Agent Skills
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alphaear-signal-tracker
GitHub追踪金融投资信号演化,基于新市场信息评估并更新信号状态(增强、减弱、证伪或不变)。结合研究与分析提示词,对比新旧信息以调整置信度与强度。
Trigger Scenarios
监控金融市场动态
评估现有投资信号有效性
根据新闻或价格变动更新持仓建议
Install
npx skills add ninehills/skills --skill alphaear-signal-tracker -g -y
SKILL.md
Frontmatter
{
"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:
- 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.
Version History
- f3e82a7 Current 2026-07-25 11:12


