# Adattributionkit

Measure ad effectiveness with privacy-preserving attribution using AdAttributionKit.

- Repository: https://github.com/dpearson2699/swift-ios-skills (1266 stars)
- Category: Engineering
- License: see repository
- Last updated: 2026-07-31
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add dpearson2699/swift-ios-skills --skill adattributionkit -g -a claude-code -y`
Codex: `npx skills add dpearson2699/swift-ios-skills --skill adattributionkit -g -a codex -y`
Cursor: `npx skills add dpearson2699/swift-ios-skills --skill adattributionkit -g -a cursor -y`
Gemini CLI: `npx skills add dpearson2699/swift-ios-skills --skill adattributionkit -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add dpearson2699/swift-ios-skills`

## Description

Measure ad effectiveness with privacy-preserving attribution using AdAttributionKit. Use when registering ad impressions, handling attribution postbacks, updating conversion values, implementing re-engagement attribution, configuring publisher or advertiser apps, or replacing SKAdNetwork with AdAttributionKit for ad measurement.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# AdAttributionKit

Privacy-preserving ad attribution for iOS 17.4+. AdAttributionKit
lets ad networks measure conversions (installs and re-engagements) without
exposing user-level data. It supports the App Store and alternative
marketplaces, and interoperates with SKAdNetwork.

Three roles exist in the attribution flow: the **ad network** (signs
impressions, receives postbacks), the **publisher app** (displays ads), and the
**advertised app** (the app being promoted).

## Contents

- [Overview and Privacy Model](#overview-and-privacy-model)
- [Publisher App Setup](#publisher-app-setup)
- [Advertiser App Setup](#advertiser-app-setup)
- [Impressions](#impressions)
- [Postbacks](#postbacks)
- [Conversion Values](#conversion-values)
- [Re-engagement](#re-engagement)
- [Common Mistakes](#common-mistakes)
- [Review Checklist](#review-checklist)
- [References](#references)

## Overview and Privacy Model

AdAttributionKit preserves user privacy through several mechanisms:

- **Crowd anonymity tiers** -- the device limits postback data granularity based
  on the crowd size associated with the ad, ranging from Tier 0 (minimal data)
  to Tier 3 (most data including publisher ID and country code).
- **Time-delayed postbacks** -- postbacks are sent 24-48 hours after conversion
  window close (first window) or 24-144 hours (second/third windows).
- **No user-level identifiers** -- postbacks contain aggregate source
  identifiers and conversion values, not device or user IDs.
- **Hierarchical source identifiers** -- 2, 3, or 4-digit source IDs where the
  number of digits returned depends on the crowd anonymity tier.

In migration and interoperability reviews, explicitly state that the system
evaluates AdAttributionKit and SKAdNetwork impressions together, only one
impression wins per conversion, click-through beats view-through, and recency
breaks ties within click-through impressions before falling back to the most
recent view-through impression.

## Publisher App Setup

The rest: https://github.com/dpearson2699/swift-ios-skills/blob/HEAD/skills/adattributionkit/SKILL.md