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-signal-tracker/SKILL.md

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+---
+name: alphaear-signal-tracker
+description: Track finance investment signal evolution and update logic based on new finance market information. Use when monitoring finance signals and determining if they are strengthened, weakened, or falsified.
+---
+
+# AlphaEar Signal Tracker Skill
+
+## Overview
+
+This skill provides logic to track and update investment signals. It assesses how new market information impacts existing signals (Strengthened, Weakened, Falsified, or Unchanged).
+
+## Capabilities
+
+### 1. Track Signal Evolution
+
+### 1. Track Signal Evolution (Agentic Workflow)
+
+**YOU (the Agent)** are the Tracker. Use the prompts in `references/PROMPTS.md`.
+
+**Workflow:**
+1.  **Research**: Use **FinResearcher Prompt** to gather facts/price for a signal.
+2.  **Analyze**: Use **FinAnalyst Prompt** to generate the initial `InvestmentSignal`.
+3.  **Track**: For existing signals, use **Signal Tracking Prompt** to assess evolution (Strengthened/Weakened/Falsified) based on new info.
+
+**Tools:**
+- Use `alphaear-search` and `alphaear-stock` skills to gather the necessary data.
+- Use `scripts/fin_agent.py` helper `_sanitize_signal_output` if needing to clean JSON.
+
+**Key Logic:**
+
+-   **Input**: Existing Signal State + New Information (News/Price).
+-   **Process**:
+    1.  Compare new info with signal thesis.
+    2.  Determine impact direction (Positive/Negative/Neutral).
+    3.  Update confidence and intensity.
+-   **Output**: Updated Signal.
+
+**Example Usage (Conceptual):**
+
+```python
+# This skill is currently a pattern extracted from FinAgent.
+# In a future refactor, it should be a standalone utility class.
+# For now, refer to `scripts/fin_agent.py`'s `track_signal` method implementation.
+```
+
+## Dependencies
+
+-   `agno` (Agent framework)
+-   `sqlite3` (built-in)
+
+Ensure `DatabaseManager` is initialized correctly.