Import 9 alphaear finance skills

- alphaear-deepear-lite: DeepEar Lite API integration
- alphaear-logic-visualizer: Draw.io XML finance diagrams
- alphaear-news: Real-time finance news (10+ sources)
- alphaear-predictor: Kronos time-series forecasting
- alphaear-reporter: Professional financial reports
- alphaear-search: Web search + local RAG
- alphaear-sentiment: FinBERT/LLM sentiment analysis
- alphaear-signal-tracker: Signal evolution tracking
- alphaear-stock: A-Share/HK/US stock data

Updates:
- All scripts updated to use universal .env path
- Added JINA_API_KEY, LLM_*, DEEPSEEK_API_KEY to .env.example
- Updated load_dotenv() to use ~/.config/opencode/.env

skills/alphaear-predictor/scripts/utils/llm/router.py

@@ -0,0 +1,81 @@
+import os
+from typing import Optional, List, Dict, Any, Union
+from agno.models.base import Model
+from loguru import logger
+from dotenv import load_dotenv
+from ..llm.factory import get_model
+from ..llm.capability import ModelCapabilityRegistry
+
+# Load environment variables from universal .env
+load_dotenv(os.path.expanduser("~/.config/opencode/.env"))
+
+
+class ModelRouter:
+    """
+    模型路由管理器
+
+    功能：
+    1. 管理“推理/写作模型” (Reasoning Model) 和“工具调用模型” (Tool Model)。
+    2. 根据任务需求自动选择合适的模型。
+    """
+
+    def __init__(self):
+        # 默认从环境变量读取
+        self.reasoning_provider = os.getenv(
+            "REASONING_MODEL_PROVIDER", os.getenv("LLM_PROVIDER", "openai")
+        )
+        self.reasoning_id = os.getenv(
+            "REASONING_MODEL_ID", os.getenv("LLM_MODEL", "gpt-4o")
+        )
+        self.reasoning_host = os.getenv("REASONING_MODEL_HOST", os.getenv("LLM_HOST"))
+
+        self.tool_provider = os.getenv("TOOL_MODEL_PROVIDER", self.reasoning_provider)
+        self.tool_id = os.getenv("TOOL_MODEL_ID", self.reasoning_id)
+        self.tool_host = os.getenv("TOOL_MODEL_HOST", self.reasoning_host)
+
+        self._reasoning_model = None
+        self._tool_model = None
+
+        logger.info(
+            f"🤖 ModelRouter initialized: Reasoning={self.reasoning_id} ({self.reasoning_host or 'default'}), Tool={self.tool_id} ({self.tool_host or 'default'})"
+        )
+
+    def get_reasoning_model(self, **kwargs) -> Model:
+        if not self._reasoning_model:
+            # 优先使用路由配置的 host
+            if self.reasoning_host and "host" not in kwargs:
+                kwargs["host"] = self.reasoning_host
+            self._reasoning_model = get_model(
+                self.reasoning_provider, self.reasoning_id, **kwargs
+            )
+        return self._reasoning_model
+
+    def get_tool_model(self, **kwargs) -> Model:
+        if not self._tool_model:
+            # 优先使用路由配置的 host
+            if self.tool_host and "host" not in kwargs:
+                kwargs["host"] = self.tool_host
+
+            # 检查 tool_model 是否真的支持 tool call
+            caps = ModelCapabilityRegistry.get_capabilities(
+                self.tool_provider, self.tool_id, **kwargs
+            )
+            if not caps["supports_tool_call"]:
+                logger.warning(
+                    f"⚠️ Configured tool model {self.tool_id} might not support native tool calls! Consider using ReAct mode or a different model."
+                )
+
+            self._tool_model = get_model(self.tool_provider, self.tool_id, **kwargs)
+        return self._tool_model
+
+    def get_model_for_agent(self, has_tools: bool = False, **kwargs) -> Model:
+        """
+        根据 Agent 是否包含工具来返回合适的模型。
+        """
+        if has_tools:
+            return self.get_tool_model(**kwargs)
+        return self.get_reasoning_model(**kwargs)
+
+
+# 全局单例
+router = ModelRouter()