Cómo usar
- Copia el comando y revisa el paquete antes de instalarlo en tu entorno de agente.
- Consulta las herramientas, credenciales y entornos necesarios en el documento original.
- Describe las entradas y el resultado deseado; contrasta la salida con las fuentes.
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-attributionAntes de empezar
- La instalación no incluye suscripción al modelo, cuota API ni permisos sobre tus archivos.
- Las estrellas e instalaciones reflejan actividad, no una prueba independiente de calidad o seguridad.
Contenido del repositorio de origen con títulos, ejemplos, código, tablas, enlaces e imágenes preservados.
Attribution Audit
- Read the main
adscontract and normalized account snapshots. - Declare the business conversion, value, data window, timezone, currency, and
decision the attribution analysis must support.
- Inventory every browser, server, platform, analytics, MMP, offline, and app
attribution source with its identity, counting, deduplication, and privacy rules.
- Reconcile comparable events and explain differences caused by eligibility,
view-through rules, consent, modeled data, conversion lag, thresholds, or scope.
- Separate measurement quality from platform-reported performance.
- 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.
