theory

Test stock theses with falsification-driven analysis across six analytical lenses.

1|Updated Apr 21, 2026
One-click install
npx skills add https://github.com/y0n1n1/financial-skills --skill theory
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: theory
Source: https://github.com/y0n1n1/financial-skills/tree/main/theory
Command: npx skills add https://github.com/y0n1n1/financial-skills --skill theory

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables structured, falsification-driven testing of stock theses across a full spectrum of analytical lenses and regime contexts, converting intuition into testable, evidence-based verdicts.

Core Features & Use Cases

  • Six analytical lenses (fundamental, technical, competitive moat, macro-sector, sentiment, contrarian-check) plus a structured ACH (analysis of competing hypotheses) framework.
  • A phased workflow including base-rate anchoring, historical analogues, monetization mapping, market mechanics, pre-mortem, reflexivity, and attention allocation to surface risk and decision points.
  • Output artifacts such as the ACH matrix, Bayesian posterior chain, expected-value calculations, and a final theory verdict suitable for updating theory cards.

Quick Start

Run a full theory analysis by invoking the NVDA example with /theory NVDA to activate the end-to-end evaluation.

Frequently Asked Questions about theory

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

FAQPage Schema
How do I falsify a stock thesis using competing hypotheses?

To falsify a stock thesis, this Skill applies an Analysis of Competing Hypotheses (ACH) matrix across six analytical lenses, converting intuition into an evidence-based verdict. It systematically tests your core narrative against alternative explanations to identify structural flaws.

How does Bayesian updating work for stock risk analysis?

Bayesian updating for stock risk analysis works by anchoring on historical base rates and then adjusting the probability of your thesis using new evidence. This Skill outputs a Bayesian posterior chain to show exactly how each data point shifts your thesis probability.

Can I run a macro-driven stock analysis on technology monopolies?

Yes, you can run a macro-driven stock analysis on technology monopolies. The framework explicitly evaluates growth narratives and hardware/software ecosystems by applying macro-sector and competitive moat lenses to determine if the monopoly thesis holds under different regime contexts.

What is the best way to calculate expected value for a stock thesis?

The best way to calculate expected value for a stock thesis is to combine pre-mortem risk analysis with Bayesian probability outputs. This Skill generates EV calculations by weighting potential upside and downside scenarios identified through its six analytical lenses.

Does this stock theory analysis framework require external market data feeds?

No external market data feeds are required as dependencies. The stock theory analysis framework operates by structuring your existing thesis inputs through its analytical lenses and ACH matrix to generate a final theory verdict without needing automated API integrations.