epistemics

Enforce evidence hierarchies and citation requirements for biomedical research claims.

Updated Nov 9, 2025
One-click install
npx skills add https://github.com/markusstrasser/skills --skill epistemics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: epistemics
Source: https://github.com/markusstrasser/skills/tree/main/epistemics
Command: npx skills add https://github.com/markusstrasser/skills --skill epistemics

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Bio/medical research often accumulates speculative claims without solid, citable evidence. Epistemics enforces a structured evidence framework to prevent hallucinations and to ensure traceable sources.

Core Features & Use Cases

  • Enforces an evidence hierarchy and mandatory citations for non-trivial claims.
  • Guides researchers through domain-specific failure modes and proper interpretation of genetic and clinical data.
  • Use Case: During a literature review of a biomarker, Epistemics ensures every claim is paired with a DOI, PMID, or official URL and clearly separates mechanistic vs clinical evidence.

Quick Start

Provide a research question and attach any available sources; Epistemics will outline citation requirements and the evidence hierarchy to govern the workflow.

Frequently Asked Questions about epistemics

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

FAQPage Schema
How do I prevent hallucinations in biomedical literature reviews?▼

To prevent hallucinations in biomedical literature reviews, use an evidence hierarchy framework that mandates citations for non-trivial claims. This ensures traceable sources and separates mechanistic from clinical evidence.

How do I enforce citation requirements for medical research claims?▼

You can enforce citation requirements for medical research claims by applying a structured evidence framework. This approach pairs every non-trivial assertion with a DOI, PMID, or official URL to maintain source traceability.

What is the best way to separate mechanistic vs clinical evidence in a meta-analysis?▼

The best way to separate mechanistic vs clinical evidence in a meta-analysis is to implement formal evidence hierarchies with explicit INFERENCE labeling. This clearly distinguishes speculative claims from validated clinical data.

Can I use an anti-hallucination guardrail for pharmacogenomics interpretation?▼

Yes, anti-hallucination guardrails can be used for pharmacogenomics interpretation. They guide researchers through domain-specific failure modes and ensure proper interpretation of genetic and clinical data.

Does biomedical evidence synthesis work without structured guardrails?▼

Biomedical evidence synthesis without structured guardrails often accumulates speculative claims without solid, citable evidence. Applying a formal evidence framework prevents hallucinations and ensures traceable sources during research.