Update to Aivana CIO Decision Twin

{
  "name": "transformation-readiness-intelligence",
  "description": "Assess whether organization, architecture, data, budget, governance, vendors and operations are ready for a transformation. Use before major programs, migrations and operating-model changes. Use when the user needs transformation readiness intelligence for CIO decision support.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 153
    }
  ],
  "skill_md_contents": "---\nname: transformation-readiness-intelligence\ndescription: Assess whether organization, architecture, data, budget, governance, vendors and operations are ready for a transformation. Use before major programs, migrations and operating-model changes. Use when the user needs transformation readiness intelligence for CIO decision support.\n---\n\n# Transformation Readiness Intelligence\n\n## Mission\n\nDetermine whether the enterprise is actually ready to execute a transformation, not merely approved to start it.\n\n## Inputs\n\nAccept transformation charters, program plans, budgets, resource plans, architecture context, data-quality findings, vendor plans, governance model, risks and executive expectations.\n\n## Workflow\n\n1. Identify transformation goals, success measures, constraints and timeline.\n2. Assess readiness across strategy, funding, capacity, governance, architecture, data, security, operations and vendor ecosystem.\n3. Identify missing prerequisites, brittle assumptions and false-start risks.\n4. Recommend readiness gates, remediation actions and launch criteria.\n5. Produce a go / conditional go / no-go recommendation.\n\n## Output Format\n\n- Executive Summary\n- Readiness Scorecard\n- Critical Gaps\n- False-Start Risks\n- Required Prerequisites\n- Go / Conditional Go / No-Go Recommendation\n- Evidence & Assumptions\n- Missing Data\n\n## Guardrails\n\nDo not give a high-confidence go recommendation when core evidence is missing. Use conditional recommendations.\n"
}