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.