AgriciDaniel/claude-ads✦ 精选0°

ads-attribution

仓库创建 2026年2月11日最近提交 13 天前SkillHot 收录 4 小时前

⬈ GitHub 仓库 ⬈ SKILL.md 原文件 ⬇ Raw 原始文件

▸ 精选理由

帮助团队厘清计数口径与数据差异，是复杂归因问题的实用工具。

▸ 风险提示

需接入多方数据源与身份标识，存在数据合规与权限风险。

这个 Skill 做什么

审计跨平台归因与转化定义，校对 GA4、MMP、服务器/浏览器事件与离线转化。

把 GA4、MMP、浏览器/服务器事件和线下转化的计数规则都拉平核对，找出重复计数、归因窗口不一致或跨平台口径差异。用在碰到转化数据对不上、要设计归因模型或要把 Meta/Google 的转化口径统一时。特别会列清每个来源的去重、隐私限制和报告窗口，给出可执行的对账和修正建议。

▸ 展开 SKILL.md 英文原文

Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation. Use for attribution audit, attribution models, conversion windows, requests to add or total Meta and Google conversions, incompatible reporting-window aggregation, GA4 attribution, MMP review, AppsFlyer, Adjust, Branch, Singular, or cross-platform discrepancies.

垂直行业归因跨平台分析通用

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SKILL.MD 节选查看完整文件 ↗

# Attribution Audit

1. Read the main `ads` contract and normalized account snapshots.
2. Declare the business conversion, value, data window, timezone, currency, and
   decision the attribution analysis must support.
3. Inventory every browser, server, platform, analytics, MMP, offline, and app
   attribution source with its identity, counting, deduplication, and privacy rules.
4. Reconcile comparable events and explain differences caused by eligibility,
   view-through rules, consent, modeled data, conversion lag, thresholds, or scope.
5. Separate measurement quality from platform-reported performance.
6. Return findings, contradictions, confidence, missing evidence, and a measurement
   i

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