安全扫描（ClawHub）

• VirusTotal ：良性
• OpenClaw ：良性

OpenClaw 评估

The skill is an instruction-only Shopify ads advisor whose requested inputs and runtime instructions are consistent with its stated purpose and it does not ask for unrelated credentials or install code.

安装（复制给龙虾 AI）

将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Shopify Ads Helper」。简介：Optimize Shopify-specific paid growth workflows for Meta (Facebook/Instagram), …。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/danyangliu-sandwichlab/shopify-ads-helper/SKILL.md
（来源：yingzhi8.cn 技能库）

SKILL.md

打开原始 SKILL.md（GitHub raw）

---
name: shopify-ads-helper
description: Optimize Shopify-specific paid growth workflows for Meta (Facebook/Instagram), Google Ads, TikTok Ads, and YouTube Ads with Shopify event integrity, ROAS diagnostics, scale planning, and funnel optimization.
---

# Shopify Ads Helper

## Purpose
Core mission:
- Verify Shopify pixel and attribution status for conversion optimization readiness.
- Diagnose account structure and creative performance affecting ROAS.
- Recommend scaling route and budget increments.
- Improve landing page and conversion funnel outcomes.

## When To Trigger
Use this skill when the user asks for:
- Shopify ads troubleshooting
- OCPX readiness in Shopify stack
- ROAS fluctuation diagnosis in store campaigns
- checkout and funnel optimization

High-signal keywords:
- shopifyads, shop, ecommerce, checkout
- pixel, attribution, tracking, campaign
- roas, cpa, budget, scale, funnel

## Input Contract
Required:
- shopify_store_url
- tracking_stack_summary
- channel_performance_snapshot
- checkout_metrics

Optional:
- product_margin_data
- collection_level_performance
- creative_breakdown
- shipping_policy_context

## Output Contract
1. Shopify Tracking Health Summary
2. Channel and Structure Diagnosis
3. ROAS Volatility Interpretation
4. Scale Path with Budget Gates
5. Checkout and Funnel Optimization Plan

## Workflow
1. Validate Shopify event mapping consistency.
2. Confirm attribution alignment across channels.
3. Audit campaign architecture per product/collection.
4. Isolate ROAS drivers by audience/creative/offer.
5. Propose staged budget lift and funnel fixes.

## Decision Rules
- If checkout completion is weak, prioritize on-site fixes over spend expansion.
- If collection-level margins vary, apply differential bid and budget controls.
- If attribution mismatch is high, rely on blended and platform views in parallel.
- If shipping/offer changes happened recently, separate pre/post effects before action.

## Platform Notes
Primary scope:
- Shopify Ads ecosystem with Meta (Facebook/Instagram), Google Ads, TikTok Ads, YouTube Ads

Platform behavior guidance:
- Keep Shopify conversion events normalized before cross-platform optimization.
- Pair channel decisions with collection-level economics when available.

## Constraints And Guardrails
- Do not optimize on ROAS alone when margin is uneven across SKUs.
- Flag data-lag effects for short lookback windows.
- Keep budget changes incremental under attribution uncertainty.

## Failure Handling And Escalation
- If event schema is broken, return patch checklist and freeze scale actions.
- If Shopify app conflicts affect tracking, escalate with app inventory and event log.
- If billing or policy lock appears, route to platform owner with urgency level.

## Code Examples
### Shopify Event Mapping Check

    events:
      product_view: ViewContent
      add_to_cart: AddToCart
      checkout_start: InitiateCheckout
      order_paid: Purchase
    status: pass_with_warnings

### Budget Lift Gate

    if blended_roas >= 2.8 and checkout_cvr >= 2.2:
      increase_budget_pct: 15
    else:
      hold_budget: true

## Examples
### Example 1: Shopify ROAS drift
Input:
- ROAS unstable after theme update

Output focus:
- tracking validation
- cause isolation
- corrective actions

### Example 2: Collection scaling
Input:
- One collection outperforming others

Output focus:
- collection-level budget logic
- structure recommendations
- risk guardrails

### Example 3: Checkout drop
Input:
- Add-to-cart steady, purchase down

Output focus:
- checkout funnel fixes
- retargeting adjustment
- measurement checks

## Quality Checklist
- [ ] Required sections are complete and non-empty
- [ ] Trigger keywords include at least 3 registry terms
- [ ] Input and output contracts are operationally testable
- [ ] Workflow and decision rules are capability-specific
- [ ] Platform references are explicit and concrete
- [ ] At least 3 practical examples are included