What is ad-intelligence?

An analysis workflow for mobile-app advertising, covering who runs ads, the creative formats and messages they use, and related user-acquisition signals. It can use Meta and Google ad records, including creative media, copy, landing pages, dates, countries, and impression fields when available.

Use it to scan a category, inspect competitor ads, research creative approaches, or plan where to advertise a mobile app.

It brings advertising examples and campaign signals together when you need to understand competitors or acquisition tactics.

ad-intelligence — Skill for Claude Code and Codex by AppKittie

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 AppKittie/aso-mcp-skills --skill ad-intelligence

Clone the repo

git clone --depth 1 https://github.com/AppKittie/aso-mcp-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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/ad-intelligence/github.svg)](https://agentmods.dev/skills/appkittie/aso-mcp-skills/ad-intelligence)

Your own site

<a href="https://agentmods.dev/skills/appkittie/aso-mcp-skills/ad-intelligence"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/ad-intelligence/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/appkittie/aso-mcp-skills/ad-intelligence"><img src="https://agentmods.dev/badge/skills/appkittie/aso-mcp-skills/ad-intelligence.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,436 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.

Model	Per session	Once invoked
Fable 5.1	$0.00086	$0.01436
Opus 5.5	$0.00034	$0.00574
Sonnet 5.5	$0.00017	$0.00287
Haiku 4.5	$0.00009	$0.00144

Measured 8d ago against content hash 59d3a85ac1f1, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

ad-intelligence 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 8d 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.

skills/ad-intelligence/SKILL.md · 134 lines

How it starts

The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Ad Intelligence

You are an expert in mobile app user acquisition and ad intelligence. Your goal is to help the user understand advertising patterns in the App Store — who's running ads, what creative strategies they use, and how ad spend relates to app performance.

Initial Assessment

Check for app-marketing-context.md — read it for context
Ask what the user wants:
- Category scan — who is advertising in my category?
- Competitor ads — what ads are my competitors running?
- Creative research — what ad formats and styles work?
- Strategy planning — should I run ads, and where?

Data Available

AppKittie exposes ad intelligence in two places:

Ad Creative Records

Use search_ads and get_ad_detail for creative-level data. App detail responses do not embed ad arrays.

Supported creative sources:

Meta ads (adSource: "meta")
TikTok ads (adSource: "tiktok") for Apple App Store and Google Play apps

all adds no network filter. google remains accepted for compatibility but has no current inventory.

Add mediaType: "image" or mediaType: "video" to keep one creative format on either network, e.g. search_ads(adSource: "tiktok", mediaType: "video") for TikTok video ads. Each result reports its format in type.

Creative data can include:

Ad creative images and videos (with poster frames)
Ad copy and landing pages
Delivery dates, status, surfaces, countries, and impression fields
Advertised app metadata such as app_slug, app_title, downloads, and revenue

App-Level Ad Signals

Use search_apps to discover apps with ad presence signals:

hasMetaAds: true — filter search_apps to only show apps with Meta ad creatives
hasTikTokAds: true — tiktok_ads_total_count > 0 in either store. False includes zero, missing, or null counts. Omit for no restriction.
adsSource: "all" — Apple apps with Meta creatives OR apps from either store with TikTok ads. Omit to include apps without ads; other filters are AND-combined.
hasAppleAds: true — filter to apps with Apple Search Ads presence signals

Read the full file on GitHub · 134 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.

8d ago Changed · +2 lines 59d3a85ac1f1
22d ago Changed · +6 lines · +5 tokens per session a2abc7c61336
2mo ago First seen · 126 lines · 81 tokens per session scan A b43a42914487

Subscribe to this mod's changes

ad-intelligence is a skill published in the GitHub repository AppKittie/aso-mcp-skills (7 stars, last pushed today), licensed MIT. It adds 86 tokens to every session and 1,436 once invoked, about $0.0003 per session on Opus 5.5. 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.

Analytics and metrics Marketing and SEO

ad-intelligence next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
ad-intelligenceAppKittie/aso-mcp-skills	Skill	7	today	MIT	A	86	Claude Code, Codex
imagegenopenai/codex	Skill	133k	yesterday	Apache-2.0	A	113	Codex
playwright-climicrosoft/playwright	Skill	99k	yesterday	Apache-2.0	A	19	Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginners	Skill	79k	4d ago	MIT	A	200	Claude Code, Codex
systematic-debuggingobra/superpowers	Skill	313k	3d ago	MIT	A	21	Claude Code
next-cache-components-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	95	Claude Code
next-partial-prefetching-adoptionvercel/next.js	Skill	143k	yesterday	MIT	A	103	Claude Code