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.
npx skills add swan-gtm/gtm-skills --skill google-ads-auditgit clone --depth 1 https://github.com/swan-gtm/gtm-skillsWrote 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.
[](https://agentmods.dev/skills/swan-gtm/gtm-skills/google-ads-audit)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/google-ads-audit"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/google-ads-audit/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.
<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/google-ads-audit"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/google-ads-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00146 | $0.13691 |
| Opus 5.5 | $0.00058 | $0.05476 |
| Sonnet 5.5 | $0.00029 | $0.02738 |
| Haiku 4.5 | $0.00015 | $0.01369 |
Grade A, and why
google-ads-audit 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 1mo 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.
How it starts
The opening of the file, as written. The whole thing — 1,200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Adapted from the GoMarble Paid Media Claude Skills repository (https://github.com/gomarble-ai/gomarble-ai-paid-media-claude-skills) by its author, shared under GoMarble's attribution license. Works with any data source: a connected ads MCP such as GoMarble, CSV exports, screenshots, or pasted tables.
A consolidated set of skills for analyzing and optimizing Google Ads accounts. These skills are framework-agnostic - the analytical logic (Q1–Q5 query tiers, auction-pressure diagnosis, PMax maturity gates, item classification) applies regardless of where the data comes from.
The skills define what to know, what data to look for, how to interpret it, and how to recommend action. They do not depend on any specific tool integration.
Read-and-recommend only. These skills never make changes to the user's Google Ads account. Claude reads data and produces recommendations in plain language; the user applies the recommended changes themselves in the Google Ads UI.
Data Sources Are Not All Equal
Data can come from four kinds of sources, but they have very different completeness. Some skill rules silently break on weaker sources - most notably, PMax asset performance labels and PMax search term insights are NOT in default Google Ads CSV exports. Always identify the source first and consult the Data Source Compatibility Matrix below before applying any rule.
| Priority | Source | Notes |
|---|---|---|
| 1 (preferred) | A connected MCP server exposing Google Ads data (e.g. GoMarble) with GAQL access | All rules work. Query each Google Ads resource via GAQL. |
| 2 | CSV / Excel exports from Google Ads UI | Most basic rules work, but PMax assets, PMax search insights, and Quality Score components require separate UI reports the user often doesn't realise they need. |
| 3 (narrow questions only) | Screenshots of report tables | Use only for spot questions on metrics visible in the screenshot. Skip deep analysis. |
| 4 (last resort) | Direct copy-paste of metric values | Treat as user-asserted; ask for the underlying export when stakes are real. |
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.
- 1mo ago First seen · 1,200 lines · 146 tokens per session scan A ae40eb3d5bad
google-ads-audit is a skill published in the GitHub repository swan-gtm/gtm-skills (221 stars, last pushed 8d ago), licensed MIT. It adds 146 tokens to every session and 13,691 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-09-11.
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