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IhsanDanish25
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edge-candidate-agent

Convert EOD market observations into research tickets and candidate specs.

2|Updated Jun 14, 2026
Search Tags:#market analysis#data transformation#trading strategy#edge detection#research ticket
One-click install
npx skills add https://github.com/IhsanDanish25/claude-trading-skills --skill edge-candidate-agent-ihsandanish25
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: edge-candidate-agent
Source: https://github.com/IhsanDanish25/claude-trading-skills/tree/main/skills/edge-candidate-agent
Command: npx skills add https://github.com/IhsanDanish25/claude-trading-skills --skill edge-candidate-agent-ihsandanish25

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyYAML, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill transforms daily market observations into reproducible research tickets and exportable candidate specs for trading strategy development.

Core Features & Use Cases

  • Edge Research Ticket Generation: Converts market observations into structured research tickets.
  • Candidate Spec Export: Converts validated tickets into strategy specs and metadata for Phase I of the trading strategy pipeline.
  • Use Case: For traders who need to identify potential trading opportunities based on market data and ensure compatibility with the trading strategy pipeline.

Quick Start

Run the edge-candidate-agent skill with the auto-detection script, providing the path to the OHLCV data and desired output directory.

Frequently Asked Questions about edge-candidate-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert EOD market observations into structured research tickets for trading strategy development?▼

The edge-candidate-agent processes EOD market observations to generate reproducible research tickets and exportable candidate specs, making it ideal for structuring market analysis into actionable trading strategy development tasks.

Can I export candidate specs directly into a trading strategy pipeline?▼

Yes, the edge-candidate-agent converts validated research tickets into strategy specs and metadata formatted for Phase I of a trading strategy pipeline, ensuring seamless downstream integration.

What Python version and dependencies do I need to run edge research ticket generation?▼

You need Python 3.9 or higher and the PyYAML library installed to run the edge research ticket generation script and access the trading strategy pipeline.

Does the edge-candidate-agent workflow support integration with external LLM ideation?▼

Yes, the edge-candidate-agent workflow supports integration with external LLM ideation to enhance market analysis and improve the quality of generated edge research tickets.

What's the best way to structure market analysis data before generating trading strategy candidate specs?▼

Provide a path to your OHLCV data and a desired output directory when running the auto-detection script, allowing the Skill to transform raw EOD market observations into structured candidate specs.

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