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 select-next-pairAntes 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.
select-next-pair
Purpose
Select the next comparison pair to maximize expected information gain while respecting unresolved uncertainty and coverage.
Input contract
yaml
required: [candidate_set, current_ratings, uncertainty_matrix, comparison_budget]
optional: [pair_history, exploration_policy, exclusion_constraints]
constraints: [candidate IDs are stable; expected information gain uses the declared model and available evidence]Procedure
- Enumerate eligible unjudged pairs and compute their current uncertainty and decision relevance.
- Estimate expected information gain under the declared comparison model, including the value of resolving a tie or cycle.
- Exclude pairs blocked by scope or data constraints, then select the highest-value eligible pair.
- Return the selected pair, rationale, alternatives considered, and the budget impact.
Output contract
yaml
produces: [selected_pair, information_gain_estimate, candidate_pair_table, selection_rationale]
delta_fields: [findings, evidence_updates, uncertainties, decisions, recommended_jumps]Quality gates
- The selected pair is eligible, not already resolved under the same model, and has a stated information-gain rationale.
- If all pairs are exhausted or blocked, return an explicit stop reason.
Failure and counterexamples
Do not select a pair solely because it is adjacent in a list. Expected information gain cannot be claimed when uncertainty inputs are absent.
Provenance map
- resolved: pair-selector
