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

Description and use

MedOrqis is an open-source medical AI skills ecosystem that delivers deterministic, zero‑token clinical calculations and safety guardrails, eliminating hallucinations in LLM‑based clinical decision support.

Problem

Deploying large language models in healthcare risks hallucinations, calculation errors, lack of deterministic guardrails, and non-reproducible outputs.

Outcome

MedOrqis delivers deterministic, zero-token clinical calculations and safety guardrails, reducing hallucinations and ensuring reproducible, evidence-grounded outputs for clinical AI assistants.

Workflow

• 1. Install MedOrqis via CLI: npx skills add seotarek/MedOrqis
• 2. Import desired calculator, e.g., calculate_egfr_ckd_epi
• 3. Call the function with patient parameters
• 4. Receive deterministic result and safety-validated output
• 5. Optionally integrate with EHR via FHIR/HL7 schemas

Evidence

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.

Source

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).

Source

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.

Source