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google-ads-quality-score

Analyze and improve Google Ads Quality Score components. Use when diagnosing high CPCs, improving Ad Rank, analyzing Expected CTR, Ad Relevance, and Landing Page Experience, or benchmarking QS by industry.

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/google-ads-quality-score/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

57%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The content is a data-rich, actionable reference with executable GAQL queries and specific thresholds, weakened by padding (promotional footer, approximate mapping table), implicit rather than explicit validation checkpoints in the playbooks, and a fully inlined structure that should be split across reference files. Core domain data is genuinely non-obvious and valuable.

Suggestions

Split the body into reference files (e.g. references/gaql-queries.md, references/playbooks.md, references/benchmarks.md) and keep SKILL.md as a concise overview with clearly signaled one-level-deep links.

Add explicit validation checkpoints to each playbook, e.g. "After 2-4 weeks, re-run GAQL Query 3 to confirm the component is no longer BELOW_AVERAGE before moving to the next fix."

Remove the promotional Synter footer and the approximate QS-to-component mapping table, and tighten the "What is Quality Score?" section to only what is non-obvious.

DimensionReasoningScore

Conciseness

Most tables (CPC modifiers by QS, industry benchmarks, page-speed targets) are domain data Claude does not reliably know, so the bulk earns its place — but the generic "What is Quality Score?" explanation, the low-value 18-row approximate QS-to-component mapping table, and the promotional Synter footer are padding that should be trimmed. It is above level 2 because the unnecessary content is a minority, not "several" padded sections of known-concept explanation.

3 / 5

Actionability

Five complete, executable GAQL queries plus concrete patterns, thresholds ("LCP < 2.5s", "min 48×48px"), and worked dollar-impact examples provide mostly copy-paste-ready guidance. It falls short of level 5 because several playbook steps are qualitative directions ("Compare to top competitors (use Ad Preview tool)", "Pull all active RSA headlines" with no accompanying query) rather than executable commands.

4 / 5

Workflow Clarity

The three playbooks have clear numbered sequences with timelines ("Timeline: 2-4 weeks to see Expected CTR improvement"), but validation checkpoints are missing or implicit — there is no step to re-run a GAQL query to verify a component actually moved from Below Average. The weekly snapshot methodology exists as a monitoring loop but is not integrated into the playbooks, so it does not reach level 4's "most checkpoints present".

3 / 5

Progressive Disclosure

The body is a ~480-line single file with clear section headers, but all content that clearly belongs in separate reference files (industry benchmarks, the GAQL query library, three detailed playbooks) is inlined with no bundle files at all. This matches the level-3 anchor ("200 lines of API reference that could be in a separate file"); structure exists, so it is not level 2, but with zero file splitting it cannot score 4 for a skill of this size.

3 / 5

Total

13

/

20

Passed

Description

92%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is strong: it pairs a concrete capability statement with an explicit, multi-trigger "Use when" clause covering the skill's full scope. Trigger terms are natural and domain-specific with only minor synonym gaps.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions ("Analyze and improve", "diagnosing high CPCs", "benchmarking QS by industry") on named domain objects (Expected CTR, Ad Relevance, Landing Page Experience), matching the level-5 anchor of comprehensive, specific action coverage. Coverage has no notable gaps, so it does not fit the level-4 anchor.

5 / 5

Completeness

It explicitly answers both "what" ("Analyze and improve Google Ads Quality Score components") and "when" ("Use when diagnosing high CPCs, improving Ad Rank, analyzing Expected CTR...") with concrete trigger phrases, matching the level-5 anchor example structure exactly. The "when" clause is explicit and multi-trigger, so it is not the level-4 anchor where the trigger is only broadly specified.

5 / 5

Trigger Term Quality

Natural phrases users would say are present ("high CPCs", "Ad Rank", "Quality Score", component names), giving good keyword coverage. It falls short of level 5 because common variations like "cost per click" spelled out or "expensive keywords" are missing.

4 / 5

Distinctiveness Conflict Risk

"Google Ads Quality Score" is a clear niche with distinct triggers (QS components, Ad Rank, CPC diagnosis) that are unlikely to fire for unrelated skills, matching the level-5 anchor. It is not level 4 because there is no meaningful overlap risk with closely related skills — the domain is narrowly pinned.

5 / 5

Total

19

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

Synter-Media-AI/free-skills

Path

skills/google-ads-quality-score/SKILL.md

Reviewed

Table of Contents

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