alphaear-signal-tracker Checked

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

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):**

# 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.