Agent skill · Testing & QA

conversion-signal-qa

Use when the user asks to "QA my conversion tracking before launch", "check my UTMs / pixel / event firing", "set up a tracking pre-flight", or "set the dedup rule so Meta and Google stop double-counting"; builds and fixes the measurement plumbing — conversion-event firing, UTM hygiene, cross-platform dedup rules, attribution-window alignment, and offline/iOS-ATT modeled-gap flags — as a pre-flight checklist plus a UTM/event-spec builder. Not for scoring R1/R2 — that is a scored veto in ad-account-auditor; not for account structure — use campaign-architect. 付费广告转化追踪QA/UTM规范/跨平台去重

aaron-he-zhugithub.com/aaron-he-zhuGitHub ↗
claude-codeApache-2.0
Install
npx skills add aaron-he-zhu/aaron-marketing-skills --skill conversion-signal-qa --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 9 KB
Bundled scripts: none
Version: 19.1.0
Requires: Claude Code and compatible agent-skill hosts
Path: ad/activate/conversion-signal-qa/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,508
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Conversion Signal QA Pre-flight QA of the measurement plumbing behind paid ads — conversion-event firing, UTM hygiene, cross-platform dedup rules, attribution-window alignment, and offline/iOS-ATT modeled-gap flags — delivered as a tracking pre-flight checklist plus a UTM/event-spec builder. **Scope line: this skill BUILDS and FIXES the signal pre-flight so the data is trustworthy; it does NOT score the ROAS `R1`/`R2` vetoes — [ad-account-auditor](../ad-account-auditor/SKILL.md) judges those as scored red lines.** It is the `R1`/`R2` prerequisite, not the verdict. It is also **not** the standing monthly de-dup / incrementality reconciliation — that is [attribution-reconciler](../../scale/attribution-reconciler/SKILL.md). Here you only **gate** that a dedup rule and aligned attribution windows *exist* pre-launch; the actual order-ID matching, double-count quantification, and incrementality read happen in attribution-reconciler. ## Quick Start ``` QA my conversion tracking before I scale. Platforms: Google + Meta. Here is my GA4 Conversions export and Traffic-acquisition (source/medium) export: [paste/path]. ``` ``` Build me a UTM scheme and event spec for this campaign, then give

What's inside
Steps it walks through
  1. Quick Start
  2. Skill Contract
  3. Handoff Summary
  4. Data Sources
  5. Instructions
  6. Save Results
  7. Reference Materials
  8. Next Best Skill
Ships with 2 files
  • references/preflight-checklist.md
  • references/utm-event-spec.md
More from aaron-marketing-skills
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About this skill
What does the conversion-signal-qa skill do?

Use when the user asks to "QA my conversion tracking before launch", "check my UTMs / pixel / event firing", "set up a tracking pre-flight", or "set the dedup rule so Meta and Google stop double-counting"; builds and fixes the measurement plumbing — conversion-event firing, UTM hygiene, cross-platform dedup rules, attribution-window alignment, and offline/iOS-ATT modeled-gap flags — as a pre-flight checklist plus a UTM/event-spec builder. Not for scoring R1/R2 — that is a scored veto in ad-account-auditor; not for account structure — use campaign-architect. 付费广告转化追踪QA/UTM规范/跨平台去重

How do I install it?

Run `npx skills add aaron-he-zhu/aaron-marketing-skills --skill conversion-signal-qa --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From aaron-he-zhu/aaron-marketing-skills, a repository with 2,508 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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