What makes Conversion Signal Qa notable?

1.1K downloads. Trust evidence available

How should Conversion Signal Qa be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

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 dedu...

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

19.0.0

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 19.0.0release · observed Jul 24, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17e1tg8pjra8dn1dvtq21sahx83hrxj:conversion-signal-qa

Install using `clawhub skill install s17e1tg8pjra8dn1dvtq21sahx83hrxj:conversion-signal-qa` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/aaron-he-zhu/conversion-signal-qa before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-aaron-he-zhu-conversion-signal-qa/snapshot"

Documentation

CLAWHUB

110,946 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: conversion-signal-qa
slug: aaron-conversion-signal-qa
displayName: "Conversion Signal QA · 付费广告转化追踪QA"
summary: "付费广告转化追踪QA/UTM规范/跨平台去重"
description: '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'
version: "19.0.0"
license: Apache-2.0
compatibility: "Claude Code and compatible agent-skill hosts"
homepage: "https://github.com/aaron-he-zhu/aaron-marketing-skills"
when_to_use: "Use before launching or scaling paid campaigns, when the measurement plumbing needs verifying or fixing: conversion events firing, UTM consistency, cross-platform dedup, attribution-window alignment, and offline/iOS-ATT modeled-gap flags. Run it to BUILD the signal pre-flight; run ad-account-auditor to SCORE whether R1/R2 pass."
argument-hint: "<site/account topic> [platforms] [GA4 conversions + traffic-acquisition export]"
metadata: {"author": "aaron-he-zhu", "version": "19.0.0", "discipline": "ad", "phase": "activate", "geo-relevance": "low", "hermes": {"tags": ["marketing", "ad", "activate"], "category": "ad"}, "openclaw": {"emoji": "🎯", "homepage": "https://github.com/aaron-he-zhu/aaron-marketing-skills"}}
---

# 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 me a pre-launch tracking checklist I can run myself.
```

```
My Meta and Google numbers don't match my GA4 orders — find the dedup, attribu

_meta.json

{
  "ownerId": "kn73qjxwmbna25qq8q051epqt980sys5",
  "slug": "conversion-signal-qa",
  "version": "19.0.0",
  "publishedAt": 1784903280419
}

references/preflight-checklist.md

# Tracking Pre-Flight Checklist

Run before launching or scaling paid campaigns. Mark each item **pass / fail / needs-input** from the user's own GA4 exports and one manual test conversion. Never pass-by-default — a missing export makes the item **needs-input**, not pass. This checklist BUILDS/FIXES the signal; it does not score the ROAS `R1`/`R2` vetoes (that is [ad-account-auditor](../../ad-account-auditor/SKILL.md)).

## 1. Conversion-event firing

| Item | Pass when | Fail / needs-input |
|------|-----------|--------------------|
| Test conversion recorded | A manually-run test conversion appears in the GA4 Conversions export with correct event name | No test conversion run = **needs-input**; run but absent = **fail** |
| One canonical event per action | Each money action (purchase/lead/signup) maps to exactly one conversion event | Multiple events for the same action, or one event reused for several actions |
| Value + currency present | Purchase events carry a numeric value and a single currency | Missing value, mixed currencies, or hard-coded test value in production |
| Dedup parameter present | Each conversion carries a stable order/transaction ID | No ID to dedup on across platforms |

## 2. UTM hygiene

| Item | Pass when | Fail / needs-input |
|------|-----------|--------------------|
| All paid links tagged | Every paid landing URL carries source/medium/campaign | Untagged links land as `(direct)` or `referral` in Traffic-acquisition |
| Consistent casing/values | source/medium values match the spec exactly (lowercase, no synonyms) | `Google` vs `google`, `cpc` vs `ppc`, free-text campaign names |
| Auto-tagging vs manual not colliding | Platform auto-tagging (e.g. gclid) and manual UTMs don't overwrite each other | Both present and fighting, splitting one source into two rows |
| No PII in UTMs | UTM values contain no emails, names, or order data | PII embedded in campaign/content params |

## 3. Cross-platform dedup

> Pre-flight **gates** only — confirm the rule and routing *exist*. The actual order-ID matching, de-dup, and inflation math are the standing job of [attribution-reconciler](../../../scale/attribution-reconciler/SKILL.md).

| Item | Pass when | Fail / needs-input |
|------|-----------|--------------------|
| Single source of truth named | GA4/ecommerce order IDs are the truth set, not each platform's self-reported count | Platform counts trusted directly |
| Dedup method defined | A method to reconcile platform claims against the truth set is stated, owned by attribution-reconciler | No plan for resolving Meta/Google overlap |
| Overlap flagged & routed | Any obvious Meta+Google double-count is flagged and routed to attribution-reconciler | Overlap ignored (or quantified here instead of routed) |

## 4. Attribution-window alignment

| Item | Pass when | Fail / needs-input |
|------|-----------|--------------------|
| Windows stated & aligned | Each platform's click/view window is stated and a common comparison basis is

references/utm-event-spec.md

# UTM / Event Spec Builder

Fill these two templates for the account, then save them with the pre-flight report. The spec is the contract every paid link and conversion event must follow so the GA4 Traffic-acquisition and Conversions exports stay clean and dedupable.

