Ingest wearable health data into a local SQLite knowledge graph.
npx skills add https://github.com/broomva/skills --skill health-broomva
Please help me install this Agent Skill. Skill: health Source: https://github.com/broomva/skills/tree/main/skills/healthcare/health Command: npx skills add https://github.com/broomva/skills --skill health-broomva
This Skill solves the fragmentation of personal health data by providing a local-first, queryable knowledge graph that synthesizes raw wearable data into validated longevity metrics without relying on vendor-controlled coaching surfaces.
Run the health sync command to pull your latest wearable data and update your local health knowledge graph.
High-intent search queries and answers about installing and using this skill.
To build a local-first health knowledge graph, ingest and synthesize personal wearable data from Garmin devices into a secure, local SQLite database using modular hexagonal architecture for diverse health data integration.
Calculate longevity metrics like HRV-CV, CTL/ATL/TSB training load, and VO2max arcs by synthesizing raw time-series health data within a local SQLite database, avoiding vendor-controlled coaching surfaces.
Yes, you can generate daily health summaries directly into your personal Obsidian knowledge base for human interpretation, projecting validated longevity metrics from your local SQLite health graph.
No, it eliminates reliance on vendor-controlled coaching surfaces by automatically pulling and mapping raw Garmin data into a secure, local SQLite database, giving you full queryable ownership of your health metrics.
The best way to avoid vendor lock-in is ingesting raw wearable traces into a local-first SQLite knowledge graph, enabling independent time-series analysis of VO2max arcs and HRV trends.
Data ingestion is currently specialized for Garmin devices via the garth dependency, meaning users with wearables from other ecosystems cannot utilize the trace ingestion pipeline without modular adaptation.
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