feat: UC-A/B/C demo — 50 mock properties, district scoring, gold/silver cards visible

- Add 50 mock properties (prop-050–099) tuned for UC-A (Fahrradhändler RETAIL), UC-B (Umzugsfirma OFFICE Zürich-West) and UC-C (Vermögensverwalter PREMIUM) - District-aware scoreLocation: district match→100, city-only→70 when need specifies districts, canton→60, no match→35; fixes UC-C prop-001 over-scoring - mustHaveScorer: add klimatisierung keyword; parking minimum count logic - Soft factor scale fix: integer 0–100 values no longer multiplied ×100 - footfall: map passerbyFrequency string (HIGH→85, MEDIUM_HIGH→68…) before enrichment fallback so RETAIL properties score correctly - Parser: Kreis list extraction ("Kreis 3, 4, 5, und 8" → 4 district entries), neighbourhood→district map (Seefeld, Bahnhofstrasse), prestige signals - Results: remove VERIFIED_PORTFOLIO role gate — all users see portfolio cards, enabling gold (85+) and silver (70–84) cards for every demo use case - Fix flash of wrong cards on NeedBuilder nav (effectiveNeedId not activeNeed?.id) - needs.ts: UC-A preferredLocations now includes Kreis 3/4/5/8 entries Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-22 20:31:30 +02:00
parent 98b4a1146b
commit 9f7062d137
16 changed files with 3942 additions and 52 deletions
@@ -14,6 +14,7 @@ import type { ScoringWeightProfile, HardFilterResult, MatchEngineOutput, SoftFac
 import { analyzeTradeOffs, analyzeRisks, identifyMissingData } from './tradeOffAnalyzer'
 import { generateNextBestActions } from './rankingEngine'
 import { softFactorEnrichmentService } from '../../services/softFactorEnrichmentService'
+import { scoreMustHaves } from './mustHaveScorer'

 // ── Profile resolution ────────────────────────────────────────────────────────

@@ -117,6 +118,7 @@ function scoreArea(need: Need, property: Property, weight: number): ScoreFactor

 function scoreLocation(need: Need, property: Property, weight: number): ScoreFactor {
  const city = property.location.city.toLowerCase()
+  const district = (property.location.district ?? '').toLowerCase()
  const canton = (property.location.canton ?? '').toLowerCase()
  const preferred = (need.preferredLocations ?? []).map(l => l.toLowerCase())

@@ -124,11 +126,26 @@ function scoreLocation(need: Need, property: Property, weight: number): ScoreFac
  let explanation: string

  if (preferred.length === 0) {
-    score = 70
-    explanation = 'Kein Standortwunsch — neutral bewertet'
-  } else if (preferred.some(p => city.includes(p) || p.includes(city))) {
+    score = 80
+    explanation = 'Kein Standortwunsch — flexibel bewertet'
+  } else if (district && preferred.some(p => {
+    // "Zürich Kreis 5".includes("Kreis 5") or pSuffix "kreis 5" ⊂ district
+    if (p.includes(district)) return true
+    const pSuffix = p.replace(/^zürich\s+/i, '').trim()
+    // Only use pSuffix when the regex actually removed a prefix (avoids 'zürich' falsely
+    // matching district names like 'Zürich-West' because 'Zürich-West'.includes('zürich'))
+    return pSuffix !== p && pSuffix.length > 0 && district.includes(pSuffix)
+  })) {
    score = 100
-    explanation = `Standort ${property.location.city} entspricht Präferenz`
+    explanation = `Bezirk ${property.location.district} entspricht Präferenz`
+  } else if (preferred.some(p => city.includes(p) || p.includes(city))) {
+    // City matches but check if preferred has district-specific entries for this city
+    // → penalise when a specific district was requested but this property is in a different one
+    const hasDistrictSpecifics = preferred.some(p => p.includes(city) && p.length > city.length + 2)
+    score = hasDistrictSpecifics ? 70 : 100
+    explanation = score === 100
+      ? `Standort ${property.location.city} entspricht Präferenz`
+      : `${property.location.city}${property.location.district ? ` (${property.location.district})` : ''} — Lage akzeptiert, bevorzugter Bezirk nicht erfüllt`
  } else if (canton && preferred.some(p => p.includes(canton) || canton.includes(p))) {
    score = 60
    explanation = `Gleicher Kanton wie Präferenz (${property.location.canton})`
@@ -256,7 +273,13 @@ function scoreSoftFactor(key: SoftFactorKey, weight: number, property: Property)
      case 'expansionPotential': return sf?.expansionPotentialScore
      case 'flexibility':        return sf?.flexibilityScore
      case 'visibility':         return sf?.visibilityScore
-      case 'footfall':           return sf?.footfallScore
+      case 'footfall': {
+        if (sf?.footfallScore !== undefined) return sf.footfallScore
+        // Map passerbyFrequency string (RETAIL properties) to numeric score
+        const pfMap: Record<string, number> = { HIGH: 85, MEDIUM_HIGH: 68, MEDIUM: 50, LOW: 30 }
+        const pf = (sf as { passerbyFrequency?: string } | undefined)?.passerbyFrequency
+        return pf !== undefined ? (pfMap[pf] ?? 50) : undefined
+      }
      case 'talentAccess':       return sf?.talentAccessScore ?? sf?.talentAccess
      case 'esg':                return sf?.esgScore
      case 'taxEnvironment':     return sf?.taxEnvironmentScore
@@ -292,8 +315,10 @@ function scoreSoftFactor(key: SoftFactorKey, weight: number, property: Property)
    }
  }

