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-150-post-peak-negative-seasonality-adjustmentgit 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-150-post-peak-negative-seasonality-adjustment)<a href="https://agentmods.dev/skills/trueclicks/claude-plugins/skill-150-post-peak-negative-seasonality-adjustment"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-150-post-peak-negative-seasonality-adjustment/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-150-post-peak-negative-seasonality-adjustment"><img src="https://agentmods.dev/badge/skills/trueclicks/claude-plugins/skill-150-post-peak-negative-seasonality-adjustment.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 | $0.00024 | $0.00602 |
| Opus 5.5 | $0.00010 | $0.00241 |
| Sonnet 5.5 | $0.00005 | $0.00120 |
| Haiku 4.5 | $0.00002 | $0.00060 |
Grade A, and why
skill-150-post-peak-negative-seasonality-adjustment 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill 150: Post-Peak Negative Seasonality Adjustment
Purpose
Audit recently completed events and recommend negative seasonality adjustments to prevent Smart Bidding from overspending during post-event conversion rate drops. After promotional peaks, algorithms continue bidding based on elevated historical performance, leading to overpayment for traffic that is now less likely to convert.
Data Requirements
Data Source: Custom GAQL Required
Need to compare event period vs. post-event period performance, which requires specific date range queries.
GAQL Query (Post-Event Performance):
SELECT
campaign.name,
segments.date,
metrics.impressions,
metrics.clicks,
metrics.conversions,
metrics.cost_micros,
metrics.average_cpc
FROM campaign
WHERE campaign.status = 'ENABLED'
AND segments.date BETWEEN '[EVENT_END_DATE]' AND '[POST_EVENT_END]'
Run via /google-ads:get-custom with event period and post-event period queries for comparison.
Additional Requirements:
- Knowledge of recently completed events (within past 30 days)
- Access to bid strategy seasonality adjustment settings
Analysis Steps
- Identify recently completed events: Review calendar for events ended within past 30 days
- Compare performance periods: Query event period vs. post-event period conversion rates
- Calculate CR decline: Measure conversion rate drop percentage post-event
- Check negative adjustments: Verify adjustments are configured for significant declines
- Monitor CPC trends: Identify elevated CPCs indicating algorithmic overbidding
Thresholds
| Condition | Severity |
|---|---|
| Post-event CR drop >30% with no negative adjustment | Critical |
| CPCs elevated >15% post-event while CR declined | Critical |
| Negative adjustment weaker than actual CR decline | Warning |
| Adjustment duration too short for recovery period | Warning |
| Minor event (<15% CR change) without adjustment | Info |
Output
Short format (default):
## Post-Peak Adjustment Audit
**Account:** [Name] | **Recent events:** [X] | **Adjustment gaps:** [Y]
### Critical ([Count])
- **Post-[Event]**: CR dropped [X]%, no adjustment -> Create -[Y]% adjustment for [dates]
### Warnings ([Count])
- **[Event]**: Adjustment -[X]% but actual drop -[Y]% -> Increase to -[Z]%
### Recommendations
1. [Specific negative adjustment with percentage, dates, and campaigns]
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 · 76 lines · 24 tokens per session scan A 38ab0ce666b1
skill-150-post-peak-negative-seasonality-adjustment is a skill published in the GitHub repository TrueClicks/claude-plugins (2 stars, last pushed 22d ago), licensed MIT. It adds 24 tokens to every session and 602 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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