Agent Skillsninehills/skills › alphaear-signal-tracker

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。

alphaear-signal-tracker/SKILL.md ninehills/skills

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
More Options

Non-standard path

npx skills add https://github.com/ninehills/skills/tree/main/alphaear-signal-tracker -g -y

Use without installing

npx skills use ninehills/skills@alphaear-signal-tracker

指定 Agent (Claude Code)

npx skills add ninehills/skills --skill alphaear-signal-tracker -a claude-code -g -y

安装 repo 全部 skill

npx skills add ninehills/skills --all -g -y

预览 repo 内 skill

npx skills add ninehills/skills --list

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:

  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.

Version History

  • f3e82a7 Current 2026-07-25 11:12

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Metadata

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Version
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Hash
f049b077
Indexed
2026-07-25 11:12

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