Alphaear signal tracker
Skill RKiding/Awesome-finance-skills/skills/alphaear-signal-tracker
A collection of Awesome Finance Agent Skills for free and easy to start | 一系列开源免费的金融分析Agent Skills
npx -y skills add RKiding/Awesome-finance-skills --skill alphaear-signal-trackerAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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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.
SKILL.md
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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:
- Research: Use FinResearcher Prompt to gather facts/price for a signal.
- Analyze: Use FinAnalyst Prompt to generate the initial
InvestmentSignal. - Track: For existing signals, use Signal Tracking Prompt to assess evolution (Strengthened/Weakened/Falsified) based on new info.
Tools:
- Use
alphaear-searchandalphaear-stockskills to gather the necessary data. - Use
scripts/fin_agent.pyhelper_sanitize_signal_outputif needing to clean JSON.
Key Logic:
- Input: Existing Signal State + New Information (News/Price).
- Process:
- Compare new info with signal thesis.
- Determine impact direction (Positive/Negative/Neutral).
- 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.