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investment-analysis

Validate investment theses and detect biases with structured analysis workflows.

Updated Nov 3, 2025
Search Tags:#investment analysis#structured analysis#thesis validation#decision workflow#divestment analysis
One-click install
npx skills add https://github.com/ethicalcapital/skills --skill investment-analysis-ethicalcapital
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: investment-analysis
Source: https://github.com/ethicalcapital/skills/tree/main/investment-analysis
Command: npx skills add https://github.com/ethicalcapital/skills --skill investment-analysis-ethicalcapital

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides structured, auditable workflows for investment analysis, ensuring the validation of theses, detection of biases, testing of assumptions, and creating defensible decision trails.

Core Features & Use Cases

  • Structured Analysis Framework: Offers a systematic approach to investment analysis, with defined steps for problem statement, assumptions, evidence, bias detection, and more.
  • Automated Workflow Generation: Generates structured output that can be audited and used for decision-making.
  • Use Case: Use this Skill to validate an investment thesis by breaking it down into testable components and assessing its robustness against various scenarios.

Quick Start

Run the investment-analysis skill to begin a new investment thesis validation.

Frequently Asked Questions about investment-analysis

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

FAQPage Schema
How do I validate an investment thesis using structured analysis?▼

Investment thesis validation breaks down your core assumptions into testable components, assesses their robustness against various scenarios, and detects biases to ensure a defensible analytical decision trail.

What is the best way to perform divestment analysis with Python?▼

Divestment analysis with Python leverages pandas, numpy, and scipy to structure problem statements, test assumptions, and generate auditable analytical workflows for complex asset decisions.

How does bias detection work in investment decision workflows?▼

Bias detection in investment decision workflows systematically evaluates evidence and assumptions within a structured framework, flagging cognitive biases to create defensible, auditable analytical trails.

Do I need pandas and scipy to run structured investment analysis?▼

Yes, structured investment analysis requires Python libraries like pandas, numpy, and scipy for data processing, scenario testing, and generating auditable output for thesis validation.

Can I use this framework for impact assessment and complex analytical decisions?▼

Yes, the structured analysis framework supports impact assessment and complex analytical decisions by defining steps for problem statements, assumptions, evidence gathering, and bias detection.

When should I not use a structured analysis workflow for investment decisions?▼

Structured investment analysis workflows are less suited for rapid, high-frequency trading decisions requiring instantaneous execution, as they prioritize auditable thesis validation, scenario testing, and comprehensive bias detection over speed.

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