capability: rag.reranking
version: 1
description: Second-stage ranking of retrieved text candidates.
input_schema:
  type: object
  additionalProperties: false
  required: [query, documents, top_n]
  properties:
    query: {type: string, minLength: 1, maxLength: 4000}
    documents:
      type: array
      minItems: 1
      maxItems: 40
      items:
        type: object
        additionalProperties: false
        required: [id, text]
        properties:
          id: {type: string, minLength: 1, maxLength: 255}
          text: {type: string, minLength: 1, maxLength: 16384}
    top_n: {type: integer, minimum: 1, maximum: 10}
output_schema:
  type: object
  additionalProperties: false
  required: [results]
  properties:
    results:
      type: array
      maxItems: 10
      items:
        type: object
        additionalProperties: false
        required: [id, score, rank]
        properties:
          id: {type: string}
          score: {type: number}
          rank: {type: integer, minimum: 1, maximum: 10}
modalities: {input: [text], output: [score]}
languages: [nl, en]
quality_metrics: [mrr, ndcg_at_10, ranking_accuracy]
upgrade_class: behavioral
fallback: {allowed: false, mode: hard_fail}
privacy: {classification: confidential, allow_persistence: false, allow_logging_payloads: false, allow_network_egress: false}
resources: {accelerator_required: true, cpu_fallback_allowed: false}
production_priority: production
default_residency: load_on_demand
estate:
  category: RAG
  purpose: Evidence-gated second-stage ranking for retrieval pipelines.
  stability: experimental
  resource_class: MEDIUM
  evaluation_type: retrieval
  consumers: [examplerag]
  payload_limits: {max_bytes: 262144, max_batch_count: 40}