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 superamped/ai-marketing-skills --skill ad-campaign-analyzergit clone --depth 1 https://github.com/superamped/ai-marketing-skillsWrote 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/superamped/ai-marketing-skills/ad-campaign-analyzer)<a href="https://agentmods.dev/skills/superamped/ai-marketing-skills/ad-campaign-analyzer"><img src="https://agentmods.dev/badge/skills/superamped/ai-marketing-skills/ad-campaign-analyzer/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/superamped/ai-marketing-skills/ad-campaign-analyzer"><img src="https://agentmods.dev/badge/skills/superamped/ai-marketing-skills/ad-campaign-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00059 | $0.02562 |
| Opus 5 | $0.00030 | $0.01281 |
| Sonnet 5 | $0.00012 | $0.00512 |
| Haiku 4.5 | $0.00006 | $0.00256 |
Grade A, and why
ad-campaign-analyzer 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 12d 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 — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ad Campaign Analyzer
Usage
Use when reviewing a running campaign to decide what to kill, keep, or scale. Works for daily 15-minute ad reviews, weekly creative refresh planning, and monthly performance trend reviews.
Process
Step 1: Gather Inputs
Ask the user for:
- Campaign data — one of:
- CSV or table with columns: ad/ad set name, impressions, clicks, conversions, spend, CPA
- Pasted text from ads manager
- Structured list of metrics per ad
- Target CPA — the maximum they're willing to pay per acquisition
- AOV (Average Order Value) — what they earn per conversion on the front end
- Product/pricing info — what they sell, offer details, known conversion benchmarks
- Daily budget per ad set (optional) — for scaling calculations
- Days running (optional) — for statistical significance judgment
- Historical data (optional) — from previous review for trend comparison
Step 2: Parse Campaign Data
Normalize the input into a consistent table structure:
| Ad / Ad Set | Impressions | Clicks | CTR | Conversions | Spend | CPA | Days Running |
|---|
Calculate any missing derived metrics:
- CTR = clicks / impressions × 100
- CPA = spend / conversions (∞ if 0 conversions)
- Conversion rate = conversions / clicks × 100
Step 3: Grade Each Ad — Red / Yellow / Green
🔴 RED = STOP
Kill this ad. It's burning money.
Criteria (any one triggers Red):
- Spent 1.5–2x target CPA with zero conversions
- CPA is 2x+ target CPA with statistically significant spend
- Consistently worsening metrics over multiple days with no improvement signs
- CTR below 0.5% after 1,000+ impressions (the creative isn't connecting)
Action: Turn off immediately. Redirect budget to greens.
🟡 YELLOW = LEAVE ALONE
Don't touch it. It needs more data or is borderline.
Criteria:
- CPA is close to target (within 0.5–1.5x) but not enough data to be confident
- Fewer than 1,000 impressions or fewer than 20 clicks — too early to judge
- Spend is under 1x target CPA — hasn't had a fair chance yet
- Metrics are mixed (good CTR but low conversion, or vice versa)
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.
- 12d ago First seen · 280 lines · 59 tokens per session scan A d54ec2d1e5a1
ad-campaign-analyzer is a skill published in the GitHub repository superamped/ai-marketing-skills (67 stars, last pushed 25d ago), licensed MIT. It adds 59 tokens to every session and 2,562 once invoked, about $0.0003 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 2026-08-30.
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