Agent Skills › AgriciDaniel/claude-ads › ads-attribution

ads-attribution

GitHub

用于审计跨平台广告归因,核查转化定义、报告窗口及多源数据一致性。通过标准化流程比对各渠道指标,识别差异原因并生成改进计划,确保数据可比性。

skills/ads-attribution/SKILL.md AgriciDaniel/claude-ads

Trigger Scenarios

需要审计跨平台广告归因数据 检查GA4、MMP等平台的数据一致性 分析转化定义和报告窗口的兼容性

Install

npx skills add AgriciDaniel/claude-ads --skill ads-attribution -g -y
More Options

Use without installing

npx skills use AgriciDaniel/claude-ads@ads-attribution

指定 Agent (Claude Code)

npx skills add AgriciDaniel/claude-ads --skill ads-attribution -a claude-code -g -y

安装 repo 全部 skill

npx skills add AgriciDaniel/claude-ads --all -g -y

预览 repo 内 skill

npx skills add AgriciDaniel/claude-ads --list

SKILL.md

Frontmatter
{
    "name": "ads-attribution",
    "description": "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."
}

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 improvement plan through the common JSON contract.

Do not assume one platform is ground truth, add incompatible reports together, or recommend an attribution model without the operator's decision context.

Comparability gate

Reject aggregation until the sources share, or are explicitly normalized to, the same conversion event and value definition, attribution window, click/view scope, counting method, deduplication identity, timezone, currency, attribution model, and modeled-data treatment. Until then, report the values side by side with their definitions; do not compute a total.

Example: Meta seven-day conversions and Google thirty-day conversions are incompatible. Refuse to add them, reconcile windows and definitions first, and only aggregate a newly comparable dataset.

Version History

  • 669c760 Current 2026-07-25 07:45

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Metadata

Files
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Version
ac21644
Hash
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Indexed
2026-07-25 07:45

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