

Google Ads Audit: [Account Name]
Health Score: X/100

Campaign Performance (30d):
Total Spend: [X] | Conversions: [X] | Avg CPA: [X]

Issues Found: [N]
- [Critical] ...
- [High] ...
- [Medium] ...

Top 3 Actions:
1. [Highest impact with estimated savings]
2. ...
3. ...