How do I install the Chatehr Clinician Assistant skill?

Run npx skillmds@latest add biotender-max/chatehr-clinician-assistant in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Chatehr Clinician Assistant skill do?

<!-- It is listed under Coding & Dev Tools on SkillMD.

Is Chatehr Clinician Assistant safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Chatehr Clinician Assistant?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Chatehr Clinician Assistant free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Chatehr Clinician Assistant?

BioTender-max (@biotender-max) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Chatehr Clinician Assistant by biotender-max

Name: Chatehr Clinician Assistant
Author: BioTender-max

File contents

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:

python -m chatehr.query --patient_id 12345 --prompt "Summarize last 3 oncology visits"

Frequently asked questions

Chatehr Clinician Assistant