agricidaniel/claude-ads

ads-test

Design and evaluate paid-ad experiments with hypotheses, randomization units, sample-size and duration assumptions, guardrails, platform experiment tools, analysis, and decision rules.

Ver código fuente

Cómo usar

  1. Copia el comando y revisa el paquete antes de instalarlo en tu entorno de agente.
  2. Consulta las herramientas, credenciales y entornos necesarios en el documento original.
  3. Describe las entradas y el resultado deseado; contrasta la salida con las fuentes.
npx skills add https://github.com/agricidaniel/claude-ads --skill ads-test

Antes 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.
Documento original del Skill

Contenido del repositorio de origen con títulos, ejemplos, código, tablas, enlaces e imágenes preservados.

Paid Media Experiment

  1. State the decision, causal hypothesis, treatment, control, randomization unit,

population, primary metric, guardrails, minimum effect, and stopping rule.

  1. Check platform constraints, overlapping experiments, conversion lag, seasonality,

interference, and measurement quality.

  1. Calculate sample and duration from declared assumptions; disclose approximations.
  2. Change one decision surface unless the design explicitly estimates interactions.
  3. Pre-register exclusions, quality checks, analysis, and decision thresholds.
  4. For readout, verify assignment integrity and data completeness before estimating

effect and uncertainty.

  1. Return setup or readout in versioned JSON with a plain-language decision.

Do not repeatedly peek and stop on a favorable result, call underpowered noise a winner, or generalize beyond the tested population.

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