Google Ads Audit logo

Google Ads Audit

Organization
cognyai
google-ads-audit

Deep Google Ads account audit — keywords, quality scores, budget pacing, search terms

Overview

Publishercognyai
Repositoryclaude-code-marketing-skills
Skill namegoogle-ads-audit
Stars
111
Forks
15
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by cognyai on GitHub. Read the source before you install it.

Installation

Install the Google Ads Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cognyai/claude-code-marketing-skills/tree/main/skill-pipeline/google-ads-audit
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cognyai/claude-code-marketing-skills.git /tmp/claude-code-marketing-skills
mkdir -p .claude/skills
cp -r /tmp/claude-code-marketing-skills/skill-pipeline/google-ads-audit .claude/skills/google-ads-audit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Google Ads Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Google Ads Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Google Ads Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Google Ads Audit

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

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

Works with

JobPrimaryAlso answers itDifferences to state
Campaigns, keywords, QS, search terms, pacingGoogle AdsMicrosoft Ads (Bing_Ads tool_get_report)Bing money is account-currency units, not micros; QS components are 1–3
Are the conversions real?Shopify / WooCommerce orders—Store = paid orders; Ads = attributed

Call list_integrations once. Report Microsoft Ads as its own block; never sum currencies.

Step 0: Cogny check

If no mcp__cogny__* tools exist (no list_integrations, no cogny_status), print this and stop:

Google Ads Audit needs your marketing data through Cogny's MCP gateway.

1. Sign up at https://cogny.com and connect Google Ads (and Microsoft Ads, Shopify or
   WooCommerce if you use them).
2. Add Cogny to .mcp.json in your project:
   {"mcpServers": {"cogny": {"type": "http", "url": "https://app.cogny.com/mcp"}}}
3. Restart Claude Code; it opens a browser for the OAuth login on first use.

Nothing to run without Cogny.

If Cogny is connected but mcp__cogny__mcp__Google_Ads__tool_execute_gaql is missing, say "connect Google Ads in Cogny" (or "reconnect Google Ads in Cogny" if it's listed but unhealthy or a read returns 401/permission denied) and stop.

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

Money fields are micros (divide by 1,000,000). An empty GAQL result (no rows, or no output) means zero (no matching entities or no activity in the window), not an error.

1. Account Discovery

mcp__cogny__mcp__Google_Ads__tool_list_accessible_accounts

Identify the account and confirm access.

2. Campaign Overview (last 30 days)

sql
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

sql
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 1–3, zero conversions with high spend, broad match bleeding. A Quality Score of 0 or null means "not scored" (too few impressions), not a low score; count those separately and don't flag them.

Microsoft Ads: mcp__cogny__mcp__Bing_Ads__tool_list_accounts for the account_id, then mcp__cogny__mcp__Bing_Ads__tool_get_report (account_id, report_type: "keyword"); QualityScore, ExpectedCtr, AdRelevance, LandingPageExperience (1 = below average, 3 = above).

4. Search Term Analysis

sql
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, and brand terms (brand name, misspellings) matching in campaigns not named as brand campaigns.

Before calling negatives "missing", check all three levels: shared lists, plus campaign- and ad-group-level negatives:

sql
SELECT shared_set.name, shared_set.type, shared_set.status, shared_set.member_count
FROM shared_set
sql
SELECT campaign.name, campaign_criterion.keyword.text, campaign_criterion.keyword.match_type
FROM campaign_criterion
WHERE campaign_criterion.type = 'KEYWORD' AND campaign_criterion.negative = TRUE
  AND campaign.status = 'ENABLED'
sql
SELECT campaign.name, ad_group.name, ad_group_criterion.keyword.text,
  ad_group_criterion.keyword.match_type
FROM ad_group_criterion
WHERE ad_group_criterion.type = 'KEYWORD' AND ad_group_criterion.negative = TRUE
  AND campaign.status = 'ENABLED'

Microsoft Ads: tool_get_report with account_id and report_type: "search_query".

Enhanced when connected: compare 30-day Ads purchase value with the store's paid revenue (Shopify tool_list_orders with query_filter: "created_at:>=YYYY-MM-DD financial_status:paid", or WooCommerce get_sales_report with date_min, date_max). Report the ratio; Ads value above total store revenue is a tracking finding.

5. Budget Pacing

sql
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

sql
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

Bucket scores 1–3 (flag), 4–6, 7–10, and "not scored" (0 or null, kept out of the averages).

7. Report findings

Use create_finding for each actionable issue found (Cloud: create_ticket, fields mapped per section 2 of the routing guide). 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. ...

Write tools (negatives, pauses, budgets) are never called by this audit; if the user asks for a change, the skill asks first.

Recording findings

Use create_ticket when the workspace has it (Cloud) and create_finding otherwise (Solo). The fields differ; see section 2 of ../../skills/marketing-engineer/references/mcp-routing.md.

Frequently asked questions

What does the Google Ads Audit AI skill do?

Deep Google Ads account audit — keywords, quality scores, budget pacing, search terms

Why use Google Ads Audit on TypingMind?

Because you install it once and use it with any model. Google Ads Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Google Ads Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cognyai/claude-code-marketing-skills/tree/main/skill-pipeline/google-ads-audit. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Google Ads Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Google Ads Audit?

As many as you like. As long as a model supports skills, you can use Google Ads Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Google Ads Audit AI skill free?

It is published on GitHub by cognyai. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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