Install
openclaw skills install @bartsoj/health-metricsIngest Apple Health Auto Export JSON (HealthMetrics + Workouts) into a local DuckDB database and render offline HTML dashboards plus a Markdown daily summary (activity rings, training load, sleep, vitals, per-workout maps). Use when the user wants to process Apple Health exports, refresh their health dashboards, or get a training-load / rings / sleep / vitals report from their exported data.
openclaw skills install @bartsoj/health-metricsA self-contained pipeline that ingests Apple Health Auto Export JSON feeds into a local
DuckDB database and renders static, offline-first HTML dashboards plus an AI-oriented Markdown
digest. No web server, no scheduler, no pip packages — just Python stdlib and the duckdb CLI.
You run it on demand whenever new export files land.
python3 and the duckdb CLI binary on PATH (no Python duckdb package needed).Regenerate everything after new exports arrive:
python3 {baseDir}/scripts/ingest.py && python3 {baseDir}/scripts/report.py -o <OUT_DIR>
ingest.py reads the source JSON and upserts into the DuckDB file (idempotent — safe to
re-run; unchanged files are skipped).report.py -o <OUT_DIR> writes all dashboards into a directory you choose. Pick a working
or output directory the user controls; do not write inside the skill folder.scripts/run.sh) — recommendedscripts/run.sh wraps the pipeline and handles two things the raw scripts do not:
bash {baseDir}/scripts/run.sh daily-md [YYYY-MM-DD] [OUT_DIR] # ingest -> flat <OUT_DIR>/YYYY-MM-DD.md (default date = today)
bash {baseDir}/scripts/run.sh html [OUT_DIR] # ingest -> full HTML dashboard set in OUT_DIR
bash {baseDir}/scripts/run.sh ingest # materialize + ingest only
Output dirs: daily-md defaults to $HEALTH_MD_DIR (else reports/summary); html defaults
to $HEALTH_HTML_DIR (else a timestamped reports/html-*). html prints HTML_OUT_DIR=<dir>
on the last lines. Exits non-zero on failure so schedulers surface it.
Use daily-md from a scheduler to keep a per-day Markdown log current (e.g. a nightly cron
that writes into a knowledge/notes folder), and html on demand for shareable dashboards.
Apple Health Auto Export writes into an iCloud Drive folder. With "Optimize Mac Storage"
enabled, macOS evicts file contents to placeholders — the files still appear in ls (with a
size!) but their bytes are not on disk until something opens them. DuckDB and Python then fail
to read them with:
IO Error: Could not read from file "…HealthMetrics-YYYY-MM-DD.json": Resource deadlock avoided
(EDEADLK). run.sh handles this by running brctl download on each source file and waiting
until the bytes are present before ingesting (no-op on Linux / non-iCloud dirs).
Permanent fix (do once): in Finder, right-click each source folder
(iCloud Drive HealthMetrics and iCloud Drive Workouts) → "Keep Downloaded". This pins the
folders so iCloud never evicts them; there is no CLI equivalent. After pinning, the brctl
step in run.sh becomes a harmless safety net.
| Env var | Purpose | Default |
|---|---|---|
HEALTH_METRICS_DIR | Folder of HealthMetrics-YYYY-MM-DD.json files | Apple Health Auto Export iCloud …/iCloud Drive HealthMetrics under $HOME |
HEALTH_WORKOUTS_DIR | Folder of Workouts-YYYY-MM-DD.json files | Apple Health Auto Export iCloud …/iCloud Drive Workouts under $HOME |
HEALTH_DB_PATH | Where the DuckDB file lives | ~/.local/state/health-metrics/health.duckdb |
--db PATH on ingest.py / report.py overrides HEALTH_DB_PATH for that run.
⚠️ The DuckDB database is personal, sensitive health data. It is created on first ingest, lives outside this skill, and must never be committed, published, or shared. It is not part of the skill bundle.
report.py -o <DIR> mirrors this layout beneath <DIR>:
<DIR>/ (daily-*.html, weekly-*.html, monthly-*.html, rings.html,
training-load.html)<DIR>/workouts/<DIR>/summary/Each script is independently runnable and honors HEALTH_DB_PATH. A single script's --out-dir
is the literal, flat directory it writes into (no subfolder appended).
| Script | What it produces | Key flags |
|---|---|---|
scripts/ingest_health_metrics.py | samples_qty / samples_hr / sleep_sessions | — |
scripts/ingest_workouts.py | workouts + workout_route/hr/hr_recovery | — |
scripts/report_health_metrics.py | activity / sleep / vitals summaries | --period daily|weekly|monthly|all --date YYYY-MM-DD -o DIR |
scripts/report_workouts.py | one page per workout + index | --force (re-render all) -o DIR |
scripts/report_rings.py | Apple-style activity rings | -o DIR |
scripts/report_training_load.py | TRIMP training load trend | -o DIR |
scripts/report_daily_summary.py | Markdown digest for AI readers | --date YYYY-MM-DD -o DIR |
Query the database directly — the tables in references/schema.md are the full analysis surface:
duckdb "$HEALTH_DB_PATH" -json -c "SELECT * FROM workouts ORDER BY date DESC LIMIT 5"
Or from Python via scripts/lib/query.py's query(sql) helper (shells out to the duckdb CLI,
returns parsed JSON rows).
See {baseDir}/references/architecture.md (data flow, ingestion pattern, report conventions,
lib/ helpers) and {baseDir}/references/schema.md (DuckDB table reference) before modifying
the scripts or adding a new report/metric.