backend/app/api/v1/parcels.py

@@ -140,7 +140,7 @@ def _fetch_seasonal_weather_sync(lat: float, lon: float) -> dict | None:
                 "period": "1995-2024 (30 лет)",
                 "model": "MRI-AGCM3-2-S",
                 "source": "open-meteo-climate",
-                "note": ("Климатические нормали. " "Текущая погода — отдельный API."),
+                "note": ("Климатические нормали. Текущая погода — отдельный API."),
             }
     except Exception as e:
         logger.warning("seasonal weather fetch failed: %s", e)
@@ -240,6 +240,21 @@ def _score_label(s: float) -> str:
     return "хорошо" if s < SCORE_THRESHOLDS["отлично"] else "отлично"
 
 
+def _confidence_label(c: float) -> str:
+    """Текстовая интерпретация confidence (0..1).
+
+    Пороги:
+      high   — c > 0.75 (плотные актуальные данные)
+      medium — 0.4-0.75
+      low    — c < 0.4 (caveats обязательны)
+    """
+    if c >= 0.75:
+        return "high"
+    if c >= 0.4:
+        return "medium"
+    return "low"
+
+
 # Веса POI-категорий для scoring (Максим: трамвай = минус)
 _POI_WEIGHTS: dict[str, float] = {
     "school": 1.5,
@@ -321,6 +336,105 @@ def _geotech_risk(region_code: int, db: Session, geom_wkt: str) -> dict[str, Any
     }
 
 
+def _compute_confidence(
+    *,
+    source: str,
+    poi_rows: list[dict[str, Any]],
+    district_row: dict[str, Any] | None,
+    competitor_rows: list[dict[str, Any]],
+    noise_sources_count: int,
+    air_q: dict[str, Any] | None,
+    weather: dict[str, Any] | None,
+    market_trend: dict[str, Any] | None,
+    zoning: dict[str, Any],
+) -> dict[str, Any]:
+    """X2 (#48) — composite confidence score 0..1 + caveats.
+
+    Stub-версия (до реализации G1/G2/D1/D2): использует сигналы которые уже
+    доступны на main. Композитный балл = avg of subscore'ов; caveats — list
+    конкретных проблем для UI ("Нет данных N, score K ненадёжен").
+    """
+    import datetime as _dt
+
+    caveats: list[str] = []
+    subscores: dict[str, float] = {}
+
+    # 1) POI freshness — % POI с last_osm_edit_date в последние 2 года.
+    # Для участков с малым числом POI (<5) — снижаем confidence как coverage.
+    poi_total = len(poi_rows)
+    if poi_total == 0:
+        subscores["poi_freshness"] = 0.0
+        caveats.append("OSM POI не найдены в радиусе 1км — скоринг неприменим")
+    else:
+        cutoff = _dt.date.today() - _dt.timedelta(days=730)
+        fresh = sum(
+            1 for p in poi_rows if p.get("last_osm_edit_date") and p["last_osm_edit_date"] >= cutoff
+        )
+        ratio = fresh / poi_total
+        # coverage penalty: <5 POI слабая статистика
+        coverage_factor = min(1.0, poi_total / 10.0)
+        subscores["poi_freshness"] = round(ratio * coverage_factor, 2)
+        if poi_total < 5:
+            caveats.append(f"Мало OSM POI в радиусе 1км ({poi_total}) — социалка-фактор ненадёжен")
+        elif ratio < 0.5:
+            caveats.append("Большая часть POI (>50%) старше 2 лет — данные OSM требуют обновления")
+
+    # 2) Geometry source confidence — участок > квартал
+    subscores["geom_source"] = 0.9 if source == "cad_building" else 0.6
+    if source == "cad_quarter":
+        caveats.append(
+            "Геометрия quartal-level (нет parcel shape) — окружение усреднено по кварталу"
+        )
+
+    # 3) District context — известен ли район
+    subscores["district"] = 1.0 if district_row else 0.3
+    if not district_row:
+        caveats.append("Район не определён (вне границ ЕКБ?) — медианные цены недоступны")
+
+    # 4) Market trend — есть ли rosreestr_deals
+    if market_trend and market_trend.get("recent_deals_count"):
+        n_recent = int(market_trend["recent_deals_count"])
+        # порог 5 сделок за 6 мес — достаточно для тренда
+        subscores["market_trend"] = min(1.0, n_recent / 10.0)
+        if n_recent < 5:
+            caveats.append(f"Мало ДДУ за 6 мес ({n_recent}) — тренд рынка статистически слабый")
+    else:
+        subscores["market_trend"] = 0.0
+        caveats.append("Нет ДДУ в 3км — тренд рынка недоступен")
+
+    # 5) Competitors coverage
+    n_competitors = len(competitor_rows)
+    subscores["competitors"] = min(1.0, n_competitors / 5.0)
+    if n_competitors == 0:
+        caveats.append("Нет конкурентов-ЖК в 3км — низкая урбанизация / окраина")
+
+    # 6) Environmental data freshness
+    env_ok = sum([bool(noise_sources_count > 0), bool(air_q), bool(weather)])
+    subscores["environment"] = env_ok / 3.0
+    if noise_sources_count == 0:
+        caveats.append("Шумовая карта не загружена — noise score = stub")
+    if not air_q:
+        caveats.append("Air Quality API недоступен — exposure unknown")
+
+    # 7) ПЗЗ coverage — placeholder до G1
+    has_zoning = bool(zoning.get("data_available")) if zoning else False
+    subscores["zoning"] = 1.0 if has_zoning else 0.2
+    if not has_zoning:
+        caveats.append(
+            "ПЗЗ zone_code не известен — нельзя оценить разрешённое использование (G1 pending)"
+        )
+
+    composite = sum(subscores.values()) / len(subscores)
+    composite = round(max(0.0, min(1.0, composite)), 2)
+
+    return {
+        "value": composite,
+        "label": _confidence_label(composite),
+        "breakdown": subscores,
+        "caveats": caveats,
+    }
+
+
 @router.post("/search", response_model=ParcelSearchResponse)
 async def search_parcels(payload: ParcelSearchRequest) -> ParcelSearchResponse:
     """Search parcels by filters + scoring.
@@ -906,6 +1020,19 @@ def analyze_parcel(
 
