apple-search-ads

apple-search-ads is a skill for Claude Code from Eronred/aso-skills. It costs 127 tokens per session (1,826 once invoked), scanned A, original, MIT.

Guidance for Apple Search Ads, the advertising system that places app ads inside the App Store when people search or browse it.

In plain words
What is it for?
Use it to plan Search Results, Search Tab, Today Tab, or Product Page campaigns and manage match types, Creative Product Sets, and return-on-ad-spend goals.
Why use it?
It helps you organize keywords, bids, ad placements, and measurement so campaigns can target people already looking for an app.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the aso-skills plugin — 40 skills shipped together

Good fit Use it to plan Search Results, Search Tab, Today Tab, or Product Page campaigns and manage match types, Creative Product Sets, and return-on-ad-spend goals.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/eronred/aso-skills/apple-search-ads
About the project

ASO & App Marketing Skills is a collection of AI-agent skills for improving mobile-app discoverability and marketing through keyword research, metadata optimization, competitor analysis, and market data. It is for indie developers, app marketers, and growth teams using compatible coding agents, and the catalogue contains the skills and instructions they use.

Eronred/aso-skills · 1,847 stars · on GitHub · appeeky.com

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 Eronred/aso-skills --skill apple-search-ads
Clone the repo
git clone --depth 1 https://github.com/Eronred/aso-skills

Made for: Claude Code.

Or install aso-skills, the plugin that ships this one along with the rest of its 40 skills.

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 apple-search-ads

README.md
[![agentmods](https://agentmods.dev/badge/skills/eronred/aso-skills/apple-search-ads/github.svg)](https://agentmods.dev/skills/eronred/aso-skills/apple-search-ads)
Your own site
<a href="https://agentmods.dev/skills/eronred/aso-skills/apple-search-ads"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/apple-search-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.

agentmods 80×15 button for apple-search-ads

Your own site · 80×15
<a href="https://agentmods.dev/skills/eronred/aso-skills/apple-search-ads"><img src="https://agentmods.dev/badge/skills/eronred/aso-skills/apple-search-ads.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,826 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. Third-party audits
  • Socket pass 22 Mar 2026
  • Snyk pass 22 Mar 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00127 $0.01826
Opus 5 $0.00063 $0.00913
Sonnet 5 $0.00025 $0.00365
Haiku 4.5 $0.00013 $0.00183

Measured 12d ago against content hash 8b0229682ca5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

apple-search-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 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.

Origin

Copies of this mod

2 near-identical copies found in the catalogue:

skills/apple-search-ads/SKILL.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Apple Search Ads

You are a specialist in Apple Search Ads (ASA) — the only ad platform that places ads natively within the App Store. ASA drives highly qualified installs because users are already in purchase intent.

Why ASA Is Different

  • Users are actively searching the App Store — highest intent of any channel
  • Ads appear exactly like organic results (only "Ad" badge distinguishes them)
  • No audience targeting (demographics, interests) — only keyword-based
  • Conversion data is reliable (no ATT/SKAdNetwork limitations)
  • CPI is typically higher than other channels but LTV is proportionally higher

Campaign Types

Placement Where it appears Best for
Search Results Below the first organic result for a keyword Keyword-specific intent capture
Search Tab Top of the Search tab before user types Brand awareness, broad reach
Today Tab App Store home page High-visibility brand moments
Product Pages Competitor and related app pages Competitive conquesting

Start with Search Results. It's the highest-intent, most measurable, most controllable placement.

Account Structure

Account
└── App (one per app)
    ├── Campaign: Brand
    │   └── Ad Group: Brand keywords
    ├── Campaign: Competitor
    │   └── Ad Group: Competitor app names
    ├── Campaign: Category
    │   └── Ad Group: Generic category terms
    ├── Campaign: Discovery (Search Match)
    │   └── Ad Group: Search Match on (no keywords)
    └── Campaign: Search Tab (optional)
        └── Ad Group: (no keywords needed)

Why Separate Campaigns

  • Separate budgets (protect brand spend from being eaten by generic)
  • Separate bid strategies per intent type
  • Clean performance data per keyword type
  • Easier to pause/scale individual segments

Match Types

Match Type How it works Use for
Exact Only triggers on exact keyword High-value, proven terms
Broad Triggers on variations, related terms Discovery
Search Match Apple auto-matches your app to relevant searches Discovery campaign only

Read the full file on GitHub · 206 lines

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 · 206 lines · 127 tokens per session scan A 8b0229682ca5

Subscribe to this mod's changes

apple-search-ads is a skill published in the GitHub repository Eronred/aso-skills (1,847 stars, last pushed 20d ago), licensed MIT. It adds 127 tokens to every session and 1,826 once invoked, about $0.0006 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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