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 TrueClicks/claude-plugins --skill skill-004-ad-group-thematic-tightnessgit clone --depth 1 https://github.com/TrueClicks/claude-pluginsWrote 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/trueclicks/claude-plugins/skill-004-ad-group-thematic-tightness)<a href="https://agentmods.dev/skills/trueclicks/claude-plugins/skill-004-ad-group-thematic-tightness"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-004-ad-group-thematic-tightness/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/trueclicks/claude-plugins/skill-004-ad-group-thematic-tightness"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-004-ad-group-thematic-tightness.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 | $0.00033 | $0.00707 |
| Opus 5 | $0.00016 | $0.00353 |
| Sonnet 5 | $0.00007 | $0.00141 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
skill-004-ad-group-thematic-tightness 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 11d 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill 004: Ad Group Thematic Tightness
Purpose
Evaluate whether each ad group contains tightly themed, closely related keywords (ideally 5-20 per group). Loosely themed ad groups reduce ad relevance and Quality Score because ad copy cannot match all keyword intents.
Data Requirements
Data Source: Standard
Standard Data:
data/account/campaigns/*/*/keywords.md- Keywords per ad groupdata/account/campaigns/*/*/ads.md- Ad copy per ad groupdata/account/campaigns/*/*/ad_group.md- Ad group settingsdata/performance/campaigns/*/*/keywords_metrics_30_days.md- Keyword performance with QS
Reference GAQL:
SELECT
campaign.name,
ad_group.name,
ad_group_criterion.keyword.text,
ad_group_criterion.keyword.match_type,
ad_group_criterion.quality_info.quality_score
FROM keyword_view
WHERE ad_group_criterion.status = 'ENABLED'
AND segments.date DURING LAST_30_DAYS
Use /google-ads:get-custom if you need different date ranges or additional QS components.
Analysis Steps
- Count keywords per ad group: Flag <3 keywords (too few) or >30 keywords (too many); ideal range is 5-20
- Analyze keyword similarity: Extract root themes, calculate semantic cohesion within each ad group
- Check ad relevance: Verify ad copy contains keyword themes from the ad group
- Correlate with Quality Score: Calculate average QS per ad group; identify loose theme → low QS patterns
- Identify splitting opportunities: Find ad groups with distinct keyword clusters that should be separated
Thresholds
| Condition | Severity |
|---|---|
| Keywords per ad group > 30 | Critical |
| Low thematic cohesion (multiple distinct themes) | Critical |
| Keywords per ad group < 3 | Warning |
| Ad copy doesn't match keyword themes | Warning |
| Average QS in ad group < 5 | Warning |
Output
Use Short format by default. Use Detailed if user requests comprehensive analysis.
Short:
## Ad Group Thematic Tightness Audit
**Account:** [Name] | **Analyzed:** [X] ad groups | **Issues:** [Y]
### Critical ([Count])
- **[Ad Group]**: [X] keywords, multiple themes detected → Split into themed ad groups
### Warnings ([Count])
- **[Ad Group]**: Only [X] keywords → Merge with similar ad group or add variations
- **[Ad Group]**: Ad copy missing keyword themes → Update RSA headlines
### Recommendations
1. Split "[Ad Group]" into [X] themed groups
2. Target 10-15 keywords per ad group
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.
- 11d ago First seen · 79 lines · 33 tokens per session scan A 2f05764ee357
skill-004-ad-group-thematic-tightness is a skill published in the GitHub repository TrueClicks/claude-plugins (2 stars, last pushed 2mo ago), licensed MIT. It adds 33 tokens to every session and 707 once invoked, about $0.0002 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 2026-08-31.
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