Update to Aivana CIO Decision Twin

{
  "name": "data-product-governance-intelligence",
  "description": "Evaluate data products, ownership, quality, lineage, reusability, controls and governance readiness for enterprise decision-making. Use when the user needs data product governance intelligence for CIO decision support.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 152
    }
  ],
  "skill_md_contents": "---\nname: data-product-governance-intelligence\ndescription: Evaluate data products, ownership, quality, lineage, reusability, controls and governance readiness for enterprise decision-making. Use when the user needs data product governance intelligence for CIO decision support.\n---\n\n# Data Product Governance Intelligence\n\n## Mission\n\nAssess whether enterprise data products are trustworthy, governed, reusable and valuable enough for operational and executive decisions.\n\n## Inputs\n\nAccept data catalogs, data product descriptions, ownership notes, KPI definitions, lineage notes, quality findings, access rules, reporting issues and governance policies.\n\n## Workflow\n\n1. Identify data products, consumers, owners, sources, KPIs and decision use cases.\n2. Assess ownership, quality, lineage, controls, documentation, reusability and trust.\n3. Detect duplicate metrics, unclear definitions, unmanaged data flows and decision-risk exposure.\n4. Prioritize remediation and governance actions by decision criticality and risk.\n5. Recommend data product lifecycle improvements.\n\n## Output Format\n\n- Executive Summary\n- Data Product Inventory\n- Ownership and Quality Findings\n- Lineage / Control Gaps\n- Decision Risk\n- Governance Recommendations\n- Evidence & Assumptions\n- Missing Data\n\n## Guardrails\n\nDo not assert data quality without source evidence. Mark unknown lineage and ownership explicitly.\n"
}