AlphaEar Predictor Skill

alphaear-predictor

Market prediction skill using Kronos. Use when user needs finance market time-series forecasting or news-aware finance market adjustments.

majiayu000/claude-skill-registry·0installs663starsFinance & Trading

SKILL.md

Full skill instructions

AlphaEar Predictor Skill

Overview

This skill utilizes the Kronos model (via KronosPredictorUtility) to perform time-series forecasting and adjust predictions based on news sentiment.

Capabilities

1. Forecast Market Trends

Workflow:

Generate Base Forecast: Use scripts/kronos_predictor.py (via KronosPredictorUtility) to generate the technical/quantitative forecast.
Adjust Forecast (Agentic): Use the Forecast Adjustment Prompt in references/PROMPTS.md to subjectively adjust the numbers based on latest news/logic.

Key Tools:

KronosPredictorUtility.get_base_forecast(df, lookback, pred_len, news_text): Returns List[KLinePoint].

Example Usage (Python):

from scripts.utils.kronos_predictor import KronosPredictorUtility
from scripts.utils.database_manager import DatabaseManager

db = DatabaseManager()
predictor = KronosPredictorUtility()

# Forecast
forecast = predictor.predict("600519", horizon="7d")
print(forecast)

Configuration

This skill requires the Kronos model and an embedding model.

Kronos Model:
- Ensure exports/models directory exists in the project root.
- Place trained news projector weights (e.g., kronos_news_v1.pt) in exports/models/.
- Or depend on the base model (automatically downloaded).
Environment Variables:
- EMBEDDING_MODEL: Path or name of the embedding model (default: sentence-transformers/all-MiniLM-L6-v2).
- KRONOS_MODEL_PATH: Optional path to override model loading.

Dependencies

torch
transformers
sentence-transformers
pandas
numpy
scikit-learn

Install skill

Copy and run in your terminal

npx -y skills add https://github.com/majiayu000/claude-skill-registry --skill alphaear-predictor

View on GitHub

skills/data/alphaear-predictor/SKILL.md

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