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 hamzabellouch/agent-skills --skill google-mobile-ads-rewardedgit clone --depth 1 https://github.com/hamzabellouch/agent-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/hamzabellouch/agent-skills/google-mobile-ads-rewarded)<a href="https://agentmods.dev/skills/hamzabellouch/agent-skills/google-mobile-ads-rewarded"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/google-mobile-ads-rewarded/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/hamzabellouch/agent-skills/google-mobile-ads-rewarded"><img src="https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/google-mobile-ads-rewarded.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 | $0.00058 | $0.00326 |
| Opus 5 | $0.00029 | $0.00163 |
| Sonnet 5 | $0.00012 | $0.00065 |
| Haiku 4.5 | $0.00006 | $0.00033 |
Grade A, and why
google-mobile-ads-rewarded 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.
What it actually says
Google Mobile Ads SDK - Rewarded Ads
Rewarded ads reward users with in-app items for interacting with full-screen ads. Rewarded ads are served after a user explicitly opts in to view a rewarded ad.
Ad Placement Guidelines
CRITICAL: You MUST evaluate and apply the following Ad Placement Guidelines before proceeding with any rewarded ad implementation.
- Determine Ad Placement:
- Identify the target file where the ad should be placed. Ask if unsure.
Workflow
-
Determine the user's platform: Identify if the project is Android or iOS. If unclear, ask before proceeding.
-
Read the platform guide for implementation details:
- Android:
references/android-rewarded.md - iOS:
references/ios-rewarded.md
- Android:
-
Follow these steps in order:
- Load the ad
- Register for ad event callbacks
- Add an opt-in UI element
- Show the ad
- Verify the implementation
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 40 lines · 58 tokens per session scan A d2188730351c
google-mobile-ads-rewarded is a skill published in the GitHub repository hamzabellouch/agent-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 326 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 2026-08-31.
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