Evo Clinical Unit Harmonization

Organization

OpenLAIR

evo-clinical-unit-harmonization

Domain-specific clinical lab unit detection and conversion module with conversion factor registry, physiological range boundaries, and boundary-based auto-detection logic to convert SI units to US conventional units.

Overview

Publisher	OpenLAIR
Repository	`OpenSkill`
Skill name	`evo-clinical-unit-harmonization`
Stars	97
Forks	4
Bundled files	1
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by OpenLAIR on GitHub. Read the source before you install it.

Installation

Install the Evo Clinical Unit Harmonization AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/OpenLAIR/OpenSkill/tree/main/tasks-evolved/lab-unit-harmonization/environment/skills/evo-clinical-unit-harmonization
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/OpenLAIR/OpenSkill/tree/main/tasks-evolved/lab-unit-harmonization/environment/skills/evo-clinical-unit-harmonization

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/OpenLAIR/OpenSkill.git /tmp/OpenSkill
mkdir -p .claude/skills
cp -r /tmp/OpenSkill/tasks-evolved/lab-unit-harmonization/environment/skills/evo-clinical-unit-harmonization .claude/skills/evo-clinical-unit-harmonization

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Evo Clinical Unit Harmonization in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Evo Clinical Unit Harmonization on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Evo Clinical Unit Harmonization is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

evo-clinical-unit-harmonization

Converts clinical lab values from SI to US conventional units using boundary-based auto-detection.

Key Functions

build_conversion_registry() - Returns dict mapping column names to analyte configs
detect_and_convert_value(val, config) - Detect and convert a single value
harmonize_column(series, config) - Harmonize an entire column
harmonize_all_features(df, skip_cols) - Harmonize all features in DataFrame

Usage

python
import sys
sys.path.insert(0, '/app/environment/skills/evo-clinical-unit-harmonization/scripts')
from utils import harmonize_all_features

df = harmonize_all_features(df, skip_cols=['patient_id'])

Conversion Registry

Covers all 62 CKD features including:

Creatinine (SI umol/L -> US mg/dL, factor 0.0113)
BUN (SI mmol/L -> US mg/dL, factor 2.8)
Hemoglobin (SI g/L -> US g/dL, factor 0.1)
Albumin/Total Protein (SI g/L -> US g/dL, factor 0.1)
Glucose (SI mmol/L -> US mg/dL, factor 18.0)
HbA1c (SI mmol/mol -> US %, linear: val*0.0915+2.15)
Calcium (SI mmol/L -> US mg/dL, factor 4.0)
Phosphorus (SI mmol/L -> US mg/dL, factor 3.1)
Cholesterol/LDL/HDL (SI mmol/L -> US mg/dL, factor 38.67)
Triglycerides (SI mmol/L -> US mg/dL, factor 88.57)
Uric Acid (SI umol/L -> US mg/dL, factor 0.0168)
Bilirubin (SI umol/L -> US mg/dL, factor 0.0585)
Iron/TIBC (SI umol/L -> US ug/dL, factor 5.587)
Hematocrit (SI L/L -> US %, factor 100)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

scripts/utils.py3 KB

Frequently asked questions

What does the Evo Clinical Unit Harmonization AI skill do?

Why use Evo Clinical Unit Harmonization on TypingMind?

Because you install it once and use it with any model. Evo Clinical Unit Harmonization is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Evo Clinical Unit Harmonization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/OpenLAIR/OpenSkill/tree/main/tasks-evolved/lab-unit-harmonization/environment/skills/evo-clinical-unit-harmonization. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Evo Clinical Unit Harmonization?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Evo Clinical Unit Harmonization?

As many as you like. As long as a model supports skills, you can use Evo Clinical Unit Harmonization with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Evo Clinical Unit Harmonization AI skill free?

Yes. It is published on GitHub by OpenLAIR under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Nano Pdf

openclaw

OrganizationPopular

Edit PDFs with natural-language instructions using the nano-pdf CLI.

Subagent Driven Development

obra

CommunityPopular

Use when executing implementation plans with independent tasks in the current session

Unified Memory

Share durable, inspectable context and handoffs between Claude, Codex, Hermes, Cursor, OpenCode, and other agents through the local ECC Memory Vault. Use when an agent must save work state, transfer…

Draw Your Font

Turn a handwriting photo into an installable TTF font.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

evo-clinical-unit-harmonization

Key Functions

Usage

Conversion Registry

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now