counterfactual-reasoning

Name: counterfactual-reasoning
Availability: InStock
Author: yipng05-max

Decompose research conclusions and enumerate competing explanations for validity threats.

265|23|Updated Feb 7, 2026

Search Tags:#literature review #causal inference #research design #counterfactual reasoning #reviewer simulation #validity threats

Ready to run

npx skills add https://github.com/yipng05-max/-skills --skill counterfactual-reasoning-yipng05-max

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: counterfactual-reasoning
Source: https://github.com/yipng05-max/-skills/tree/main/counterfactual-reasoning
Command: npx skills add https://github.com/yipng05-max/-skills --skill counterfactual-reasoning-yipng05-max

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps researchers systematically challenge their own research conclusion by enumerating competing explanations, checking common validity threats, and clarifying the boundary conditions under which the claim holds.

Core Features & Use Cases

Conclusion decomposition: Breaks the user’s claim into core assertions, causal/interpretive direction, mechanism, scope, and evidence-to-claim inference gap.
Competing explanations coverage: Enumerates and evaluates threats from confounding variables, reverse causation, selection bias, observer effects, and alternative mechanisms.
Boundary and reviewer simulation: Tests representativeness, time robustness, and contextual transferability, then simulates multiple reviewer perspectives and produces revision guidance.

Quick Start

Use the counterfactual-reasoning skill to pressure-test your conclusion by providing your core claim, key evidence, optional study design, and target journal.

Frequently Asked Questions about counterfactual-reasoning

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

FAQPage Schema

How do I stress-test research conclusions for causal inference validity threats?▼

To stress-test research conclusions for causal inference, provide your core claim, key evidence, and optional study design. The skill decomposes the causal structure, enumerates competing explanations, and outputs simulated reviewer critiques with actionable revision recommendations.

How do I identify competing explanations and selection bias in my research design?▼

Identifying competing explanations and selection bias requires systematically evaluating threats from confounding variables, reverse causation, and observer effects. The skill breaks down your claim's interpretive direction and mechanism to evaluate alternative explanations against your evidence.

Can I use counterfactual reasoning to simulate reviewer critiques before journal submission?▼

Yes, you can simulate reviewer critiques before journal submission by inputting your target journal alongside your claim and evidence. It generates multiple reviewer perspectives, testing generalizability challenges and contextual transferability.

What is the best way to check boundary conditions and generalizability of academic claims?▼

The best way to check boundary conditions and generalizability of academic claims is to test representativeness, time robustness, and contextual transferability. The skill validates the scope of your claim and clarifies the specific conditions under which it holds.

Does this approach work for qualitative research conclusions or only quantitative causal claims?▼

This approach works for both qualitative and quantitative academic claims requiring pre-submission defenses against reviewer objections. It decomposes the interpretive structure and evidence-to-claim inference gap regardless of the research methodology used.