agricidaniel/claude-ads

ads-attribution

Audit cross-platform attribution, conversion definitions, reporting windows, GA4, AdServices and AdAttributionKit, MMPs, browser and server events, offline conversions, and platform reconciliation.

View source

How to use

  1. Copy the installation command and review the source package before installing it in your own agent environment.
  2. Check the source document for required tools, credentials and supported hosts.
  3. Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-attribution

Before you start

  • Installation does not include a model subscription, API allowance or permission to access your files.
  • Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document

Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.

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.

  1. Inventory every browser, server, platform, analytics, MMP, offline, and app

attribution source with its identity, counting, deduplication, and privacy rules.

  1. Reconcile comparable events and explain differences caused by eligibility,

view-through rules, consent, modeled data, conversion lag, thresholds, or scope.

  1. Separate measurement quality from platform-reported performance.
  2. 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.

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