attribution-reconciler
Reconcile Paid Conversion Attribution
Platform reports can overstate conversions when several channels claim the same order. This skill matches conversion exports to an order-ID truth set and produces a normalized reconciliation view.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "attribution-reconciler" from https://skillstore.io/skills/aaron-he-zhu-attribution-reconciler.md and its manifest at https://skillstore.io/api/skills/aaron-he-zhu-attribution-reconciler/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "attribution-reconciler". Meta, Google, and GA4 order exports for one month.
Expected outcome:
- A match table for every platform claim.
- De-duplicated order counts by platform.
- A list of unmatched claims that need investigation.
Using "attribution-reconciler". A test and control regional order export with spend data.
Expected outcome:
- A stated estimate of measured lift or an explanation of missing inputs.
- A comparison between holdout evidence and attributed conversions.
- A note that ROAS and CPA require a separate calculation.
Security Audit
Low RiskAll 35 static findings are false positives caused by Markdown code formatting, relative documentation links, or a public homepage URL; no command execution, network request, path traversal, or system reconnaissance is instructed. The skill handles user-provided marketing exports and can persist order-level reconciliation results after confirmation, so data retention controls should be documented.
Confirmed security concerns (1)
Risk Factors
⚙️ External commands (17)
🌐 Network access (2)
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<iframe src="https://skillstore.io/embed/skills/aaron-he-zhu-attribution-reconciler.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
aaron-he-zhu. (2026). attribution-reconciler security audit report (audit version 7) [Author version 19.0.0]. Skillstore. https://skillstore.io/skills/aaron-he-zhu-attribution-reconciler/audits/7BibTeX citation
@techreport{aaron-he-zhu-aaron-he-zhu-attribution-reconciler-2026,
author = {aaron-he-zhu},
title = {attribution-reconciler security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/aaron-he-zhu-attribution-reconciler/audits/7},
note = {Author version 19.0.0}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "attribution-reconciler security audit report (audit version 7)"
version: "19.0.0"
type: report
authors:
- name: "aaron-he-zhu"
date-released: "2026-07-26"
url: "https://skillstore.io/skills/aaron-he-zhu-attribution-reconciler/audits/7"
identifiers:
- type: other
value: "skillstore:aaron-he-zhu-attribution-reconciler:audit:7"
description: "Skillstore immutable audit report identifier"
Skillstore Score
Why this score Evidence Confidence: MediumWhat You Can Build
Audit overlapping platform claims
Compare Meta and Google conversion exports with a GA4 order export to identify sales claimed by multiple platforms.
Build a monthly reconciliation
Create a recurring workbook that tracks matched, double-counted, and unmatched conversions across paid channels.
Interpret a holdout test
Compare test and control order exports with platform spend to distinguish measured lift from last-click credit.
Try These Prompts
Reconcile these Meta and Google conversion exports against this GA4 order-ID export for May. Show matched, double-counted, and unmatched orders.
Build a monthly attribution reconciliation. Normalize Meta 7-day-click and Google 30-day windows to the order dates, then state the currency basis used.
Using this reconciled order set, compare last-click and linear attribution by platform. Keep the total number of real orders unchanged.
Use these test-region and control-region order exports and spend data to assess incrementality. Compare measured lift with last-click claims and mark unsupported conclusions.
Best Practices
- Provide complete order IDs, timestamps, values, currencies, and attribution windows for every export.
- Use the ecommerce or GA4 order export as the truth set, not platform-reported totals.
- Review unmatched claims before using reconciled counts in budget decisions.
Avoid
- Do not add platform conversion totals together without checking overlapping order IDs.
- Do not compare counts from different attribution windows or currencies without normalization.
- Do not claim incrementality when no valid geo or holdout evidence exists.
Frequently Asked Questions
What data do I need?
Can it reconcile Meta and Google data?
What is the truth set?
Does it calculate ROAS or CPA?
Can it measure incrementality?
Will it save my results?
Developer Details
Author
aaron-he-zhuLicense
Apache-2.0
Author version
v19.0.0
Skillstore revision
r2
Repository
https://github.com/aaron-he-zhu/aaron-marketing-skills/tree/main/ad/scale/attribution-reconcilerRef
adcb3549b15782055d0beb6d29f113d20de08f92
Maintenance freshness
7/28/2026
Usage
1 downloads · 1 views
File structure
📄 SKILL.md