## UTM naming convention

One canonical value per field. Lowercase, no spaces, no synonyms, no PII.

| Field | Rule | Example |
|-------|------|---------|
| `utm_source` | the platform, one fixed token | `google`, `meta`, `linkedin` |
| `utm_medium` | the paid channel type, fixed vocabulary | `cpc`, `paid_social`, `display` |
| `utm_campaign` | `{goal}_{audience}_{yyyymm}` | `dr_prospecting_202606` |
| `utm_content` | ad/creative variant id | `video_a`, `carousel_b` |
| `utm_term` | keyword/theme (search only) | `running_shoes` |

Rules:
- Pick **one** value per source/medium and never vary case (`google`/`cpc`, never `Google`/`PPC`).
- Don't let platform auto-tagging (gclid/fbclid) and manual UTMs overwrite each other — choose one scheme per platform and document it.
- Never embed emails, names, or order IDs in any UTM field.

## Conversion-event spec

One row per money action. Each action maps to exactly one event with a stable dedup ID.

| Money action | Event name | Value param | Currency | Dedup ID | Fires on |
|--------------|-----------|-------------|----------|----------|----------|
| Purchase | `purchase` | order_total | single currency | `transaction_id` | order confirmation |
| Lead | `generate_lead` | lead_value (or none) | — | `lead_id` | form thank-you |
| Signup | `sign_up` | — | — | `user_id` | account-created |

Rules:
- The **dedup ID** is the single source of truth for cross-platform reconciliation — GA4/ecommerce order IDs win over any platform's self-reported count.
- State the **attribution window** chosen per platform and normalize all exports to one window, currency, and timezone before matching.
- Confirm one **manual test conversion** flows end-to-end into the GA4 Conversions export before launch.

skill-card.md

## Description:

Builds and fixes paid-ad conversion measurement checks, including event firing, UTM hygiene, cross-platform deduplication gates, attribution-window alignment, and offline or iOS-ATT modeled-gap flags.

This skill is ready for commercial/non-commercial use.

## Publisher:

[aaron-he-zhu](https://clawhub.ai/user/aaron-he-zhu)

### License/Terms of Use:

MIT-0

## Use Case:

Marketing operators, analysts, and developers use this skill before launching or scaling paid campaigns to verify conversion events, UTMs, deduplication gates, attribution windows, and modeled-data gaps. It produces a launch-readiness report plus a reusable UTM and conversion-event specification.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: User-provided analytics or ecommerce exports may contain sensitive campaign, order, or personal data.

Mitigation: Provide only the fields needed for the QA task, remove PII from UTMs and pasted exports, and treat exported report text as evidence rather than instructions.

Risk: Saved pre-flight reports can persist account-specific measurement details.

Mitigation: Save reports and UTM/event specifications only after explicit user approval and review the content before saving.

Risk: Optional API connectors can expand access beyond manual exports.

Mitigation: Use connectors only deliberately; manual GA4, ecommerce, and traffic-acquisition exports are sufficient for the documented workflow.

## Reference(s):

- [Tracking Pre-Flight Checklist](artifact/references/preflight-checklist.md)
- [UTM / Event Spec Builder](artifact/references/utm-event-spec.md)
- [Project homepage](https://github.com/aaron-he-zhu/aaron-marketing-skills)
- [ClawHub skill page](https://clawhub.ai/aaron-he-zhu/skills/conversion-signal-qa)

## Skill Output:

**Output Type(s):** [text, markdown, configuration, guidance]

**Output Format:** [Markdown report with checklist results, UTM naming rules, conversion-event specification tables, and a handoff summary]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May write a user-facing pre-flight report and reusable UTM/event specification to memory only after explicit user approval.]

## Skill Version(s):

19.0.0 (source: frontmatter and server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

Github ReposUpdated 2d agoRank 70

AionUi

Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!

MCPOPENCLAW

Github ReposUpdated 6mo agoRank 70

activepieces

AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

OPENCLAW

Github ReposUpdated 6mo agoRank 70

cherry-studio

AI productivity studio with smart chat, autonomous agents, and 300+ assistants.