version: 1
rules:
  require_primary_source: true
  require_version_model_use_case_and_jurisdiction_fit: true
  require_reproducible_contextual_evidence: true
  require_corroboration_for_major_change: true
  reject_unsourced_claims: true
  automatic_apply: false
# El contexto de la empresa no es una fuente de la profesión: vive en
# organization/roles/machine-learning-engineer.md dentro de cada instalación.
sources:
  - name: NIST Artificial Intelligence Risk Management Framework 1.0
    url: https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-ai-rmf-10
    tier: standard
    topics: [ai-risk, govern, map, measure, manage]
  - name: NIST Generative AI Profile AI 600-1
    url: https://www.nist.gov/publications/artificial-intelligence-risk-management-framework-generative-artificial-intelligence
    tier: standard
    topics: [generative-ai, risks, evaluation, governance]
  - name: ISO IEC 23894:2023 AI risk management
    url: https://webstore.iec.ch/en/publication/82914
    tier: standard
    topics: [ai, risk, lifecycle, integration]
  - name: ISO IEC 42001:2023 AI management system
    url: https://webstore.iec.ch/en/publication/90574
    tier: standard
    topics: [ai-governance, management-system, accountability, improvement]
  - name: ISO IEC 42005:2025 AI system impact assessment
    url: https://webstore.iec.ch/en/publication/107659
    tier: standard
    topics: [ai-impact, people, society, lifecycle, assessment]
  - name: scikit-learn changelog
    url: https://scikit-learn.org/stable/whats_new.html
    tier: project
    topics: [defaults, deprecaciones, api]
  - name: PyTorch releases
    url: https://github.com/pytorch/pytorch/releases
    tier: project
    topics: [versiones, cambios incompatibles]