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rkiding/awesome-finance-skills551 installs

alphaear-signal-tracker

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.

How do I install this agent skill?

npx skills add https://github.com/rkiding/awesome-finance-skills --skill alphaear-signal-tracker
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubwarn

    The skill tracks financial investment signals and generates reports. It contains security risks including the execution of shell commands for report timestamps and dynamic code execution patterns in its machine learning components. It also processes external web content, which presents an indirect prompt injection surface.

  • Socketwarn

    1 alert: gptAnomaly

  • Snykwarn

    Risk: MEDIUM · 1 issue

  • Runlayerfail

    10/35 files flagged

What does this agent skill do?

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.

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/rkiding/awesome-finance-skills/alphaear-signal-tracker">View alphaear-signal-tracker on skillZs</a>