describe-concept-set

Name: describe-concept-set
Availability: InStock
Author: indicate-eu

Generate detailed Markdown descriptions of clinical concept sets using biomedical vocabularies.

7|4|Updated Feb 12, 2026

Search Tags:#documentation #vocabulary #clinical terminology #SNOMED #concept set #OHDSI #LOINC

Ready to run

npx skills add https://github.com/indicate-eu/data-dictionary --skill describe-concept-set

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: describe-concept-set
Source: https://github.com/indicate-eu/data-dictionary/tree/main/.claude/skills/describe-concept-set
Command: npx skills add https://github.com/indicate-eu/data-dictionary --skill describe-concept-set

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps data scientists and data engineers understand and document clinical concept sets by automatically generating detailed natural language descriptions.

Core Features & Use Cases

Automated Documentation: Creates comprehensive descriptions of concept sets using vocabulary sources like LOINC, SNOMED, and UMLS.
Vocabulary Integration: Retrieves definitions, hierarchies, and mappings from multiple biomedical vocabularies to enhance understanding.
Use Case: When developing a new lab test concept set, generate a concise yet thorough overview to assist mapping and validation efforts.

Quick Start

Provide the concept set ID when prompted; the Skill will fetch relevant vocabulary data and produce a detailed Markdown document summarizing the set's clinical context and concept grouping.

Frequently Asked Questions about describe-concept-set

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate descriptions for clinical concept sets using SNOMED and LOINC?▼

You can generate descriptions for clinical concept sets by providing a concept set ID to automate documentation. The tool retrieves definitions and hierarchies from vocabularies like SNOMED and LOINC to produce a detailed Markdown summary.

What is an automated concept set description and why is it needed for data mapping?▼

An automated concept set description is a human-readable summary of clinical terms used to assist data mapping and validation. It clarifies the clinical context and concept grouping so data engineers can verify vocabulary accuracy.

Can I document OHDSI concept sets without manually looking up UMLS hierarchies?▼

Yes, you can document OHDSI concept sets without manual UMLS lookups by providing the concept set ID. The process automatically fetches relevant vocabulary data, including hierarchies and mappings, to generate the overview.

Does this approach retrieve vocabulary definitions for lab test concept sets from multiple biomedical sources?▼

Yes, this approach retrieves definitions from multiple biomedical vocabularies including SNOMED, LOINC, and UMLS. It integrates these sources to enhance understanding when developing lab test concept sets for validation efforts.

What is the best way to validate clinical terminology mappings for data engineering pipelines?▼

The best way to validate clinical terminology mappings is to generate a detailed natural language description of the concept set. This provides a concise overview of the clinical context to assist validation efforts.