fix: P0 stabilisation — score modifiers, logout cache clear, provider isolation, mutation error feedback

- scoreCalculator: apply dataQuality/confidence modifiers to finalScore (were computed but hardcoded to 0)
- authService: call queryClient.clear() on logout to prevent cross-session data leakage
- queryClient: extract to src/lib/queryClient.ts singleton so services can access it without circular imports
- matchSyncService: new service layer owns match-generation logic; MockupNeedProvider no longer imports other providers directly
- hooks (11 files): add onError + German toast feedback to every useMutation

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/features/matching/scoreCalculator.ts

@@ -586,9 +586,17 @@ export function calculateScore(need: Need, property: Property): MatchEngineOutpu
   ]
   const mustHaveEval = scoreMustHaves(allMustHaveText, property)
 
-  // ── Final score: purely hard/soft weighted sum + must-have penalty ──────────
+  // ── Modifiers: data quality and confidence adjust the final score ─────────
+  // These are intentionally applied after the hard/soft weighted sum so that
+  // a low-confidence or poor-data property can be penalised without distorting
+  // the individual criterion breakdown.
+  const dataQualityModifier = calcDataQualityModifier(property)
+  const confidenceModifier  = calcConfidenceModifier(property)
+
+  // ── Final score: hard/soft weighted sum + must-have penalty + modifiers ───
   const baseScore = hardMatchScore * 0.60 + softFactorScore * 0.40
   const rawFinal = baseScore - hardFilter.severePenalty + mustHaveEval.scoreImpact
+    + dataQualityModifier + confidenceModifier
   const finalScore = Math.round(Math.min(100, Math.max(0, rawFinal)))
 
   // ── Factor classification — only use weighted soft factors for positive/negative ──
@@ -616,8 +624,8 @@ export function calculateScore(need: Need, property: Property): MatchEngineOutpu
     finalScore,
     hardMatchScore,
     softFactorScore,
-    dataQualityModifier: 0,
-    confidenceModifier: 0,
+    dataQualityModifier,
+    confidenceModifier,
     positiveFactors,
     negativeFactors,
     allHardFactors: hardFactors,