What devices does this skill support?

The skill integrates with Oura (sleep/HRV), Garmin (activity/VO2max), Withings (weight/composition), and Yazio (nutrition) via MCP servers.

Does it track habit consistency?

Yes, it can optionally use Streaks-export-analysis to determine if changes in biometrics are linked to adherence or routine drift.

Can it perform deep weekly health reviews?

No, this skill is optimized for ad-hoc, targeted questions. For comprehensive periodic reviews, it is designed to escalate to the body-cadence-review skill.

What is the typical output format?

The skill provides a direct answer, followed by specific evidence (numbers/trends), interpretation relative to goals, caveats about data quality, and suggested next actions.

How does it prioritize data for health questions?

It follows a strict reasoning order: it first reads local strategy and numerical targets, then checks body area protocols, and finally pulls raw data from MCP sensors.

Body Metrics & Health Analytics

Name: Body Metrics & Health Analytics
Author: Rachnog

byRachnog

•

Analytics & Monitoring

Analyzes and synthesizes personal health data from multiple trackers to provide instant, numbers-driven answers about sleep, fitness, and nutrition.

This skill serves as a high-performance entry point for Claude to interact with personal health data stored in local vaults and external MCP servers like Oura, Garmin, Withings, and Yazio. Designed for a 'quant analyst' style of interaction, it prioritizes raw metrics and trend deltas over generic wellness advice. By cross-referencing biometric data with personal protocols, numerical targets, and habit adherence exports, it provides concise, evidence-based interpretations of your physical status, recovery levels, and progress toward long-term health goals.

Key Features

015 GitHub stars

02Domain-specific logic for sleep, diet, recovery, and body composition

03Unified health data synthesis across Oura, Garmin, Withings, and Yazio MCPs

04Context-aware analysis using local strategy documents and numerical targets

05Numbers-first reporting with direct metric deltas and trend interpretations

06Habit adherence correlation through Streaks export analysis

Use Cases

01Determining daily training readiness based on sleep, HRV, and recovery metrics

02Monitoring body composition trends and weight deltas relative to specific yearly targets

03Comparing nutritional intake like protein and calories against exercise consistency

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add rachnog/alex-honchar-claude-for-life body-data-qa

For use in Claude.ai and ChatGPT

Key Features

015 GitHub stars

02Domain-specific logic for sleep, diet, recovery, and body composition

03Unified health data synthesis across Oura, Garmin, Withings, and Yazio MCPs

04Context-aware analysis using local strategy documents and numerical targets

05Numbers-first reporting with direct metric deltas and trend interpretations

06Habit adherence correlation through Streaks export analysis

Use Cases

01Determining daily training readiness based on sleep, HRV, and recovery metrics

02Monitoring body composition trends and weight deltas relative to specific yearly targets

03Comparing nutritional intake like protein and calories against exercise consistency

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add rachnog/alex-honchar-claude-for-life body-data-qa

For use in Claude.ai and ChatGPT