Health Data

Name: Health Data
Author: glebis

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by glebis · vlatest · Repository

Analyzes patient health records to identify trends, anomalies, and potential risks based on provided data.

Install on your platform

We auto-selected Claude Code based on this skill’s supported platforms.

Run in terminal (recommended)

terminal

claude mcp add health-data npx -- -y @trustedskills/health-data

Or manually add to ~/.claude/settings.json

~/.claude/settings.json

{
  "mcpServers": {
    "health-data": {
      "command": "npx",
      "args": [
        "-y",
        "@trustedskills/health-data"
      ]
    }
  }
}

Requires Claude Code (claude CLI). Run claude --version to verify your install.

About This Skill

What it does

This skill enables AI agents to query and analyze health data stored in a local SQLite database containing over 6 million records across 43 different health metrics. It provides both pre-built Python scripts for common queries and allows for direct SQL execution for more customized analysis. The skill can retrieve daily summaries, weekly trends, sleep patterns, recent vital signs, activity ring progress, and workout history from the provided data.

When to use it

To understand your fitness trends over time (e.g., weekly steps or exercise minutes).
To review recent health metrics like heart rate and blood oxygen levels.
To analyze sleep patterns and identify potential issues.
To track workout history, including duration, distance, and calories burned for specific activities like running.
To generate reports summarizing daily activity and progress towards fitness goals.

Key capabilities

Data Source: Accesses health data from a local SQLite database (~/data/health.db).
Pre-built Python Scripts: Offers scripts for common queries (daily summary, weekly trends, sleep analysis, latest vitals, activity rings, workout history).
Custom SQL Queries: Allows direct execution of SQL queries against the database.
Output Formats: Supports output in Markdown, JSON, FHIR and ASCII formats.
Query Examples: Provides pre-defined queries for daily summaries, weekly trends, sleep analysis, latest vitals, activity rings, and workout history.

Example prompts

"Get my daily health summary."
"Show me my weekly trends in exercise minutes over the last 4 weeks as JSON."
"Analyze my sleep patterns for the past two weeks."
"What are my latest vital readings?"
"Give me a markdown report of my running workout history from the last 30 days."

Tips & gotchas

Database Location: The skill requires access to the ~/data/health.db database file. Ensure this path is accessible.
SQL Knowledge (Optional): While pre-built scripts are available, custom queries require familiarity with SQL syntax. Refer to references/schema.md for table structures and query templates.
Output Format: Specify the desired output format (markdown, json, fhir, ascii) using the --format flag in the Python script commands.

View Repository →

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Security Audits

Gen Agent Trust Hub	Pass
Socket	Pass
Snyk	Pass

Details

Version: vlatest
License
Author: glebis
Installs: 36

Repository (canonical source) →

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Passed automated security scans.