Token导航 LogoToken导航TokenDH.com
待分类只读github未标认证来源可访问许可证需确认审计通过

ecom-analytics经济分析

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

总安装

509

周安装

21

GitHub Stars

124

下载量

166
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ecom-analytics(经济分析)
来源仓库:https://github.com/asgard-ai-platform/skills
仓库路径:skills/ecom-analytics
安装命令:
npx skills add https://github.com/asgard-ai-platform/skills --skill ecom-analytics
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/asgard-ai-platform/skills --skill ecom-analytics

简介

电商数据分析框架,覆盖 GA4 追踪设置、漏斗分析与关键指标解读。

  • 适用于流量、转化与收入维度的店铺性能评估,支持问题根因定位。
  • 遵循“按漏斗阶段诊断而非症状”原则,分解 Traffic × Conversion Rate × AOV = Revenue。
  • 需结合真实交易数据与平台接口提取信息,避免依赖模拟或假设性数据源。
  • ecom-analytics 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

E-Commerce Analytics

Overview

E-commerce analytics measures online store performance across traffic, conversion, and revenue dimensions. This skill covers GA4 e-commerce tracking setup, funnel analysis, and key metric interpretation to diagnose why a store is or isn't performing.

Framework

IRON LAW: Diagnose by Funnel Stage, Not by Symptom

"Sales are down" is a symptom, not a diagnosis. Decompose into funnel stages:
Traffic × Conversion Rate × AOV = Revenue

If revenue drops 20%, is it because traffic dropped (acquisition problem),
conversion dropped (UX/pricing problem), or AOV dropped (product mix problem)?
Each requires a completely different fix.

E-Commerce Funnel & Key Metrics

StageMetricsWhat It Tells You
AcquisitionSessions, Users, Traffic sources, CPC, CACAre you attracting enough visitors? From where? At what cost?
EngagementPages/session, Time on site, Bounce rate, Product viewsAre visitors interested? Are they browsing?
ConversionAdd-to-cart rate, Checkout initiation rate, Purchase conversion rateWhere in the funnel are they dropping off?
RevenueRevenue, AOV, Items per order, Revenue per sessionHow much are they spending? Is the mix healthy?
RetentionRepeat purchase rate, Purchase frequency, Customer lifetime valueAre they coming back?

GA4 E-Commerce Events

EventTriggerKey Parameters
view_itemProduct page viewitem_id, item_name, price, category
add_to_cartAdd to cart clickitems array, value, currency
begin_checkoutCheckout starteditems, value, coupon
add_payment_infoPayment enteredpayment_type
purchaseOrder completedtransaction_id, value, tax, shipping, items

Diagnosis Framework

Phase 1: Traffic Check

  • Is total traffic up/down/flat vs prior period?
  • Which channels changed? (organic, paid, social, direct, referral)
  • Is traffic quality declining? (bounce rate, pages/session by source)

Phase 2: Conversion Check

  • Where is the biggest funnel drop-off?
  • Compare: View → Add to cart → Checkout → Purchase
  • Industry benchmark conversion rates: 1-3% overall, 5-10% add-to-cart

Phase 3: Revenue Check

  • AOV trend: rising (upselling working) or falling (discounting eroding value)?
  • Product mix: is revenue shifting to lower-margin products?
  • Revenue per session: the master metric (traffic quality × conversion × AOV)

Phase 4: Retention Check

  • Repeat purchase rate by cohort
  • Time between first and second purchase
  • LTV trend by acquisition channel

Output Format

# E-Commerce Performance Report: {Store}

## Summary Dashboard
| Metric | Current | Prior Period | Change | Status |
|--------|---------|-------------|--------|--------|
| Sessions | {N} | {N} | {%} | 🟢/🟡/🔴 |
| Conversion Rate | {%} | {%} | {%} | 🟢/🟡/🔴 |
| AOV | ${X} | ${X} | {%} | 🟢/🟡/🔴 |
| Revenue | ${X} | ${X} | {%} | 🟢/🟡/🔴 |

## Funnel Analysis
| Stage | Volume | Rate | Drop-off | Benchmark |
|-------|--------|------|----------|-----------|
| Sessions | {N} | 100% | — | — |
| Product Views | {N} | {%} | {%} | — |
| Add to Cart | {N} | {%} | {%} | 5-10% |
| Checkout | {N} | {%} | {%} | 40-60% of ATC |
| Purchase | {N} | {%} | {%} | 1-3% overall |

## Diagnosis
- Primary issue: {funnel stage} — {specific problem}
- Root cause: {analysis}

## Recommendations
1. {action targeting the diagnosed stage}

Gotchas

  • Conversion rate is meaningless without traffic quality context: A 5% conversion rate from email (high-intent) and 0.5% from display ads (low-intent) are both normal. Don't compare across channels.
  • GA4 sessions ≠ Universal Analytics sessions: GA4 uses event-based model. Session timeout and attribution rules differ. Expect 5-15% discrepancy during migration.
  • Mobile conversion is always lower: Mobile: 1-2%, Desktop: 3-5% is typical. Don't mix them in one number — analyze separately.
  • Seasonality matters: Compare same period YoY, not just MoM. E-commerce has strong seasonal patterns (11.11, Christmas, Chinese New Year).
  • Revenue ≠ profit: A 20% revenue increase from aggressive discounting may reduce profit. Track margin alongside revenue.

References

  • For GA4 setup guide, see references/ga4-setup.md
  • For e-commerce benchmark data by industry, see references/ecom-benchmarks.md

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.41%
按下载量换算57

Claude

31.23%
按下载量换算52

Cursor

20.28%
按下载量换算34

Gemini CLI

9.53%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills