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-127-trending-search-term-detectiongit 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-127-trending-search-term-detection)<a href="https://agentmods.dev/skills/trueclicks/claude-plugins/skill-127-trending-search-term-detection"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-127-trending-search-term-detection/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-127-trending-search-term-detection"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-127-trending-search-term-detection.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 | $0.00026 | $0.00620 |
| Opus 5.5 | $0.00010 | $0.00248 |
| Sonnet 5.5 | $0.00005 | $0.00124 |
| Haiku 4.5 | $0.00003 | $0.00062 |
Grade A, and why
skill-127-trending-search-term-detection 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 21d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill 127: Trending Search Term Detection
Purpose
Analyze search term data across time periods to identify rising trends (opportunities to add as keywords), declining terms (investigate relevance), and new emerging queries worth capturing.
Data Requirements
Data Source: Standard + Custom GAQL
Standard Data:
data/performance/campaigns/*/*/search_terms_metrics_30_days.md- Recent search terms
GAQL Query (for trend analysis):
SELECT
search_term_view.search_term,
campaign.name,
ad_group.name,
segments.date,
metrics.impressions,
metrics.clicks,
metrics.cost_micros,
metrics.conversions
FROM search_term_view
WHERE segments.date DURING LAST_14_DAYS
AND metrics.impressions > 0
ORDER BY search_term_view.search_term, segments.date
Run via /google-ads:get-custom with query name search_term_trends.
Analysis Steps
- Fetch multi-period data: Get search term data segmented by date for trend analysis
- Calculate week-over-week changes: Compare this week vs last week impressions/clicks
- Identify rising trends: Terms with >50% impression increase
- Flag declining terms: Terms with >30% impression decrease
- Spot new terms: First-time appearances with conversion potential
Thresholds
| Condition | Severity |
|---|---|
| New term with conversion, not added as keyword | Critical |
| Rising term (>100% increase) with good CTR | Warning |
| Declining term (>50% drop) with high spend | Warning |
| High-volume term not in keyword list | Info |
Output
Short format (default):
## Search Term Trends Audit
**Account:** [Name] | **Period:** Last 14 days | **Trending Terms:** [X]
### Rising Trends - Add as Keywords ([Count])
- **"[Term]"**: +[X]% impressions, [Y] conversions → Add as [match type]
- **"[Term]"**: +[X]% impressions, high CTR → Add as exact match
### New High-Potential Terms ([Count])
- **"[Term]"**: First appearance, [X] conversions → Add immediately
### Declining Terms - Investigate ([Count])
- **"[Term]"**: -[X]% impressions → Check relevance/seasonality
### Recommendations
1. Add [X] rising terms as keywords
2. Investigate [Y] declining terms
3. Monitor [Z] new terms for patterns
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.
- 21d ago First seen · 83 lines · 26 tokens per session scan A ddf5e8c82e54
skill-127-trending-search-term-detection is a skill published in the GitHub repository TrueClicks/claude-plugins (2 stars, last pushed 22d ago), licensed MIT. It adds 26 tokens to every session and 620 once invoked, about $0.0001 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 2026-10-08.
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