AlphaEar News Skill

## Overview

25 stars

Best use case

AlphaEar News Skill is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

## Overview

Teams using AlphaEar News Skill should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/alphaear-news/SKILL.md --create-dirs "https://raw.githubusercontent.com/ComeOnOliver/skillshub/main/skills/RKiding/Awesome-finance-skills/alphaear-news/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/alphaear-news/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How AlphaEar News Skill Compares

Feature / Agent	AlphaEar News Skill	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

## Overview

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# AlphaEar News Skill

## Overview

Fetch real-time hot news, generate unified trend reports, and retrieve Polymarket prediction data.

## Capabilities

### 1. Fetch Hot News & Trends

Use `scripts/news_tools.py` via `NewsNowTools`.

-   **Fetch News**: `fetch_hot_news(source_id, count)`
    -   See [sources.md](references/sources.md) for valid `source_id`s (e.g., `cls`, `weibo`).
-   **Unified Report**: `get_unified_trends(sources)`
    -   Aggregates top news from multiple sources.

### 2. Fetch Prediction Markets

Use `scripts/news_tools.py` via `PolymarketTools`.

-   **Market Summary**: `get_market_summary(limit)`
    -   Returns a formatted report of active prediction markets.

## Dependencies

-   `requests`, `loguru`
-   `scripts/database_manager.py` (Local DB)

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