yogsoth-ai/de-anthropocentric-research-engine

specify-metrics

Define primary/secondary metrics, estimands, directionality, uncertainty reporting, and decision thresholds before analysis.

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/yogsoth-ai/de-anthropocentric-research-engine --skill specify-metrics

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.

specify-metrics

Purpose

Define primary/secondary metrics, estimands, directionality, uncertainty reporting, and decision thresholds before analysis.

Input contract

yaml
required: [estimand, outcome_schema, decision_thresholds]
optional: [evidence, assumptions, prior_results]
constraints: [use named scientific objects; retain provenance and missingness; $\alpha$ = 0.05 and power = 0.8 where applicable]

Procedure

  1. Validate the typed inputs and state the decision this operation must support.
  2. Apply the declared operation to the named object; record intermediate values that affect interpretation.
  3. Check boundary conditions and counterexamples, then emit the result with uncertainty and source links.

If estimands, metrics, and decision thresholds are fixed, consider estimate-sample-size as the next tactic.

Output contract

yaml
produces: [specify_metrics_result, evidence_trace, uncertainties]
delta_fields: [evidence_updates, uncertainties]

Quality gates

  • Inputs are named scientific objects with compatible schemas.
  • Every material result has a derivation or source reference.
  • Fixed statistical criteria remain exact where applicable: $\alpha$ 0.05 and power 0.8.

Failure and counterexamples

Return a failed operation with the violated precondition when inputs are incomplete, assumptions are unsupported, or a counterexample defeats the result.

Provenance map

  • intermediate: experiment-execution/metric-specification

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