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 T4wroot/agentic-seo --skill app-adsgit clone --depth 1 https://github.com/T4wroot/agentic-seoWrote 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/t4wroot/agentic-seo/app-ads)<a href="https://agentmods.dev/skills/t4wroot/agentic-seo/app-ads"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/app-ads/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/t4wroot/agentic-seo/app-ads"><img src="https://agentmods.dev/badge/skills/t4wroot/agentic-seo/app-ads.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 | $0.00092 | $0.00802 |
| Opus 5.5 | $0.00037 | $0.00321 |
| Sonnet 5.5 | $0.00018 | $0.00160 |
| Haiku 4.5 | $0.00009 | $0.00080 |
Grade A, and why
app-ads 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 1mo 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.
This is a copy
100% identical to app-ads — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Paid Ads: App Ads
Guides app advertising: app install campaigns, user acquisition (UA), and in-app promotion. Use when promoting mobile apps (iOS, Android); conversion = install or in-app action, not landing page.
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Key Platforms
| Platform | Best for | Conversion |
|---|---|---|
| Google App Campaigns | Android + iOS; automated across Search, YouTube, Display, Play, Discover | Install, in-app event |
| Apple Search Ads (ASA) | iOS only; high-intent App Store search | Install |
| Meta App Install | Facebook/Instagram; demand gen for apps | Install, in-app event |
| TikTok App Install | Younger users; viral creative | Install |
Google App Campaigns
- Reach: Search, YouTube, Display, Google Play, Discover
- Bidding: Maximize Conversions (automated) or Target CPI/CPA (30+ conversions/week)
- Creative: Provide diverse assets (videos, images, text); algorithm tests combinations
- iOS: SKAdNetwork; conversion value mapping; Firebase for in-app events
- Bid–budget ratio: ≥10× for CPI, ≥15× for CPA
Apple Search Ads
- Placements: App Store search results, Today tab, Search tab, product pages
- Modes: Basic (automated) or Advanced (keywords, audiences, bids)
- Audience: High-intent users actively searching in App Store
- ASO benefit: Can improve keyword rankings as secondary effect
Metrics
| Metric | Use |
|---|---|
| CPI | Cost per install |
| CPA | Cost per acquisition (in-app action) |
| LTV | Lifetime value; iOS often higher than Android |
| Retention | D1, D7, D30; quality signal |
iOS vs Android: iOS typically higher LTV, higher CPI; Android greater scale, lower CPI.
Tracking
- Firebase: In-app events, audiences, value-based optimization (Google)
- SKAdNetwork: iOS attribution; configure conversion value mapping
- UTM: Use
utm_medium=apporcpcwithutm_sourcefor app campaigns in GA4
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.
- 1mo ago First seen · 68 lines · 92 tokens per session scan A e55ee30e1fd1
app-ads is a skill published in the GitHub repository T4wroot/agentic-seo (15 stars, last pushed 1mo ago), licensed MIT. It adds 92 tokens to every session and 802 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to app-ads, differing in 0 lines, and is treated as a copy.
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