install
source · Clone the upstream repo
git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/chatehr-clinician-assistant" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-chatehr-clinician-assistant && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/chatehr-clinician-assistant" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-chatehr-clinician-assistant && rm -rf "$T"
manifest:
skills/chatehr-clinician-assistant/SKILL.mdsource content
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
-->
name: chatehr-clinician-assistant description: EHR Chat Assistant keywords:
- EHR
- clinical
- summarization
- patient-records
- FHIR measurable_outcome: Answer 5 clinical queries and generate a discharge summary from a patient record with <10s latency. license: Apache-2.0 metadata: author: Stanford Medicine version: "1.0.0" compatibility:
- system: Python 3.10+ allowed-tools:
- run_shell_command
- read_file
ChatEHR
AI software for clinicians to interact with patient medical records via natural language queries and automatic chart summarization.
When to Use
- Rapid Review: "Summarize the patient's cardiology history."
- Data Extraction: "What was the last creatinine level?"
- Documentation: Generating draft notes or discharge summaries.
Core Capabilities
- Chart Summarization: Condense complex history into readable notes.
- QA: Answer specific questions about the patient's data.
- FHIR Integration: Works with standard FHIR resources.
Workflow
- Connect: Authenticate with the EHR system (sandbox or secure instance).
- Select Patient: Load patient context.
- Query: Submit natural language questions.
Example Usage
User: "Summarize the last 3 oncology visits."
Agent Action:
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->python -m chatehr.query --patient_id 12345 --prompt "Summarize last 3 oncology visits"