google-mobile-ads-rewarded

google-mobile-ads-rewarded is a skill for Claude Code, Codex from hamzabellouch/agent-skills. It costs 58 tokens per session (326 once invoked), scanned A, original, MIT.

A guide for adding rewarded ads to Android or iOS apps using the Google Mobile Ads SDK. Rewarded ads are full-screen ads that users choose to watch in exchange for an in-app item.

In plain words
What is it for?
Setting up rewarded ads, adding an opt-in control, handling ad callbacks, displaying the ad, and checking that the implementation works.
Why use it?
It gives developers a structured way to load the ad, react to its events, obtain user consent, and show it in the intended place.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Setting up rewarded ads, adding an opt-in control, handling ad callbacks, displaying the ad, and checking that the implementation works.

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Install with agentmods
npx agentmods add skills/hamzabellouch/agent-skills/google-mobile-ads-rewarded
Install

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.

Any agent
npx skills add hamzabellouch/agent-skills --skill google-mobile-ads-rewarded
Clone the repo
git clone --depth 1 https://github.com/hamzabellouch/agent-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for google-mobile-ads-rewarded

README.md
[![agentmods](https://agentmods.dev/badge/skills/hamzabellouch/agent-skills/google-mobile-ads-rewarded/github.svg)](https://agentmods.dev/skills/hamzabellouch/agent-skills/google-mobile-ads-rewarded)
Your own site
<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.

agentmods 80×15 button for google-mobile-ads-rewarded

Your own site · 80×15
<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>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 326 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 12d ago against content hash d2188730351c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

AI API and Agent Platform/google-mobile-ads-rewarded/SKILL.md · 40 lines

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

  1. Determine the user's platform: Identify if the project is Android or iOS. If unclear, ask before proceeding.

  2. Read the platform guide for implementation details:

    • Android: references/android-rewarded.md
    • iOS: references/ios-rewarded.md
  3. 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
Files

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.

Changes

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.

  1. 12d ago First seen · 40 lines · 58 tokens per session scan A d2188730351c

Subscribe to this mod's changes

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.