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/yogsoth-ai/de-anthropocentric-research-engine --skill audit-data-contaminationAntes 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.
audit-data-contamination
Purpose
Audit train/test leakage, memorization artifacts, temporal leakage, and disclosure pathways that can invalidate evaluation.
Input contract
yaml
required: [dataset_partitions, training_sources, evaluation_records]
optional: [release_history, deduplication_keys, access_logs]
constraints: [each contamination claim requires a matched record, pathway, and comparison basis]Procedure
- Define partition, temporal, entity, and disclosure boundaries.
- Match evaluation items against training and public-source records using declared keys.
- Test suspected leakage pathways and compare affected with unaffected cases.
- Classify confirmed, plausible, and unassessed contamination with impact notes.
Output contract
yaml
produces: [contamination_matches, pathway_map, affected_case_set, impact_assessment, audit_uncertainties]
delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]Quality gates
- Matching keys and time boundaries are recorded.
- False-positive matches are sampled and documented.
Failure and counterexamples
Do not call lexical overlap contamination without a disclosure pathway, and do not infer clean separation from missing metadata.
Provenance map
resolved: knowledge-acquisition-contamination-audit
