fix(docs): correct inaccuracies and add missing documentation

Documentation fixes:
- configuration.md: Fix default min period length (30→60 min)
- configuration.md: Fix Average Sensor Display location (Step 6→General Settings)
- sensors-volatility.md: Add missing price_volatility attribute to table
- sensors-trends.md: Document undocumented next_price_trend_change_in sensor
- actions.md: Document undocumented get_price service

Code quality fixes:
- get_price.py: Fix misleading module docstring
- timing.py: Remove dead code (unreachable return None)
- binary_sensor/core.py: Simplify redundant tomorrow_data logic

Impact: Users get accurate documentation. No behavioral changes.

custom_components/tibber_prices/binary_sensor/core.py

@@ -207,11 +207,8 @@ class TibberPricesBinarySensor(TibberPricesEntity, BinarySensorEntity, RestoreEn
         # Get expected intervals for tomorrow (handles DST)
         expected_intervals = self.coordinator.time.get_expected_intervals_for_day(tomorrow_date)
 
-        if interval_count == expected_intervals:
+        # True only when ALL intervals are available (partial = not available)
-            return True
+        return interval_count == expected_intervals
-        if interval_count == 0:
-            return False
-        return False
 
     @property
     def available(self) -> bool:

custom_components/tibber_prices/sensor/calculators/timing.py

@@ -183,9 +183,7 @@ class TibberPricesTimingCalculator(TibberPricesBaseCalculator):
             return future_periods[1]
 
         # Default: return first future period
-        return future_periods[0] if future_periods else None
+        return future_periods[0]
-
-        return None
 
     def _calc_remaining_minutes(self, period: dict) -> int:
         """

custom_components/tibber_prices/services/get_price.py

@@ -1,18 +1,13 @@
 """
 Service handler for get_price service.
 
-This service provides direct access to the interval pool for testing and development
+This service fetches raw price interval data for any time range using the
-purposes. It uses intelligent caching to minimize API calls by fetching only missing
+interval pool's intelligent caching. Only intervals not already cached are
-intervals from the API.
+fetched from the Tibber API.
 
 Functions:
     handle_get_price: Service handler for fetching price data
 
-Used for:
-    - Testing interval pool caching logic
-    - Development and debugging of historical data queries
-    - Verifying gap detection and cache hit/miss behavior
-
 """
 
 from __future__ import annotations

docs/user/docs/actions.md

@@ -303,6 +303,57 @@ data:
 
 ---
 
+### tibber_prices.get_price
+
+**Purpose:** Fetches raw price interval data for any time range. Uses intelligent caching — only intervals not already cached are fetched from the Tibber API.
+
+**Parameters:**
+
+| Parameter | Description | Required |
+|-----------|-------------|----------|
+| `entry_id` | Integration entry ID | Yes |
+| `start_time` | Start of the time range | Yes |
+| `end_time` | End of the time range | Yes |
+
+**Example:**
+
+```yaml
+service: tibber_prices.get_price
+data:
+    entry_id: YOUR_CONFIG_ENTRY_ID
+    start_time: "2025-11-01T00:00:00"
+    end_time: "2025-11-02T00:00:00"
+response_variable: price_data
+```
+
+**Response Format:**
+
+```json
+{
+    "home_id": "abc-123",
+    "start_time": "2025-11-01T00:00:00+01:00",
+    "end_time": "2025-11-02T00:00:00+01:00",
+    "interval_count": 96,
+    "price_info": [
+        {
+            "startsAt": "2025-11-01T00:00:00+01:00",
+            "total": 0.2534,
+            "energy": 0.1218,
+            "tax": 0.1316
+        }
+    ]
+}
+```
+
+**Use cases:**
+- Fetching historical price data for analysis
+- Comparing prices across arbitrary date ranges
+- Building custom charts with historical data
+
+**Note:** Times are automatically converted to your Tibber home's timezone. The interval pool caches previously fetched intervals, so repeated calls for the same range are fast.
+
+---
+
 ## Migration from Chart Data Export Sensor
 
 If you're still using the `sensor.<home_name>_chart_data_export` sensor, consider migrating to the `tibber_prices.get_chartdata` action:

docs/user/docs/configuration.md

@@ -91,7 +91,7 @@ Configure the Coefficient of Variation (CV) boundaries:
 Configure detection of favorable price windows. Three collapsible sections:
 
 **Period Settings:**
-- Minimum period length (default: 30 min)
+- Minimum period length (default: 60 min)
 - Maximum price level to include (default: CHEAP)
 - Gap tolerance: how many expensive intervals to bridge (default: 1)
 
@@ -131,7 +131,7 @@ Information page for the legacy chart data export sensor. For new setups, use th
 
 ### Average Sensor Display Settings
 
-**Location:** Settings → Devices & Services → Tibber Prices → Configure → Step 6
+**Location:** Settings → Devices & Services → Tibber Prices → Configure → **General Settings**
 
 The integration allows you to choose how average price sensors display their values. This setting affects all average sensors (daily, 24h rolling, hourly smoothed, and future forecasts).
 

docs/user/docs/sensors-trends.md

@@ -176,6 +176,35 @@ A change from `rising` to `strongly_rising` (same direction) is **not** reported
 
 ---
 
+## Next Price Trend Change In (Countdown)
+
+**Entity ID:** `sensor.<home_name>_next_price_trend_change_in`
+
+A **countdown timer** companion to the Next Price Trend Change sensor above. Instead of a timestamp, it shows **how many minutes** remain until the trend changes direction.
+
+**State:** Duration in minutes until the next trend change (displayed in hours via HA unit conversion). Unavailable if no change is predicted.
+
+**Use cases:**
+- Dashboard countdown: "Trend changes in 1.5 h"
+- Automation trigger: "If trend change is less than 15 minutes away, prepare for price direction change"
+
+**Example automation:**
+
+```yaml
+trigger:
+  - platform: numeric_state
+    entity_id: sensor.<home_name>_next_price_trend_change_in
+    below: 0.25  # 15 minutes (displayed in hours)
+action:
+  - service: notify.mobile_app
+    data:
+      message: "Price trend is about to change direction!"
+```
+
+**Tip:** Use this sensor for "HOW LONG" and the Next Price Trend Change sensor (timestamp) for "WHEN".
+
+---
+
 ## How to Use Trend Sensors for Decisions
 
 :::danger Common Misconception — Don't "Wait for Stable"!

docs/user/docs/sensors-volatility.md

@@ -39,6 +39,7 @@ All volatility sensors provide these attributes:
 
 | Attribute | Description | Example |
 |---|---|---|
+| `price_volatility` | Volatility level (language-independent, always English) | `"moderate"` |
 | `price_coefficient_variation_%` | The calculated Coefficient of Variation | `23.5` |
 | `price_spread` | The difference between the highest and lowest price | `12.3` |
 | `price_min` | The lowest price in the period | `10.2` |