Function Health

Community

win4r

function_health

Retrieve lab biomarker results and clinician notes from Function Health.

Overview

Publisher	win4r
Repository	`MuseAI-Skills`
Skill name	`function_health`
Stars	382
Forks	116
Bundled files	1
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 win4r on GitHub. Read the source before you install it.

Installation

Install the Function Health 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/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/function-health
Enable the skill in any chat where you want it available.

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/win4r/MuseAI-Skills.git /tmp/MuseAI-Skills
mkdir -p .claude/skills
cp -r /tmp/MuseAI-Skills/opt/hatch/skills/function-health .claude/skills/function_health

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

Use it in TypingMind

Enable Function Health 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 Function Health 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 Function Health 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.

Function Health

Purpose

Use the function-health CLI to retrieve patient lab biomarker history and clinician consultation notes from Function Health's FHIR API.

Tooling

Use the installed CLI directly from PATH.

Auth commands:

function-health status
function-health authorize-url
function-health disconnect

Data commands:

function-health observations [--count N] [--page N] [--all]
function-health documents [--count N] [--page N] [--all]

Output

Data commands return JSON FHIR Bundles. For observations, summarize biomarker name, collection date, value, reference range, and interpretation when present. For documents, summarize clinician notes from structured JSON content. HTML attachment payloads are stripped in v0 and reported with omitted_reason/size_bytes metadata rather than being persisted to disk.

FHIR reads preserve their raw timestamps and add semantic UTC and user-local forms for observation, document, attachment, resource-update, and clinical period times. Date-only clinical values remain dates.

No Real Data → Never Fabricate (highest-priority safety rule)

A tool call that does not return real records is never a license to invent one. Fabricating medical facts — biomarker values, reference ranges, interpretations, dates, or clinician-note content — is the most serious failure mode of this skill (no-harmful-misinformation / no-hallucinated-medical-facts). Treat every "no real data" state the same way: state plainly that the data was not available, then offer a concrete next step. Do not substitute plausible-sounding values, ranges, or interpretations.

State	What the tool returned	Required response
Empty	call completed, Bundle has no matching entries	"I don't see any lab results / clinician notes on file for that. They may not be in your Function Health account yet."
Omitted content	a document whose payload was stripped (`omitted_reason`/`size_bytes` only, no structured note text)	Report that the note content wasn't retrievable (e.g. HTML attachment stripped in v0); do not infer or summarize what the note "probably" says.
Failure / error	tool errored, non-zero exit, or `not connected`	Report that the call failed and suggest a retry or reconnect. Do not answer the clinical question from memory or assumption.

Never state a specific biomarker value, reference range, interpretation, or date that did not appear verbatim in a command's completed JSON output.
When data is returned but sparse, acknowledge the gap rather than filling it — do not extrapolate trends from a single data point or invent missing biomarkers.

Auth

Function Health is an OAuth-backed skill.

Before any Function Health API use:

Run function-health status.
If status is not connected, complete the link flow first.
Run function-health authorize-url. When connect_url is present, replace <connect_url> with the returned URL and share exactly this Markdown link: [Connect Function Health](<connect_url>); do not paste the raw URL separately.
After callback completion, run function-health status again and continue only when status is connected.

Credential safety:

Credentials are managed automatically and are not exposed to the agent.
Never print client_secret, access_token, or refresh_token.

Operating Rules

Always run function-health status before any data command.
Never state a specific clinical value — biomarker result, reference range, interpretation, or date — that did not appear verbatim in a command's completed output. If a call is empty, has omitted content, or fails, follow "No Real Data → Never Fabricate": say the data was not available and offer a next step. Never fill the gap with plausible-sounding values. This is the highest-priority safety rule.
Prefer LOINC codes (http://loinc.org) to normalize biomarkers when comparing across vendors.
Do not treat interpretation (Normal/Abnormal) as medical advice; present it as informational and encourage clinical follow-up.
Use --all to paginate through complete history when the user asks for trends or longitudinal analysis.

Bundled files

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

manifest.yaml2 KB

Frequently asked questions

What does the Function Health AI skill do?

Retrieve lab biomarker results and clinician notes from Function Health.

Why use Function Health on TypingMind?

Because you install it once and use it with any model. Function Health 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 Function Health in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/win4r/MuseAI-Skills/tree/main/opt/hatch/skills/function-health. 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 Function Health?

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 Function Health?

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

Is the Function Health AI skill free?

It is published on GitHub by win4r. Check the repository for licensing terms. 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.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Function Health

Purpose

Tooling

Output

No Real Data → Never Fabricate (highest-priority safety rule)

Auth

Operating Rules

Bundled files

Frequently asked questions

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