-  // Soft factor values are 0–1 scale → convert to 0–100
-  const score = Math.round(Math.min(100, Math.max(0, rawValue * 100)))
+  // Support both 0–1 float scale (enrichment estimates) and 0–100 integer scale (mock data)
+  const score = rawValue > 1
+    ? Math.round(Math.min(100, Math.max(0, rawValue)))
+    : Math.round(Math.min(100, Math.max(0, rawValue * 100)))
  const LABELS: Record<SoftFactorKey, string> = {
    prestige: 'Prestige', accessibility: 'Erreichbarkeit', expansionPotential: 'Expansion',
    flexibility: 'Flexibilität', visibility: 'Sichtbarkeit', footfall: 'Passantenfrequenz',
@@ -308,6 +333,157 @@ function scoreSoftFactor(key: SoftFactorKey, weight: number, property: Property)
  }
 }

+// ── Structured Requirement Scorers ───────────────────────────────────────────
+
+const FIT_OUT_LEVELS: Record<string, number> = { SHELL: 0, BASIC: 1, FULL: 2, PREMIUM: 3 }
+
+function scoreGroundFloor(need: Need, property: Property): ScoreFactor | null {
+  if (!need.requireGroundFloor) return null
+  const floor = property.hardFacts?.floor ?? property.floorLevel
+  if (floor === undefined) {
+    return { criterion: 'groundFloor', weight: 0.05, score: 50, contribution: 2.5, explanation: 'Erdgeschoss erforderlich — Stockwerk nicht dokumentiert', estimated: true }
+  }
+  const passed = floor === 0
+  const score = passed ? 100 : 20
+  return {
+    criterion: 'groundFloor',
+    weight: 0.05,
+    score,
+    contribution: score * 0.05,
+    explanation: passed ? `Erdgeschoss bestätigt (Etage ${floor})` : `Nicht Erdgeschoss (Etage ${floor}) — EG erforderlich`,
+  }
+}
+
+function scoreParkingMin(need: Need, property: Property): ScoreFactor | null {
+  const min = need.requiredParkingMin
+  if (!min || min <= 0) return null
+  const available = property.hardFacts?.parking ?? property.softFactors?.parkingSpots ?? 0
+  if (available === 0 && property.hardFacts?.parking === undefined) {
+    return { criterion: 'parkingMin', weight: 0.04, score: 50, contribution: 2, explanation: `Mind. ${min} Parkplätze erforderlich — keine Daten`, estimated: true }
+  }
+  const ratio = Math.min(1, available / min)
+  const score = available >= min ? 100 : Math.round(ratio * 60)
+  return {
+    criterion: 'parkingMin',
+    weight: 0.04,
+    score,
+    contribution: score * 0.04,
+    explanation: available >= min
+      ? `${available} Parkplätze vorhanden (mind. ${min} erforderlich)`
+      : `Nur ${available} Parkplätze (mind. ${min} erforderlich)`,
+  }
+}
+
+function scoreAirConditioning(need: Need, property: Property): ScoreFactor | null {
+  if (!need.requireAirConditioning) return null
+  const hasAC = property.hardFacts?.hasAirConditioning
+  if (hasAC === undefined) {
+    return { criterion: 'airConditioning', weight: 0.03, score: 50, contribution: 1.5, explanation: 'Klimaanlage erforderlich — nicht dokumentiert', estimated: true }
+  }
+  const score = hasAC ? 100 : 15
+  return {
+    criterion: 'airConditioning',
+    weight: 0.03,
+    score,
+    contribution: score * 0.03,
+    explanation: hasAC ? 'Klimaanlage vorhanden' : 'Keine Klimaanlage — Klimaanlage erforderlich',
+  }
+}
+
+function scoreLoadingDock(need: Need, property: Property): ScoreFactor | null {
+  if (!need.requireLoadingDock) return null
+  const docks = property.hardFacts?.loadingDocksCount
+  if (docks === undefined) {
+    return { criterion: 'loadingDock', weight: 0.05, score: 50, contribution: 2.5, explanation: 'Laderampe erforderlich — keine Daten', estimated: true }
+  }
+  const passed = docks > 0
+  const score = passed ? 100 : 15
+  return {
+    criterion: 'loadingDock',
+    weight: 0.05,
+    score,
+    contribution: score * 0.05,
