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Alphaear Predictor

ASecurity

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

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  • Added September 12, 2026
ai-agentspythonrustgogitdatabasesecurity

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Scanned September 12, 2026

npx -y skills add thedixitjain/the-mega-skill-library --skill alphaear-predictor --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: alphaear-predictor
description: "Market prediction skill using Kronos. Use when user needs finance market time-series forecasting or news-aware finance market adjustments."
category: data-science-and-ml
source_repo: RKiding/Awesome-finance-skills
source_path: "skills/alphaear-predictor/SKILL.md"
source_url: https://github.com/RKiding/Awesome-finance-skills/blob/HEAD/skills/alphaear-predictor/SKILL.md
---


# 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

### 1. Forecast Market Trends

**Workflow:**
1.  **Generate Base Forecast**: Use `scripts/kronos_predictor.py` (via `KronosPredictorUtility`) to generate the technical/quantitative forecast.
2.  **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):**

```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.

1.  **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).

> [!CAUTION]
> **Model Security**: This skill loads model weights from `exports/models`. We use `weights_only=True` and only scan for the `kronos_news_*.pt` pattern. Ensure you only place trusted checkpoints in this directory.

2.  **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`

---

**Source:** [`RKiding/Awesome-finance-skills`](https://github.com/RKiding/Awesome-finance-skills) → `skills/alphaear-predictor/SKILL.md`

Files in this skill

  • SKILL.md2.4 KB
  • references/PROMPTS.md1 KB
  • scripts/forecast_agent.py2.9 KB
  • scripts/json_utils.py6.2 KB
  • scripts/kronos_predictor.py7.6 KB
  • scripts/predictor/model/__init__.py394 B
  • scripts/predictor/model/kronos.py30.4 KB
  • scripts/predictor/model/module.py22.3 KB
  • scripts/prompts/fin_agent.py6.6 KB
  • scripts/prompts/forecast_analyst.py1.9 KB
  • scripts/prompts/intent_agent.py2.2 KB
  • scripts/prompts/isq_prompt_generator.py1.8 KB
  • scripts/prompts/report_agent.py18.1 KB
  • scripts/prompts/trend_agent.py7.4 KB
  • scripts/prompts/visualizer.py2 KB
  • scripts/schema/isq_template.py13.6 KB
  • scripts/schema/models.py6.1 KB
  • scripts/utils/__init__.py25 B
  • scripts/utils/database_manager.py21.3 KB

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