     score_final = score + center_bonus
 
+    # X2 (#48): composite confidence + caveats
+    confidence_info = _compute_confidence(
+        source=source,
+        poi_rows=[dict(p) for p in poi_rows],
+        district_row=dict(district_row) if district_row else None,
+        competitor_rows=[dict(c) for c in competitor_rows],
+        noise_sources_count=len(noise_rows),
+        air_q=air_q,
+        weather=weather,
+        market_trend=market_trend,
+        zoning=zoning,
+    )
+
     return {
         "cad_num": cad_num,
         "source": source,
@@ -946,6 +1073,11 @@ def analyze_parcel(
         "zoning": zoning,
         "success_recommendation": success_recommendation,
         "isochrones_available": bool(settings.openrouteservice_api_key),
+        # X2 (#48) — confidence indicator
+        "confidence": confidence_info["value"],
+        "confidence_label": confidence_info["label"],
+        "confidence_breakdown": confidence_info["breakdown"],
+        "confidence_caveats": confidence_info["caveats"],
     }
 
 

frontend/src/components/site-finder/ConfidenceBadge.tsx

@@ -0,0 +1,167 @@
+"use client";
+
+import { useState } from "react";
+
+interface Props {
+  value: number;
+  label: "high" | "medium" | "low";
+  breakdown?: Record<string, number>;
+  caveats?: string[];
+}
+
+const LABEL_RU: Record<Props["label"], string> = {
+  high: "высокая",
+  medium: "средняя",
+  low: "низкая",
+};
+
+const COLOR: Record<
+  Props["label"],
+  { bg: string; fg: string; border: string }
+> = {
+  high: { bg: "#dcfce7", fg: "#15803d", border: "#86efac" },
+  medium: { bg: "#fef9c3", fg: "#a16207", border: "#fde68a" },
+  low: { bg: "#fee2e2", fg: "#b91c1c", border: "#fca5a5" },
+};
+
+const BREAKDOWN_RU: Record<string, string> = {
+  poi_freshness: "Свежесть OSM POI",
+  geom_source: "Точность геометрии",
+  district: "Известность района",
+  market_trend: "Глубина ДДУ",
+  competitors: "Покрытие конкурентами",
+  environment: "Экологические данные",
+  zoning: "ПЗЗ / зонирование",
+};
+
+export function ConfidenceBadge({ value, label, breakdown, caveats }: Props) {
+  const [expanded, setExpanded] = useState(false);
+  const c = COLOR[label];
+  const pct = Math.round(value * 100);
+  const hasDetails =
+    (caveats && caveats.length > 0) ||
+    (breakdown && Object.keys(breakdown).length > 0);
+
+  return (
+    <div
+      style={{
+        border: `1px solid ${c.border}`,
+        background: c.bg,
+        borderRadius: 10,
+        padding: "10px 14px",
+        display: "flex",
+        flexDirection: "column",
+        gap: 8,
+      }}
+    >
+      <div
+        style={{
+          display: "flex",
+          alignItems: "center",
+          justifyContent: "space-between",
+          gap: 12,
+        }}
+      >
+        <div style={{ display: "flex", alignItems: "center", gap: 10 }}>
+          <span
+            style={{
+              fontSize: 11,
+              fontWeight: 700,
+              color: c.fg,
+              textTransform: "uppercase",
+              letterSpacing: "0.06em",
+            }}
+          >
+            Достоверность
+          </span>
+          <span
+            style={{
+              fontSize: 14,
+              fontWeight: 700,
+              color: c.fg,
+              fontVariantNumeric: "tabular-nums",
+            }}
+            title="Composite confidence: средневзвешенная по 7 подскорам"
+          >
+            {pct}% · {LABEL_RU[label]}
+          </span>
+        </div>
