attribution-setup
by EronredThe attribution-setup skill helps you design, validate, and debug app install attribution for iOS and Android. It covers SKAdNetwork, AdAttributionKit, Google Play Install Referrer, deferred deep links, conversion values, postbacks, and MMP setup for AppsFlyer, Adjust, Singular, Branch, or Kochava. Use this attribution-setup guide when you need practical setup, troubleshooting, or measurement tradeoffs for Project Management and mobile growth.
This skill scores 78/100, which means it is a solid directory candidate for users working on app install attribution. The repo gives an agent a clear trigger, a defined initial assessment flow, and substantial domain-specific guidance, so users can expect better-than-generic help for attribution setup and debugging. It is not fully turnkey because there are no support files or install command, but it is clear enough to justify listing.
- Strong triggerability: the description names concrete attribution topics and tools (SKAdNetwork/SKAN, AdAttributionKit, Install Referrer, major MMPs, deep links, ATT).
- Operationally useful workflow: the skill tells the agent to check for app-marketing-context.md and ask key setup questions about platform, MMP, channels, and the problem.
- Good repository substance: valid frontmatter, a long skill body, and multiple workflow/constraint sections suggest real guidance rather than a placeholder.
- No support files or install command, so adoption will rely on the SKILL.md text alone and may require manual interpretation.
- The repository evidence shows no scripts/references/resources, so users should expect guidance content rather than automated checks or sourced implementation assets.
Overview of attribution-setup skill
The attribution-setup skill helps you design, validate, and debug app install attribution when you need a measurement setup that survives modern iOS privacy limits. It is most useful for teams working on the attribution-setup for Project Management, mobile growth, or analytics who need to know which campaigns drove installs and revenue, not just which ads got clicks.
This attribution-setup skill is a good fit when the work involves SKAdNetwork, AdAttributionKit, Google Play Install Referrer, deferred deep links, conversion values, postback timing, ATT, or MMP configuration in AppsFlyer, Adjust, Singular, Branch, or Kochava. It is less about generic media planning and more about building a measurement stack that can actually answer “what worked?” across iOS and Android.
What this skill is for
Use attribution-setup when you need to:
- set up first-time install attribution
- investigate missing or mismatched conversion data
- plan an iOS measurement approach under ATT and SKAN
- align MMP, deep link, and analytics event logic
- choose what to measure when full user-level tracking is not available
What makes it different
Unlike a broad growth prompt, attribution-setup focuses on the operational details that block adoption: platform differences, postback limits, privacy thresholds, and schema decisions. That means it is most valuable when you already know the business question, but need help translating it into an implementation plan or debugging path.
Best-fit users and misfit cases
Best fit: app marketers, product managers, tracking analysts, and engineers who need an attribution-setup guide that is practical and platform-aware. Not the best fit if you only want ad strategy, keyword bidding, or generic analytics dashboards without install attribution complexity.
How to Use attribution-setup skill
Install and activate the skill
Use the attribution-setup install path provided by your skill runner, then open the skill files before asking for output. If your environment supports it, install with:
npx skills add Eronred/aso-skills --skill attribution-setup
The main entry point is skills/attribution-setup/SKILL.md. This repo currently appears to be single-file, so start there first and treat it as the source of truth.
Give the skill the right input
The attribution-setup usage works best when you provide four things up front:
- platform: iOS, Android, or both
- stack: MMP, MMP name, or “none”
- goal: new setup, discrepancy fix, migration, or schema design
- constraints: ATT status, SKAN version, deep link needs, privacy limits, channel mix
Strong prompt example:
“Use attribution-setup to plan an iOS install attribution stack for a subscription app. We use AppsFlyer, run Meta and Apple Search Ads, and need a SKAN 4 conversion value schema that can still support trial-start optimization. We currently lose some deferred deep link data. Give me the setup steps, key risks, and what to verify in the MMP dashboard.”
Suggested workflow
- Read
SKILL.mdfor the attribution model and assessment order. - Gather platform, channel, and MMP details before you ask for recommendations.
- Ask for a plan, not just an explanation: setup, validation, and failure points.
- Re-run with actual symptoms if the first answer is too generic.
Read these sections first
For this skill, the most decision-useful parts of the repo are the assessment flow, the iOS attribution reality section, SKAdNetwork guidance, and conversion value schema design. If you only skim one file, skim SKILL.md and use the headings as your prompt outline.
attribution-setup skill FAQ
Is attribution-setup only for iOS?
No. The attribution-setup skill covers both iOS and Android, but it is especially useful for iOS because ATT, SKAN, and AdAttributionKit make attribution setup more fragile. On Android, it is most helpful for Install Referrer, deep links, and MMP coordination.
Do I need an MMP to use this skill?
No, but having one changes the advice. If you use AppsFlyer, Adjust, Singular, Branch, or Kochava, include that in your prompt because setup and debugging depend on the vendor’s event model and dashboard behavior.
How is this different from a normal prompt?
A normal prompt may explain attribution concepts. The attribution-setup skill is better for implementation decisions: what to configure, what to verify, what will break, and which measurement tradeoffs matter under privacy constraints.
Is it beginner-friendly?
Yes, if you can answer basic setup questions. The skill is most effective when you can name the app, platform, channels, and current tracking stack. Without that, the output will be more generic and less actionable.
How to Improve attribution-setup skill
Provide the minimum debugging context
The fastest way to improve attribution-setup output is to include the exact symptom and where it appears. For example: “SKAN postbacks exist but revenue is missing in BI,” or “deferred deep links fail only on first open.” That is much better than “attribution isn’t working.”
State the measurement goal explicitly
Say whether you care most about install counts, trial starts, purchase revenue, re-engagement, or campaign-level optimization. The best attribution-setup guidance changes depending on whether the goal is reporting accuracy or ad network optimization.
Share the schema and channel constraints
If you already have a conversion value schema, include it. If not, say what events you can reliably send within the SKAN window, which channels you buy, and whether ATT opt-in is expected to be high or low. Those details materially affect the recommended setup.
Iterate with real output and errors
After the first answer, feed back dashboard mismatches, postback gaps, or event timing issues. The skill becomes more useful when you ask it to refine one layer at a time: setup, validation, then optimization.