Parse Apple Health export archives into structured CSV files.
npx skills add https://github.com/aquiladev/claude-skills --skill apple-health
Please help me install this Agent Skill. Skill: apple-health Source: https://github.com/aquiladev/claude-skills/tree/main/skills/apple-health Command: npx skills add https://github.com/aquiladev/claude-skills --skill apple-health
This skill solves the challenge of analyzing massive, multi-gigabyte Apple Health XML exports that typically cause memory crashes in standard environments.
Use the apple-health skill to parse the export.xml file in the current directory and generate a folder of clean CSVs for analysis.
High-intent search queries and answers about installing and using this skill.
To parse a multi-gigabyte Apple Health export.xml file without memory crashes, you need stream-based XML processing. This approach reads the document sequentially, preventing memory exhaustion while converting large HealthKit datasets into structured CSV formats.
You can extract ECG waveforms and GPX workout routes from Apple Health data using specialized parsing tools. This process transforms raw HealthKit records and GPS files into structured formats, enabling efficient clinical analysis and route mapping.
The best way to convert HealthKit metrics into tidy CSVs for pandas data analysis is through specialized XML parsing. This process streams complex Apple Health export data into queryable formats, allowing you to aggregate step counts or visualize heart rate trends efficiently.
This tool does support extracting clinical CDA records from HealthKit exports. It includes dedicated components designed to parse clinical documents alongside standard fitness tracking metrics, structuring them for immediate data analysis within your environment.
Parsing Apple Health XML with pandas causes memory crashes on large datasets because standard methods load the entire document into RAM. Using stream-based XML processing avoids this by reading sequentially, generating per-metric CSVs without exhausting memory.
You do need to install lxml and numpy to analyze HealthKit data with this skill. These dependencies provide the foundational stream-based XML parsing and numerical operations required to process multi-gigabyte Apple Health export archives efficiently.
mycelium-hqIngest Apple Health data into the local DuckDB used by health-mcp.
dotlab-hqPerform GPU-accelerated groupby aggregations and statistical summaries on large CSV datasets.
heroveAnalyze fitness data with linear regression and Pearson correlations for trends and coaching guidance.
yashpalsince2004Integrate Apple HealthKit to read, write, and query health data in iOS apps.
