---
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.