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-029-rsa-asset-performance-analysisgit 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-029-rsa-asset-performance-analysis)<a href="https://agentmods.dev/skills/trueclicks/claude-plugins/skill-029-rsa-asset-performance-analysis"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-029-rsa-asset-performance-analysis/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-029-rsa-asset-performance-analysis"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-029-rsa-asset-performance-analysis.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 | $0.00022 | $0.00627 |
| Opus 5 | $0.00011 | $0.00313 |
| Sonnet 5 | $0.00004 | $0.00125 |
| Haiku 4.5 | $0.00002 | $0.00063 |
Grade A, and why
skill-029-rsa-asset-performance-analysis 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill 029: RSA Asset Performance Analysis
Purpose
Google rates individual RSA assets (headlines, descriptions) as Best, Good, Low, or Learning. Low-rated assets reduce overall ad effectiveness and should be replaced. This analysis identifies underperformers and suggests replacements based on high-performing asset patterns.
Data Requirements
Data Source: Custom GAQL Required
Standard export does not include asset-level performance ratings.
GAQL Query:
SELECT
campaign.name,
ad_group.name,
ad_group_ad.ad.id,
ad_group_ad_asset_view.field_type,
ad_group_ad_asset_view.performance_label,
asset.text_asset.text,
asset.type,
metrics.impressions,
metrics.clicks
FROM ad_group_ad_asset_view
WHERE ad_group_ad.status = 'ENABLED'
AND segments.date DURING LAST_30_DAYS
ORDER BY ad_group_ad_asset_view.performance_label DESC
Run via /google-ads:get-custom with query name asset_performance.
Analysis Steps
- Categorize assets by rating: Best (keep/replicate), Good (no action), Low (replace), Learning (need data), Unrated (insufficient data)
- Identify Low-rated assets: List all headlines and descriptions rated Low with their campaign/ad group
- Analyze low-performer patterns: Common themes, length patterns, missing elements (CTA, benefit)
- Identify high-performer patterns: What makes Best-rated assets work - use for replacement suggestions
- Generate replacement recommendations: Based on high-performing patterns, maintain diversity
Thresholds
| Condition | Severity |
|---|---|
| >20% of assets rated Low | Critical |
| Low asset in high-spend campaign | Critical |
| Any asset rated Low | Warning |
| No Best assets in RSA | Warning |
| All assets Learning (new RSA) | Info |
Output
Short (default):
## RSA Asset Performance Audit
**Account:** [Name] | **Assets:** [X] | **Low-rated:** [Y]%
### Replace (Low-rated) ([Count])
- **[Campaign] / [Ad Group]**: "[Low asset text]" -> Suggested: "[replacement based on Best patterns]"
### Top Performers to Replicate
- "[Best asset text]" - [X] campaigns, [Y]% CTR
### Summary
| Rating | Headlines | Descriptions |
|--------|-----------|--------------|
| Best | X | X |
| Good | X | X |
| Low | X | X |
| Learning | X | X |
### Recommendations
1. [Priority replacement action]
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 · 84 lines · 22 tokens per session scan A 8565ce8c47ac
skill-029-rsa-asset-performance-analysis is a skill published in the GitHub repository TrueClicks/claude-plugins (2 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 627 once invoked, about $0.0001 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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