hypothesis-triangulator

Validate hypotheses by cross-referencing Git, documentation, and code sources.

3|Updated Apr 3, 2026
One-click install
npx skills add https://github.com/ForgePlan/marketplace --skill hypothesis-triangulator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: hypothesis-triangulator
Source: https://github.com/ForgePlan/marketplace/tree/main/plugins/forgeplan-brownfield-pack/skills/hypothesis-triangulator
Command: npx skills add https://github.com/ForgePlan/marketplace --skill hypothesis-triangulator

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the validation of hypotheses against multiple independent sources, assigning confidence scores to improve decision-making.

Core Features & Use Cases

  • Hypothesis Validation: Validates hypotheses against Git history, legacy docs, code comments, naming patterns, test evidence, and domain owner interviews.
  • Confidence Scoring: Assigns confidence scores to hypotheses based on evidence from various sources.
  • Use Case: Utilize this Skill to validate a hypothesis like "The duration=5 hardcoded for LO stevedores is a placeholder awaiting domain owner value." It will analyze the code, documentation, and other relevant sources to determine the confidence in the hypothesis.

Quick Start

Run the hypothesis-triangulator skill with the command: extract hypothesis triangulator

Frequently Asked Questions about hypothesis-triangulator

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

FAQPage Schema
How do I validate code hypotheses against Git history and documentation automatically?

You can validate code hypotheses by cross-referencing them against Git history, legacy docs, code comments, and test evidence to assign a confidence score for your decision-making workflow.

What is hypothesis triangulation in software engineering?

Hypothesis triangulation is the process of validating assumptions by cross-referencing multiple independent sources like Git history, documentation, and domain owner interviews to assign a confidence score.

Can I use confidence scoring for hardcoded values found during code review?

Yes, confidence scoring evaluates hardcoded values by analyzing code, documentation, and naming patterns to determine if they are placeholders awaiting domain owner input.

Do I need Git repository access to automate hypothesis validation?

Yes, you need Git repository access because the validation process cross-references Git history alongside documentation and domain knowledge to generate accurate confidence scores.

What is the best way to score confidence in legacy code assumptions?

The best way to score confidence in legacy code assumptions is to cross-reference Git analysis, legacy docs, and domain owner interviews to systematically validate the hypothesis.

When should I not use automated hypothesis validation for decision support?

You should avoid automated hypothesis validation when you lack access to Git repositories or domain knowledge, as confidence scoring requires cross-referencing multiple independent sources.