skills/alphaear-signal-tracker/SKILL.md
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.
npx skillsauth add rkiding/awesome-finance-skills alphaear-signal-trackerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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This skill provides logic to track and update investment signals. It assesses how new market information impacts existing signals (Strengthened, Weakened, Falsified, or Unchanged).
YOU (the Agent) are the Tracker. Use the prompts in references/PROMPTS.md.
Workflow:
InvestmentSignal.Tools:
alphaear-search and alphaear-stock skills to gather the necessary data.scripts/fin_agent.py helper _sanitize_signal_output if needing to clean JSON.Key Logic:
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.
agno (Agent framework)sqlite3 (built-in)Ensure DatabaseManager is initialized correctly.
data-ai
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
development
Search A-Share/HK/US finance stock tickers and retrieve finance stock price history. Use when user asks about finance stock codes, recent price changes, or specific company finance stock info.
testing
Analyze finance text sentiment using FinBERT or LLM. Use when the user needs to determine the sentiment (positive/negative/neutral) and score of financial text markets.
development
Perform finance web searches and local context searches. Use when the user needs general finance info from the web (Jina/DDG/Baidu) or needs to retrieve finance information from a local document store (RAG).