Does this require manual operation?

No, it is designed to run as a background service or a continuous loop for 24/7 autonomous market surveillance without user intervention.

What is the Stirrup framework?

Stirrup is a framework developed by Artificial Analysis that enables autonomous agents to perform complex market research, web searching, and tool execution.

Can I use different LLM models for scanning?

Yes, the scanner supports various models including Claude 3.5 Sonnet, Claude Haiku, and DeepSeek-Chat via OpenRouter to balance cost and analysis depth.

Does it include real-time news analysis?

Yes, it includes tools for web searching and fetching latest news and sentiment data to inform its signal generation logic.

How does the scanner output its findings?

It generates UDM-validated JSON signals saved to a local directory, which can be programmatically consumed by other trading execution scripts.

Stirrup Market Scanner

Name: Stirrup Market Scanner
Author: IgorGanapolsky

byIgorGanapolsky

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Data Science & ML

Monitors financial markets autonomously to generate AI-driven trading signals using multi-agent consensus and the Stirrup framework.

About

Stirrup Market Scanner is an autonomous agent designed for continuous market surveillance and high-accuracy signal generation. By leveraging the Stirrup framework and multi-agent LLM consensus, it provides 24/7 background monitoring across multiple symbols, ranging from quick headline checks to deep-dive pre-trade research. This skill integrates seamlessly with automated trading systems by outputting UDM-validated signals in JSON format, allowing users to identify opportunities and maintain market awareness even when their primary coding session is idle.

Key Features

Tiered scan modes (Quick, Standard, Deep) for varying analysis depth
4 GitHub stars
Multi-symbol parallel scanning for stocks, crypto, and ETFs
Multi-agent LLM consensus for high-accuracy signal validation
24/7 autonomous market monitoring and background research
Direct integration with trading systems via UDM-validated signal output

Use Cases

Automating sentiment analysis and news monitoring across diverse financial assets
Running background research agents to identify trade opportunities while the main system is idle
Generating validated trading signals for automated execution or manual review

About

Key Features

Tiered scan modes (Quick, Standard, Deep) for varying analysis depth
4 GitHub stars
Multi-symbol parallel scanning for stocks, crypto, and ETFs
Multi-agent LLM consensus for high-accuracy signal validation
24/7 autonomous market monitoring and background research
Direct integration with trading systems via UDM-validated signal output

Use Cases

Automating sentiment analysis and news monitoring across diverse financial assets
Running background research agents to identify trade opportunities while the main system is idle
Generating validated trading signals for automated execution or manual review