yogsoth-ai/de-anthropocentric-research-engine

validate-causal-link

Audit a causal relation for clarity, existence, sufficiency, and logical completeness using CLR-style checks.

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 validate-causal-link

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.

validate-causal-link

Purpose

Audit a causal relation for clarity, existence, sufficiency, and logical completeness using CLR-style checks.

Input contract

yaml
required: [causal_relation, source_evidence, boundary_conditions]
optional: [causal_graph, alternative_explanations, clr_checklist]
constraints: [the relation has explicit cause and effect; distinguish clarity, existence, sufficiency, and logical completeness]

Procedure

  1. Parse the causal relation and define its scope and terms.
  2. Check whether the stated cause exists and is connected to the effect.
  3. Test sufficiency, omitted conditions, and alternative explanations.
  4. Record each CLR result and return a validated, weakened, or unresolved link.

Output contract

yaml
produces: [causal_link_assessment, clr_results, missing_conditions, evidence_requests]
delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties]

Quality gates

  • All eight CLR categories are retained when the caller supplies the full checklist.
  • Clarity, existence, sufficiency, and logical completeness are reported separately.
  • A causal label is not accepted when evidence supports only association.

Parameterization

The caller must provide the cause/effect schema, evidence and boundary conditions, CLR checklist, alternative-explanation fields, and verdict vocabulary.

Failure and counterexamples

Reject links with undefined variables, missing scope, circular support, or causal language unsupported by the evidence.

Provenance map

  • resolved: deep-insight/clr-validation

Preserved source criteria ledger

sourcephysical linekindsource criterion
deep-insight/clr-validation13structuralRetain eight CLR validation categories for causal claims: clarity, existence, sufficiency, and logical completeness are explicit checks.

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