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-quality-score-diagnosisgit 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-quality-score-diagnosis)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/google-ads-quality-score-diagnosis"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/google-ads-quality-score-diagnosis/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-quality-score-diagnosis"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/google-ads-quality-score-diagnosis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00094 | $0.00776 |
| Opus 5 | $0.00047 | $0.00388 |
| Sonnet 5 | $0.00019 | $0.00155 |
| Haiku 4.5 | $0.00009 | $0.00078 |
Grade A, and why
google-ads-quality-score-diagnosis 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 9d 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 — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quality Score Diagnosis and Prioritization
Applies whenever a keyword-level quality signal is available and CPC or ad-rank performance is in question.
The play
- Treat Quality Score as a diagnostic, not a KPI. Never optimize toward the score itself or report it as a headline metric — it exists to point at which of three components (expected click-through rate, ad relevance, landing page experience) is dragging a keyword down, each rated below average, average, or above average.
- Weight the fix list by spend, not by score. A below-average component on a keyword burning real budget matters far more than the same flag on a keyword that barely spends — fix the expensive ones first, and don't chase score on low-volume keywords where the read is unreliable in the first place.
- Route each below-average component to a different fix, because they don't share a cause: below-average expected CTR means the ad isn't compelling enough for the query it's showing on; below-average ad relevance means the ad and the query have drifted apart, usually from an ad group covering too many themes; below-average landing page experience means the page itself — speed, match to intent, ease of use — isn't holding up its end.
- For ad relevance specifically, check ad group breadth before touching the ad copy. A group covering fifteen loosely-related terms with one ad can't be relevant to all of them — split it into tighter, single-theme groups before rewriting anything.
- Give landing page experience issues time and the right owner — cite the estimated CPC savings across affected spend to justify the page work, since that's usually a different team's backlog item, not something to fix inside the account.
- Re-check on a weekly cadence, not daily — day-to-day Quality Score noise from Google's own recalculation will make a fine account look like it's regressing.
What good looks like
- The best diagnosis never treats a "below average" flag as one problem — it separates which of the three components is actually driving it, because the fix for each is completely different work.
- The common mistake is chasing Quality Score to 10. Scores of 7-8 are the realistic ceiling for most keywords; treating anything below 10 as broken burns effort with diminishing returns instead of moving to the next highest-spend keyword that actually needs the attention.
- A good fix list is spend-weighted and names the specific component driving each entry — a list that says "improve relevance" without saying which keywords, which component, and how much spend is affected hasn't actually diagnosed anything.
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.
- 9d ago First seen · 65 lines · 94 tokens per session scan A 583e9a7e35fb
google-ads-quality-score-diagnosis is a skill published in the GitHub repository swan-gtm/gtm-skills (153 stars, last pushed 2d ago), licensed MIT. It adds 94 tokens to every session and 776 once invoked, about $0.0005 per session on Opus 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 2026-09-03.
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