/**
 * WorthDoing.ai
 * Author: Simon-Pierre Boucher
 * Contact: contact@spboucher.ai
 * File: tests/scoring.test.ts
 * Description: Worth Score computation tests — weighting, renormalization, separate evidence confidence.
 */
import { describe, it, expect } from "vitest";
import { computeWorthScore, type DimensionScore } from "@/lib/agent/scoring";

const dim = (
  dimension: DimensionScore["dimension"],
  score: number,
  confidence: number,
): DimensionScore => ({ dimension, score, confidence });

describe("computeWorthScore", () => {
  it("returns the score itself when all dimensions are equal", () => {
    const { worthScore } = computeWorthScore([
      dim("demand", 80, 0.9),
      dim("neglectedness", 80, 0.9),
      dim("feasibility", 80, 0.9),
      dim("why_now", 80, 0.9),
      dim("impact", 80, 0.9),
    ]);
    expect(worthScore).toBe(80);
  });

  it("keeps evidence confidence separate from the score", () => {
    const strong = computeWorthScore([dim("demand", 90, 0.95), dim("impact", 90, 0.95)]);
    const weak = computeWorthScore([dim("demand", 90, 0.3), dim("impact", 90, 0.3)]);
    expect(strong.worthScore).toBe(weak.worthScore); // same score...
    expect(strong.evidenceConfidence).toBeGreaterThan(weak.evidenceConfidence); // ...different confidence
  });

  it("weights demand and impact more than risk", () => {
    const demandHeavy = computeWorthScore([dim("demand", 100, 1), dim("risk", 0, 1)]);
    const riskHeavy = computeWorthScore([dim("demand", 0, 1), dim("risk", 100, 1)]);
    expect(demandHeavy.worthScore).toBeGreaterThan(riskHeavy.worthScore);
  });

  it("renormalizes weights over provided dimensions", () => {
    const { worthScore } = computeWorthScore([dim("demand", 60, 0.8)]);
    expect(worthScore).toBe(60);
  });

  it("handles the empty case defensively", () => {
    expect(computeWorthScore([])).toEqual({ worthScore: 0, evidenceConfidence: 0 });
  });
});