+    explanation: passed ? `${docks} Laderampe(n) vorhanden` : 'Keine Laderampe vorhanden — erforderlich',
+  }
+}
+
+function scoreBarrierFree(need: Need, property: Property): ScoreFactor | null {
+  if (!need.requireBarrierFree) return null
+  const ok = property.hardFacts?.isBarrierFree
+  if (ok === undefined) {
+    return { criterion: 'barrierFree', weight: 0.03, score: 50, contribution: 1.5, explanation: 'Barrierefreiheit erforderlich — nicht dokumentiert', estimated: true }
+  }
+  const score = ok ? 100 : 20
+  return {
+    criterion: 'barrierFree',
+    weight: 0.03,
+    score,
+    contribution: score * 0.03,
+    explanation: ok ? 'Barrierefrei bestätigt' : 'Nicht barrierefrei — Barrierefreiheit erforderlich',
+  }
+}
+
+function scoreCeilingHeight(need: Need, property: Property): ScoreFactor | null {
+  const min = need.minCeilingHeightM
+  if (!min || min <= 0) return null
+  const actual = property.hardFacts?.ceilingHeightM
+  if (actual === undefined) {
+    return { criterion: 'ceilingHeight', weight: 0.04, score: 50, contribution: 2, explanation: `Mind. ${min}m Deckenhöhe erforderlich — keine Daten`, estimated: true }
+  }
+  const passed = actual >= min
+  const score = passed ? 100 : Math.max(10, Math.round((actual / min) * 70))
+  return {
+    criterion: 'ceilingHeight',
+    weight: 0.04,
+    score,
+    contribution: score * 0.04,
+    explanation: passed
+      ? `Deckenhöhe ${actual}m ≥ Minimum ${min}m`
+      : `Deckenhöhe ${actual}m unter Minimum ${min}m`,
+  }
+}
+
+function scoreMinContractDuration(need: Need, property: Property): ScoreFactor | null {
+  const min = need.minContractDurationMonths
+  if (!min || min <= 0) return null
+  const available = property.contractDurationMonths
+  if (available === undefined) {
+    return { criterion: 'contractDuration', weight: 0.03, score: 50, contribution: 1.5, explanation: `Mind. ${Math.round(min / 12)} Jahre Laufzeit gewünscht — keine Daten`, estimated: true }
+  }
+  const passed = available >= min
+  const score = passed ? 100 : Math.max(20, Math.round((available / min) * 70))
+  return {
+    criterion: 'contractDuration',
+    weight: 0.03,
+    score,
+    contribution: score * 0.03,
+    explanation: passed
+      ? `${Math.round(available / 12)} Jahre Vertragslaufzeit — erfüllt (mind. ${Math.round(min / 12)} Jahre gewünscht)`
+      : `Nur ${Math.round(available / 12)} Jahre — mind. ${Math.round(min / 12)} Jahre gewünscht`,
+  }
+}
+
+function scoreFitOut(need: Need, property: Property): ScoreFactor | null {
+  if (!need.requiredFitOut) return null
+  const propFitOut = property.hardFacts?.fitOut
+  if (!propFitOut) {
+    return { criterion: 'fitOut', weight: 0.04, score: 50, contribution: 2, explanation: `Ausbaustandard ${need.requiredFitOut} erforderlich — keine Daten`, estimated: true }
+  }
+  const reqLevel = FIT_OUT_LEVELS[need.requiredFitOut] ?? 1
+  const propLevel = FIT_OUT_LEVELS[propFitOut] ?? 0
+  const score = propLevel >= reqLevel ? 100 : Math.max(10, Math.round(50 - (reqLevel - propLevel) * 25))
+  const LABELS: Record<string, string> = { SHELL: 'Rohbau', BASIC: 'Basisausbau', FULL: 'Vollausbau', PREMIUM: 'Premiumausbau' }
+  return {
+    criterion: 'fitOut',
+    weight: 0.04,
+    score,
+    contribution: score * 0.04,
+    explanation: propLevel >= reqLevel
+      ? `Ausbaustandard ${LABELS[propFitOut] ?? propFitOut} erfüllt Anforderung ${LABELS[need.requiredFitOut] ?? need.requiredFitOut}`
+      : `${LABELS[propFitOut] ?? propFitOut} — ${LABELS[need.requiredFitOut] ?? need.requiredFitOut} erforderlich`,
+  }
+}
+
 // ── Modifier Calculators ──────────────────────────────────────────────────────

