Update to Power BI Desktop

{
  "description": "Use when constraining Power BI revenue planning by delivery, capacity, stock, supply, margin, cash, payment terms, sales resources, or operational feasibility rather than forecasting unconstrained demand only.",
  "included_files": [
    {
      "relative_path": "agents/openai.yaml",
      "size_in_bytes": 146
    }
  ],
  "name": "powerbi-constraint-aware-planning",
  "skill_md_contents": "---\r\nname: powerbi-constraint-aware-planning\r\ndescription: Use when constraining Power BI revenue planning by delivery, capacity, stock, supply, margin, cash, payment terms, sales resources, or operational feasibility rather than forecasting unconstrained demand only.\r\n---\r\n\r\n# Power BI Constraint-Aware Planning\r\n\r\nUse this skill when autonomous planning must respect operational limits.\r\n\r\n## Constraint classes\r\n\r\n- delivery: planned date, requested date, delay, shipment risk\r\n- inventory: stockout, substitute availability, item lifecycle\r\n- capacity: production, picking, shipping, service bottlenecks\r\n- commercial: margin, discount, price change, payment terms\r\n- customer: block status, churn risk, buying cadence, credit risk\r\n- sales: owner capacity, account priority, campaign timing\r\n\r\n## Workflow\r\n\r\n1. Start from an unconstrained forecast or target scenario.\r\n2. Apply constraints as filters or down-weighting factors.\r\n3. Produce both unconstrained and constrained values.\r\n4. Explain every material reduction.\r\n5. Mark missing constraints as `unknown`, not as zero risk.\r\n\r\n## Required outputs\r\n\r\n- `forecast_month`\r\n- `customer`\r\n- `product`\r\n- `unconstrained_forecast`\r\n- `constrained_forecast`\r\n- `constraint_type`\r\n- `constraint_severity`\r\n- `revenue_blocked`\r\n- `evidence`\r\n- `recommended_resolution`\r\n\r\n## Guardrails\r\n\r\n- Never assume demand can convert when delivery or credit constraints contradict it.\r\n- Keep constraint assumptions auditable and separate from statistical demand.\r\n"
}