Update to Aivana CIO Decision Twin

{
  "name": "process-operations-intelligence",
  "description": "Analyze business processes, operational KPIs, service quality, bottlenecks, recurring issues, root causes, trends and improvement actions. Use for COO, operations, service management and process optimization work. Use when the user needs process operations intelligence for CIO decision support.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 147
    }
  ],
  "skill_md_contents": "---\nname: process-operations-intelligence\ndescription: Analyze business processes, operational KPIs, service quality, bottlenecks, recurring issues, root causes, trends and improvement actions. Use for COO, operations, service management and process optimization work. Use when the user needs process operations intelligence for CIO decision support.\n---\n\n# Process Operations Intelligence\n\n## Mission\n\nIdentify operational friction, recurring problems, process bottlenecks, service-quality risks and concrete improvement actions.\n\n## Inputs\n\nAccept process descriptions, ticket exports, incident summaries, SLA data, cycle-time data, backlog reports, customer feedback, runbooks, operating reviews and service-quality metrics.\n\n## Workflow\n\n1. Identify process scope, actors, handoffs, systems, KPIs and customer/business impact.\n2. Detect bottlenecks, rework loops, long wait states, failure clusters and recurring incidents.\n3. Compare process variants where multiple teams, regions or systems are involved.\n4. Cluster root-cause hypotheses into people, process, technology, data, vendor and governance categories.\n5. Prioritize improvements by impact, effort, risk reduction and time to value.\n6. Convert insights into a practical action plan.\n\n## Output Format\n\n- Executive Summary\n- Process / Operations Situation\n- Bottlenecks & Failure Patterns\n- Recurring Issues and Cause Clusters\n- Service Quality Risks\n- Improvement Opportunities\n- Recommended Actions\n- Owners / Suggested Accountability\n- Evidence & Assumptions\n- Missing Data\n- Next 24h / 7d / 30d Actions\n\n## Guardrails\n\nDo not present causal conclusions as facts unless evidence is strong. Use root-cause hypotheses when data is incomplete.\n"
}