trade-hypothesis-ideator

Generate ranked falsifiable trade hypotheses with experiment designs and kill criteria.

Updated Mar 25, 2026
One-click install
npx skills add https://github.com/MileniumTick/skills --skill trade-hypothesis-ideator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: trade-hypothesis-ideator
Source: https://github.com/MileniumTick/skills/tree/main/skills/trade-hypothesis-ideator
Command: npx skills add https://github.com/MileniumTick/skills --skill trade-hypothesis-ideator

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Generate falsifiable trade hypotheses from structured inputs, returning ranked hypothesis cards with experiment designs and kill criteria, and optional strategy exports compatible with edge-finder-candidate/v1.

Core Features & Use Cases

  • Generate 1-5 hypothesis cards from a normalized input bundle.
  • Rank hypotheses with guardrails and provide actionable next steps.
  • Optionally export qualifying hypotheses into strategy.yaml and metadata.json artifacts for edge-finder-candidate/v1.

Quick Start

Provide a normalized input bundle as JSON to generate and rank hypotheses, and optionally export strategies.

Frequently Asked Questions about trade-hypothesis-ideator

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

FAQPage Schema
How do I generate testable trade hypotheses from market data?

Generate falsifiable trade hypotheses by submitting a normalized JSON input bundle, which produces 1-5 ranked hypothesis cards complete with experiment designs and kill criteria.

What is a falsifiable trade hypothesis and how does backtesting use it?

A falsifiable trade hypothesis is a structured market assumption paired with specific kill criteria, enabling rigorous backtesting validation and risk management before capital deployment.

How do I export trading strategies to edge-finder-candidate format?

Export qualifying hypotheses into strategy.yaml and metadata.json artifacts compatible with edge-finder-candidate/v1 by enabling the optional export feature during the trade hypothesis generation process.

Do I need a specific data format to generate trade hypothesis cards?

Yes, you must provide a normalized input bundle formatted as JSON to successfully generate, rank, and evaluate trade hypothesis cards with computed priority scores and experiment designs.

How are generated trade hypotheses ranked by priority?

Trade hypotheses are evaluated and ranked by a computed priority score incorporating guardrails, presenting the most actionable trading edges first as structured cards for immediate evaluation.

Can I use this for risk management and edge-finding in trading?

Yes, it identifies testable trade edges and defines explicit kill criteria for each generated hypothesis, directly supporting systematic risk management and edge-finding workflows.