What does this skill do, and when should you use it?
This skill is for developers implementing Google Mobile Ads banner ads in Android or iOS mobile applications. It first establishes the platform and the intended ad location, then examines the target file’s view hierarchy. It recommends Inline Adaptive Banner for scrollable content and Large Anchored Adaptive for static content. The workflow proceeds through defining the ad view, setting its size, registering load events, loading the ad, and verifying the implementation.
Determines whether the project is Android or iOS; identifies the target file and inspects its view hierarchy; selects Inline Adaptive Banner for scrollable content or Large Anchored Adaptive for non-scrollable content; asks whether the ad should be anchored to the top or bottom when positioning is unspecified; directs the user to define the ad view, set the ad size, register ad-load events, load the banner, and verify the implementation; reminds the user to replace the test ad unit ID after successful implementation.
- An Android developer needs to place a banner ad inside a scrolling list, scroll view, or grid.
- An iOS developer needs to configure a banner ad in a static screen layout.
- A mobile developer has not yet identified the target screen or parent container for the ad.
- A team wants a defined sequence for banner setup, loading, and verification.
How do you install this skill?
- Before production use, add SDK installation and initialization, privacy/consent management, advertising data-flow disclosure, production ad-unit confirmation, and failure fallback guidance.
- Reconcile the Android API and imports, especially the contradictory BannerAd deprecation statement versus the prescribed AdView usage, and build-test in real Android/iOS projects.
- Confirm regional network reachability and compliance requirements; users in mainland China may not be able to reliably access the core advertising service.
- Local filesystem
Run npx skills add google/skills and select Google Mobile Ads SDK - Banner Ads during installation. The repository contains 90 skills; the source does not document a more specific single-skill installation command or client-specific destination.
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/google/skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/ads/google-mobile-ads-banner" ~/.claude/skills/
rm -rf "$tmp"Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.
How do you use this skill?
Once installed, send your agent any of these to trigger it:
- Implement a Google Mobile Ads banner in the scrolling view of my iOS app.
In an Agent Skills-compatible client with the skill installed, submit a request such as: "Implement a Google Mobile Ads banner in the scrolling view of my iOS app." The client should confirm the platform, target file, and view hierarchy; for non-scrollable content, it should also confirm whether the banner belongs at the top or bottom. Platform-specific instructions are referenced at references/android-banner.md and references/ios-banner.md, but their contents are not included in the source material.
What are this skill's strengths and limitations?
- Covers banner-ad implementation for both Android and iOS.
- Distinguishes adaptive banner types based on whether the content scrolls.
- Includes an ordered loading workflow, verification, and a test-ad reminder.
- The referenced Android and iOS guides are not included, so the provided SKILL.md alone cannot supply code-level implementation details.
- No test suite or evidence of validated platforms is provided.
- The source does not document costs, permission configuration, or ad-unit creation.
How does this skill compare with similar options?
Side by side with related skills; every score comes from the same FSRS standard.
| Skill | FS score | Stars | Last updated | License |
|---|---|---|---|---|
| Google Mobile Ads Banner Integrator this page ✓ Google · Official | 47 · Use with care | ★ 21k | 13d ago | Apache-2.0 |
| Google Mobile Ads Rewarded Ads Guide ✓ Google · Official | 47 · Use with care | ★ 21k | 13d ago | Apache-2.0 |
| Google Mobile Ads SDK Starter ✓ Google · Official | 43 · Not recommended | ★ 21k | 13d ago | Apache-2.0 |
| Google Mobile Ads Interstitial Integration Guide ✓ Google · Official | 41 · Not recommended | ★ 21k | 13d ago | Apache-2.0 |
| Google Mobile Ads Next-Gen Migration Assistant ✓ Google · Official | 46 · Use with care | ★ 21k | 13d ago | Apache-2.0 |
How did FollowSkills review this skill?
The skill asks the agent to confirm the target file, inspect the view hierarchy, and use test ad unit IDs; no malware, credential theft, or destructive default is evident. It does not disclose advertising data flows, consent and privacy handling, personalization controls, dependency security, production-release confirmation, or rollback, so points are deducted.
The workflow is ordered and includes Android callback-thread guidance plus build-verification advice. Static files contain no executable tests or CI evidence; the Android imports include BannerAd while the text calls it deprecated, and initialization, lifecycle, and failure handling are incomplete, so points are deducted.
The audience, Android/iOS platforms, scrollable versus static placement scenarios, and trigger description are reasonably clear. Non-fit boundaries, input/output boundaries, and Chinese-language support are absent; reachability of the Google advertising service from mainland China is not addressed, so points are deducted.
The repository provides platform-separated references, test IDs, version 1.0.0 metadata, an Apache-2.0 license, and a support path, with basic progressive structure. There is no changelog, explicit maintenance owner, dependency-installation guidance, complete example, FAQ, or systematic limitations section, so points are deducted.
The material can guide banner-type selection, sizing, callback registration, ad loading, and replacement of test IDs, giving it clear core-task value. It lacks complete copy-ready Android/iOS implementations and installation, initialization, privacy-compliance, and production-configuration steps; static review cannot verify the result, so the score remains conservative.
Specific method signatures, test ad unit IDs, platform references, and official documentation links provide limited auditability. There is no committed test suite, CI coverage, or third-party execution evidence, and some API/threading claims cannot be cross-validated from the supplied files, so points are deducted.
Open a dimension to read why it scored that way
Evidence confidence：Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.
See the full review method →