from __future__ import annotations

from decimal import Decimal


def build_pricing_recommendations(
    cost_floor: dict,
    value_range: dict,
    market_price: dict,
    simulations: dict,
    usage_summary: dict,
) -> list[dict]:
    recommendations: list[dict] = []
    margin_pct = Decimal(str(cost_floor.get("gross_margin_pct", "0")))
    ai_spend = Decimal(str(usage_summary.get("total_ai_spend_eur", "0")))
    active_price = Decimal(str(value_range.get("current_price_eur", "0")))
    cost_per_member = Decimal(str(cost_floor.get("cost_per_member", "0")))

    if margin_pct < Decimal("10"):
        recommendations.append(
            {
                "id": "margin-pressure",
                "priority": "high",
                "title": "Margin below 10%",
                "rationale": f"Gross margin is {margin_pct}% at current pricing.",
                "suggested_action": "Review infrastructure cost or test a higher access fee within value-range bands.",
            }
        )

    if ai_spend > Decimal("0") and cost_per_member > Decimal("0"):
        ai_ratio = (ai_spend / cost_per_member) * Decimal("100")
        if ai_ratio > Decimal("15"):
            best = simulations.get("best_margin_scenario_id")
            recommendations.append(
                {
                    "id": "usage-pricing-signal",
                    "priority": "medium",
                    "title": "AI cost becoming material",
                    "rationale": f"AI spend is {ai_ratio:.1f}% of cost-per-member this period.",
                    "suggested_action": f"Evaluate hybrid model '{best}' in the pricing simulator before customer-visible credits.",
                }
            )

    if market_price.get("market_high_eur") and active_price < Decimal(str(market_price["market_high_eur"])):
        headroom = Decimal(str(value_range.get("aggregate_high_eur", active_price))) - active_price
        if headroom > Decimal("5"):
            recommendations.append(
                {
                    "id": "value-headroom",
                    "priority": "low",
                    "title": "Value headroom above list price",
                    "rationale": f"Aggregate value band high is €{value_range['aggregate_high_eur']} vs €{active_price} list.",
                    "suggested_action": "Run a staged price experiment within the solo-builder segment band.",
                }
            )

    if not recommendations:
        recommendations.append(
            {
                "id": "hold-course",
                "priority": "low",
                "title": "Hold current pricing",
                "rationale": "No urgent margin, usage, or competitive signals detected.",
                "suggested_action": "Continue observatory tracking; re-run after next ledger period.",
            }
        )

    return recommendations