What makes Attribution Reconciler notable?

1.1K downloads. Trust evidence available

How should Attribution Reconciler 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

Attribution Reconciler

Use when platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (m... Skill: Attribution Reconciler Owner: aaron-he-zhu Summary: Use when platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (m... Tags: latest:19.0.0 Version history: v19.0.0 | 2026-07-24T14:14:40.979Z | auto Attribution Reconciler 19.0.0 - Version bump to 19.0.0 with updated metadata. - Added new file: distribution-manifest.jso

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:attribution-reconciler

Setup complexity is classified as HIGH. You must provision dedicated cloud infrastructure or an isolated VM. Do not run this directly on your local workstation.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-aaron-he-zhu-attribution-reconciler/snapshot"

Documentation

CLAWHUB

88,339 characters of source documentation, loaded on request.

Extracted files

4 files captured from the source.

SKILL.md

---
name: attribution-reconciler
slug: aaron-attribution-reconciler
displayName: "Attribution Reconciler · 付费广告归因对账"
summary: "付费广告归因对账/去重/增量"
description: 'Use when platform-reported conversions disagree with GA4/ecommerce, when you suspect Meta and Google are double-counting the same sales, or for a standing (monthly) reconciliation workbook that de-dups stacked credit against an order-ID truth set, normalizes attribution windows and currency, compares attribution models, and reads incrementality from a geo/holdout test. Not for the point-in-time R2 veto or RQS gate — use ad-account-auditor; not for the ROI/ROAS ratio math itself — use roi-calculator; not for organic dark-social share attribution or GA4 direct-traffic decomposition — use dark-social-attributor. 付费广告归因对账/去重/增量'
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 when running a standing reconciliation of platform-reported conversions against the GA4/ecommerce order-ID truth set: de-dup stacked credit across Meta + Google, normalize differing attribution windows and currency, compare attribution models side by side, and read incrementality where a geo/holdout test exists. Activate when the user has each platform's conversion export plus an order-ID export and wants to know which conversions are real and not double-counted."
argument-hint: "<GA4/ecommerce order-ID export> [platform conversion exports] [goal: DR|prospecting]"
metadata: {"author": "aaron-he-zhu", "version": "19.0.0", "discipline": "ad", "phase": "scale", "geo-relevance": "low", "hermes": {"tags": ["marketing", "ad", "scale"], "category": "ad"}, "openclaw": {"emoji": "🎯", "homepage": "https://github.com/aaron-he-zhu/aaron-marketing-skills"}}
---

# Attribution Reconciler

> Based on the ROAS dimension **R** (attribution integrity) in the [ROAS Benchmark](../../../references/roas-benchmark.md). This is the **standing de-dup / incrementality workbook**: it reconciles platform-reported conversions against the GA4/ecommerce order-ID truth set on a recurring cadence. It delegates **all** ratio/ROAS math to [roi-calculator](../../../influencer/report/roi-calculator/SKILL.md) and does **not** re-run the R2 veto — [ad-account-auditor](../../activate/ad-account-auditor/SKILL.md) judges R2 once, point-in-time. This workbook just keeps the truth set clean between audits. Upstream, [conversion-signal-qa](../../activate/conversion-signal-qa/SKILL.md) is the **pre-launch** instrumentation pass that makes the signal trustworthy and only *gates* that a dedup rule exists; this skill is the recurring reconciliation that runs **on** that signal — match, de-dup, quantify, read incrementality.

The single rule: the truth set is the **order IDs** from GA4/ecommerce, **never** any platform's reported-conversion count. This workbook reconciles **paid** channels only — decomposing GA4 direct traffic and estimat

_meta.json

{
  "ownerId": "kn73qjxwmbna25qq8q051epqt980sys5",
  "slug": "attribution-reconciler",
  "version": "19.0.0",
  "publishedAt": 1784902480979
}

skill-card.md

## Description:

Helps reconcile paid-ad conversion exports against GA4/ecommerce order IDs by normalizing windows and currency, de-duplicating stacked platform credit, comparing attribution models, and reading incrementality when a holdout exists.

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 and growth teams use this skill to reconcile paid-channel conversion exports against an order-ID truth set, identify double-counted platform claims, normalize attribution windows and currency, compare credit-allocation models, and summarize incrementality when holdout data is available.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: The skill may process order IDs, conversion exports, spend data, and attribution results.

Mitigation: Provide only exports appropriate for reconciliation and avoid including unnecessary sensitive fields.

Risk: Reconciliation summaries may be persisted for future sessions if saving is approved.

Mitigation: Approve the save step only when the summarized results should be retained in memory.

Risk: User-provided exports can contain misleading text or malformed attribution claims.

Mitigation: Treat export contents as data to reconcile against the order-ID truth set, not as instructions.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/aaron-he-zhu/skills/attribution-reconciler)
- [Project homepage](https://github.com/aaron-he-zhu/aaron-marketing-skills)

## Skill Output:

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

**Output Format:** [Markdown workbook with reconciliation tables and a handoff summary]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [May write a Markdown workbook and update memory only after the user approves saving results.]

## Skill Version(s):

19.0.0 (source: SKILL.md 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.

distribution-manifest.json

{
  "capabilities": [
    "inline-delivery",
    "canonical-state-read"
  ],
  "capability_ceiling": "lite",
  "catalog_sha256": "6f0256cf52710f2916ecebaea0f3110c9313099ec4a69a11cac72ba9b2f3b940",
  "files": [
    {
      "bytes": 11331,
      "mode": "0644",
      "path": "SKILL.md",
      "sha256": "04ffe883c21ecc3150a8611dbcd5ccbd93d3ec93f76eae956567c008ace612f5"
    }
  ],
  "files_sha256": "dd6f9e46b8e2b66315978671f422534587b7cc8619a29469c601f845f85024b7",
  "hash_algorithm": "sha256",
  "kind": "standalone-skill",
  "manifest_excludes": [
    "distribution-manifest.json"
  ],
  "manifest_path": "distribution-manifest.json",
  "package_ceiling": {
    "max_bytes": 1000000,
    "max_files": 64
  },
  "profile": "lite",
  "profile_definition_sha256": "4598e1f7bba667ef928ea2a60a6252ad9348086e9eecab29437db442df2a568e",
  "schema_version": "1.1",
  "source": {
    "commit": "f552620c278afddcb25d09637a0cfcc1ce48faf4",
    "repository": "aaron-he-zhu/aaron-marketing-skills"
  }
}

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.