MedOrqis: Zero-Token Deterministic Medical AI Skills • Evidence-Grounded Decision Support
Home Playground Skills Library Model Comparison Documentation
24 Skills Zero-Token Core 100% Verified
Class A (IEC 62304 / MDR) Tier 1 v2.1.0

ebm-research-biostatistics

Evidence-Based Medicine & Public Health

Intended Clinical Purpose

Appraises clinical study designs, computes biostatistical parameters (OR, RR, NNT), and assigns GRADE certainty.

Prohibited Clinical Uses & Gating Boundary

Fabricating citations or clinical trial results
Direct clinical care without clinician review

Mandatory Input Parameters

study_abstract_or_claim study_type

Deterministic Dependencies

core.citation_validator core.claim_entailment_verifier
Clinical Review Status: REFERENCE_SEED_REQUIRES_CLINICAL_SIGN_OFF

Claude Code & MCP Configuration

Add to Claude Code via MCP stdio:

$ claude mcp add ebm-research-biostatistics npx medorqis --skill=ebm-research-biostatistics

Skills CLI Execution

Dispatch directly to agent workspace:

$ npx skills run seotarek/MedOrqis/ebm-research-biostatistics
SKILL.md & Manifest Specification YAML Frontmatter
---
name: ebm-research-biostatistics
description: >-
  Evidence-Based Medicine (EBM) research assistant. Formulates PICO questions, conducts CASP and RoB-2 critical appraisals, evaluates GRADE evidence certainty, and interprets biostatistical metrics.
allowed-tools: bash
license: Apache-2.0
compatibility: Linux, macOS, Windows (Python 3.10+, MCP stdio, Claude Code, Gemini CLI, OpenAI)
metadata:
  ...
Copied to clipboard!