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Cover image for MedOrqis: An Open-Source Medical AI Skills Ecosystem for Clinical Agents
Tarek Mohamed
Tarek Mohamed

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MedOrqis: An Open-Source Medical AI Skills Ecosystem for Clinical Agents

#python #ai #healthcare #opensource

Deploying Large Language Models in healthcare and clinical decision support comes with immense challenges: hallucinations, calculation errors, lack of deterministic guardrails, and non-reproducible outputs.

To address this, I built MedOrqis: an open-source medical AI skills ecosystem designed specifically for clinical AI assistants and autonomous medical agents.

GitHub logo seotarek / MedOrqis

MedOrqis — Medical AI Skills Ecosystem: 24 Specialized Clinical AI Skills, Deterministic Safety Guardrails & Zero-Token Calculators

MedOrqis — Medical AI Skills Ecosystem (v2.1.1)

Live Interactive Catalog Skills CLI npm version Verification: 36/36 Passed (100%) GitHub CI License: Apache-2.0

MedOrqis is an open-source, evidence-grounded, cross-platform ecosystem of 24 specialized clinical AI skills, 12 deterministic zero-token clinical calculators & safety engines, and multi-platform adapters (Skills CLI, Claude Code, Gemini CLI, Model Context Protocol, and OpenAI).

Tip

🌐 Interactive Web Hub & Live Zero-Token Calculators:
Explore the live searchable 24-skill catalog, test interactive clinical calculators (ESC 2024 CHA₂DS₂-VA, CKD-EPI 2021, Bedside Schwartz, HAS-BLED, NEWS2, DDI Checker), and inspect dialect benchmarks directly in your browser at https://seotarek.github.io/MedOrqis/.

⚡ Fleet Install in 1-Second (Claude Code, Cursor, Codex, Antigravity, OpenCode):

npx skills add seotarek/MedOrqis
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Built with an evidence-first, patient-safety-first architecture, MedOrqis eliminates medical hallucination risks in high-stakes clinical calculations by executing arithmetic, unit conversions, PHI scrubbing, negation parsing, and drug interaction screenings through a local, deterministic Python core with zero LLM API token overhead.

⚡ 1-Minute Quick Start & Integration

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View on GitHub

🏥 What is MedOrqis?

MedOrqis is a modular library of 24 specialized clinical skills combined with hard mathematical guardrails:

  1. Zero-Token Clinical Calculators: Medical calculations (eGFR, Child-Pugh, CHA2DS2-VASc, MELD, Apache II) must never rely on LLM arithmetic. MedOrqis runs these calculations deterministically in pure Python/C.
  2. Clinical Safety Guardrails: Strict validation filters preventing unverified drug-drug interaction outputs, dosage oversights, and contraindications.
  3. Structured Clinical Schemata: FHIR and HL7 compatible output formatting for seamless electronic health record (EHR) integration.

🔬 Core Capabilities

  • Diagnostic Differential Assister: Evidence-grounded differential diagnosis prompts and verification steps.
  • Drug Interaction & Renal Dosing Engine: Instant renal dose adjustment recommendations based on verified equations.
  • Explainable Clinical Reasoning: Every suggestion links directly to authoritative guidelines and peer-reviewed clinical literature.

💻 Quickstart 

from medorqis.calculators import calculate_egfr_ckd_epi
from medorqis.guardrails import ClinicalSafetyGuard

# Deterministic eGFR Calculation (Zero LLM hallucinations)
result = calculate_egfr_ckd_epi(serum_creatinine=1.4, age=62, is_female=True)
print(f"eGFR: {result.value} mL/min/1.73m2 - Stage: {result.ckd_stage}")
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Check out the full repository and contribute on GitHub:
👉 https://github.com/seotarek/MedOrqis

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