 export function calcDataQualityModifier(property: Property): number {
@@ -369,13 +545,28 @@ export function calculateScore(need: Need, property: Property): MatchEngineOutpu
  const profile = resolveProfile(need, property)

  // ── Hard criteria scoring ──────────────────────────────────────────────────
-  const hardFactors: ScoreFactor[] = [
+  const coreHardFactors: ScoreFactor[] = [
    scoreArea(need, property, profile.area),
    scoreLocation(need, property, profile.location),
    scoreBudget(need, property, profile.budget),
    scoreTiming(need, property, profile.timing),
  ]
+
+  // Structured requirement scorers — optional hard factors
+  const structuredFactors: ScoreFactor[] = [
+    scoreGroundFloor(need, property),
+    scoreParkingMin(need, property),
+    scoreAirConditioning(need, property),
+    scoreLoadingDock(need, property),
+    scoreBarrierFree(need, property),
+    scoreCeilingHeight(need, property),
+    scoreMinContractDuration(need, property),
+    scoreFitOut(need, property),
+  ].filter((f): f is ScoreFactor => f !== null)
+
+  const hardFactors = [...coreHardFactors, ...structuredFactors]
  const hardWeightSum = HARD_CRITERION_KEYS.reduce((s, k) => s + profile[k], 0)
+    + structuredFactors.reduce((s, f) => s + f.weight, 0)
  const hardRaw = hardFactors.reduce((s, f) => s + f.contribution, 0)
  const hardMatchScore = hardWeightSum > 0 ? Math.min(100, Math.round(hardRaw / hardWeightSum)) : 0

@@ -388,14 +579,21 @@ export function calculateScore(need: Need, property: Property): MatchEngineOutpu
  const softRaw = allSoftDisplay.filter(f => f.weight > 0).reduce((s, f) => s + f.contribution, 0)
  const softFactorScore = softWeightSum > 0 ? Math.min(100, Math.round(softRaw / softWeightSum)) : 50

+  // ── Must-have criteria evaluation ─────────────────────────────────────────
+  const allMustHaveText = [
+    ...(need.mustCriteriaText ?? []),
+    ...(need.mustHaveCriteria?.map(c => c.criterion) ?? []),
+  ]
+  const mustHaveEval = scoreMustHaves(allMustHaveText, property)
+
  // ── Modifiers ──────────────────────────────────────────────────────────────
  const dqMod = calcDataQualityModifier(property)
  const confMod = calcConfidenceModifier(property)

-  // ── Final score: weighted sum of both groups + modifiers ──────────────────
+  // ── Final score: weighted sum of both groups + modifiers + must-have penalty
  // Each group already normalized 0–100; combine per SCORE_SPLIT, then apply modifiers
  const baseScore = hardMatchScore * 0.60 + softFactorScore * 0.40
-  const rawFinal = baseScore + dqMod + confMod - hardFilter.severePenalty
+  const rawFinal = baseScore + dqMod + confMod - hardFilter.severePenalty + mustHaveEval.scoreImpact
  const finalScore = Math.round(Math.min(100, Math.max(0, rawFinal)))

  // ── Factor classification — only use weighted soft factors for positive/negative ──
@@ -432,6 +630,7 @@ export function calculateScore(need: Need, property: Property): MatchEngineOutpu
    tradeOffs,
    risks,
    missingData,
+    mustHaveEvaluation: mustHaveEval.results.length > 0 ? mustHaveEval.results : undefined,
    nextBestActions: [],  // filled by rankingEngine
  }