+        {hasDetails && (
+          <button
+            type="button"
+            onClick={() => setExpanded((e) => !e)}
+            aria-expanded={expanded}
+            style={{
+              background: "none",
+              border: "none",
+              padding: 0,
+              color: c.fg,
+              fontSize: 12,
+              cursor: "pointer",
+              fontWeight: 500,
+              textDecoration: "underline",
+            }}
+          >
+            {expanded ? "Скрыть" : "Подробнее"}
+          </button>
+        )}
+      </div>
+
+      {/* Caveats — показываем сразу для low, под toggle для medium/high */}
+      {caveats && caveats.length > 0 && (label === "low" || expanded) && (
+        <ul
+          style={{
+            margin: 0,
+            padding: 0,
+            paddingLeft: 18,
+            fontSize: 12,
+            color: c.fg,
+            display: "flex",
+            flexDirection: "column",
+            gap: 3,
+          }}
+        >
+          {caveats.map((cv, i) => (
+            <li key={i}>{cv}</li>
+          ))}
+        </ul>
+      )}
+
+      {/* Breakdown — под toggle */}
+      {expanded && breakdown && Object.keys(breakdown).length > 0 && (
+        <div
+          style={{
+            display: "flex",
+            flexDirection: "column",
+            gap: 4,
+            fontSize: 12,
+            color: c.fg,
+            paddingTop: 6,
+            borderTop: `1px solid ${c.border}`,
+          }}
+        >
+          {Object.entries(breakdown).map(([k, v]) => (
+            <div
+              key={k}
+              style={{
+                display: "flex",
+                justifyContent: "space-between",
+                gap: 12,
+              }}
+            >
+              <span>{BREAKDOWN_RU[k] ?? k}</span>
+              <span
+                style={{
+                  fontVariantNumeric: "tabular-nums",
+                  fontWeight: 600,
+                }}
+              >
+                {Math.round(v * 100)}%
+              </span>
+            </div>
+          ))}
+        </div>
+      )}
+    </div>
+  );
+}

frontend/src/components/site-finder/OverviewTab.tsx

@@ -2,6 +2,7 @@
 
 import type { FeatureCollection } from "geojson";
 import type { ParcelAnalysis } from "@/types/site-finder";
+import { ConfidenceBadge } from "./ConfidenceBadge";
 import { IsochronesPanel } from "./IsochronesPanel";
 
 interface Props {
@@ -37,6 +38,16 @@ export function OverviewTab({ data, onIsochronesResult }: Props) {
 
   return (
     <div style={{ display: "flex", flexDirection: "column", gap: 20 }}>
+      {/* X2 (#48): confidence indicator на самом верху Overview */}
+      {data.confidence !== undefined && data.confidence_label && (
+        <ConfidenceBadge
+          value={data.confidence}
+          label={data.confidence_label}
+          breakdown={data.confidence_breakdown}
+          caveats={data.confidence_caveats}
+        />
+      )}
+
       {/* District info */}
       {data.district && (
         <div

frontend/src/types/site-finder.ts

@@ -184,6 +184,11 @@ export interface ParcelAnalysis {
   score_without_center?: number;
   location?: ParcelLocation;
   success_recommendation?: ParcelSuccessRecommendation | null;
+  // X2 (#48) — confidence indicator
+  confidence?: number;
+  confidence_label?: "high" | "medium" | "low";
+  confidence_breakdown?: Record<string, number>;
+  confidence_caveats?: string[];
 }
 
 export type PoiCategory =