research-graph-analysis

Analyze research claim graphs for structural integrity and trustworthiness.

Updated Jun 6, 2026

Search Tags:#decision support #research integrity #evidence evaluation #research analysis #claim graph

Ready to run

npx skills add https://github.com/kenziecreative/kenzie-creative --skill research-graph-analysis

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-graph-analysis
Source: https://github.com/kenziecreative/kenzie-creative/tree/main/researcher/skills/research-graph-analysis
Command: npx skills add https://github.com/kenziecreative/kenzie-creative --skill research-graph-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps users assess the trustworthiness and strength of research by analyzing the structure of the research graph, identifying load-bearing claims, fragile foundations, and opportunities for confidence upgrades.

Core Features & Use Cases

Graph Analysis: Analyzes the research graph to determine the strength of evidence supporting claims.
Claim Evaluation: Identifies claims that are well-supported, thinly supported, or in need of additional evidence.
Decision Support: Provides insights into where targeted follow-up would have the biggest impact on the research's overall reliability.
Use Case: When a user has a research document with a claim graph, they can use this Skill to understand the structural health of the evidence base, identify areas of concern, and make informed decisions about the research's reliability.

Quick Start

Run the research-graph-analysis skill on your research document to get an analysis of the evidence base's structure and trustworthiness.

Frequently Asked Questions about research-graph-analysis

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

FAQPage Schema

How do I evaluate the trustworthiness of a research graph's evidence base?▼

Research graph analysis evaluates structural integrity by identifying load-bearing claims and fragile foundations within the evidence. It reveals whether core claims are well-supported or thinly supported, directly indicating the research findings' overall reliability and trustworthiness.

What is a load-bearing claim in research analysis?▼

A load-bearing claim is a foundational structural node in research analysis that the broader evidence base relies upon. Identifying these claims is critical because if they are thinly supported, the structural integrity and trustworthiness of the entire research finding are compromised.

How do I identify fragile foundations in a structured claim graph?▼

You identify fragile foundations in a claim graph by analyzing the structural support for each node to find thinly supported claims. This research analysis highlights areas where targeted follow-up evidence is needed to prevent structural failure in the research documentation.

Can I use research graph analysis for decision support?▼

Yes, you can use research graph analysis for decision support. It provides insights into where targeted follow-up evidence would have the biggest impact on overall reliability, helping you make informed decisions about the trustworthiness of research findings.

When do I need to analyze evidence strength in research documentation?▼

You need to analyze evidence strength in research documentation when you must assess the structural integrity of structured claim graphs. This is essential before relying on the findings for decision support, ensuring that load-bearing claims have adequate support and trustworthiness.