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KISHOR403
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health-data

Query and summarize health metrics from a local SQLite database.

Updated Apr 16, 2026
Search Tags:#analytics#sqlite#query#health#fhir#health-data#loinc
One-click install
npx skills add https://github.com/KISHOR403/claude-skills --skill health-data-kishor403
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: health-data
Source: https://github.com/KISHOR403/claude-skills/tree/main/health-data
Command: npx skills add https://github.com/KISHOR403/claude-skills --skill health-data-kishor403

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Analyze local health data stored in a SQLite database to produce actionable health insights and ready-to-share reports.

Core Features & Use Cases

  • Query daily health summaries, weekly trends, sleep analysis, vitals, activity rings, and workout histories from the local health database.
  • Output formats include Markdown, JSON, FHIR R4, and ASCII for easy integration with reports and dashboards.
  • Real-world example: generate a 14-day sleep quality overview and export it as JSON for a health dashboard.

Quick Start

Ask it to generate a daily health summary for today using the default Markdown format.

Frequently Asked Questions about health-data

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

FAQPage Schema
How do I query local SQLite health data for daily summaries and weekly trends?▼

Query local SQLite health data by running Python scripts against a documented database schema to extract daily summaries and weekly trends, outputting structured results in Markdown or JSON formats for reporting.

Can I export health metrics to FHIR R4 format using LOINC codes?▼

Export health metrics to FHIR R4 by mapping metric types to LOINC codes within the Python script engine, generating standardized FHIR outputs for interoperable health data exchange and integration.

What's the best way to analyze sleep patterns and vitals from a local health database?▼

Analyze sleep patterns and vitals from a local health database by executing SQL queries that summarize sleep quality, heart rate, and activity rings, producing structured outputs for health dashboards.

Does this approach support generating workout histories in JSON and Markdown?▼

Generating workout histories in JSON and Markdown is supported through the script-based query engine, which formats extracted activity data into multiple structured output types for reporting and analysis.

How do I customize SQL queries for specific health data analysis?▼

Customize SQL queries for health data analysis by modifying the Python scripts that interface with the local SQLite database, allowing tailored extraction of metrics like vitals, sleep, and activity rings.

What output formats are available for health data reporting and dashboards?▼

Available output formats for health data reporting include Markdown, JSON, FHIR R4, and ASCII, enabling seamless integration with reports, dashboards, and health information systems.

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