ghealth

CLI for the Google Health API v4 — built for AI agents and developers.

• 40 verified data types: steps, heart rate, exercise, sleep, weight, SpO2, HRV, ECG, blood glucose, nutrition, and more
• Agent-first: simplified JSON output, deterministic exit codes, --dry-run, --raw
• Single binary: go build -o ghealth .

Quick Start

ghealth setup                                              # One-time: GCP project + OAuth
ghealth data steps daily-rollup --from 2026-03-22 --to 2026-03-29  # Weekly step totals
ghealth data heart-rate list --from today --limit 10       # Recent heart rate readings
ghealth schema types                                       # See all available data types

Requirements

Download and Install Go

Installation

git clone https://github.com/Google-Health-API/google-health-cli.git
cd google-health-cli
go build -o ghealth .

Setup

ghealth setup

Walks you through: GCP project ID, OAuth credentials (download from Console — Desktop application type), Health API enablement, scope selection, and browser-based OAuth login.

Files written under ~/.config/ghealth/ (override with GHEALTH_CONFIG_DIR):

• client_secret.json — your OAuth client (mode 0600)
• credentials.json — access + refresh tokens (mode 0600, plaintext JSON)
• config.toml — active profile (project, scopes)

Tokens refresh automatically.

Non-interactive setup (for agents / CI)

ghealth setup \
  --project-id my-project \
  --client-secret ~/Downloads/client_secret_123.json \
  --scopes-preset readonly \
  --skip-enable-api \
  --no-prompt

Add --non-interactive-auth to skip the browser step too — complete later with ghealth auth login --complete <code> (see below).

Authentication

Scenario	Method
Interactive	ghealth setup or ghealth auth login
Headless / no browser	ghealth auth login --non-interactive → click URL on any device → ghealth auth login --complete <code>
Move tokens between machines	ghealth auth export → ghealth auth import
Pre-configured token	export GHEALTH_ACCESS_TOKEN=ya29...
Credential file	export GHEALTH_CREDENTIALS_FILE=/path/to/creds.json
GCP environment	Application Default Credentials (automatic)

Precedence: GHEALTH_ACCESS_TOKEN > GHEALTH_CREDENTIALS_FILE > stored credentials > ADC.

Headless OAuth flow

# 1. On the host running ghealth:
ghealth auth login --non-interactive --scopes-preset readonly
# → JSON with auth_url (PKCE S256 challenge + random state baked in)
#   and a complete_command. pending_auth.json holds the verifier locally.

# 2. Open auth_url in any browser, click "Allow".
#    The browser will redirect to a localhost URL that fails to load — expected.
#    Copy either the full redirected URL or just the 'code' query parameter.

# 3. Back on the ghealth host (both forms work):
ghealth auth login --complete 'http://localhost/?code=4/0AX4XfWh...&state=cQq...'
ghealth auth login --complete 4/0AX4XfWh...
# → state validated, PKCE verifier sent on exchange, tokens persisted.

State mismatch (URL paste with the wrong state parameter) clears the pending flow and returns exit 2. The bare-code form skips state validation but still consumes the pending file, so a stale flow can't be replayed.

Move tokens between machines

# source (already authenticated):
ghealth auth export > /tmp/ghealth-creds.json
scp /tmp/ghealth-creds.json target:

# target (also needs client_secret.json — either run 'ghealth setup --non-interactive-auth' or copy it):
ghealth auth import --file /tmp/ghealth-creds.json

Bootstrap from a fresh machine (no client_secret yet)

When no OAuth client_secret.json is configured, every auth command returns a structured error with a next_steps array — the same six steps every time — so an agent can relay it to a user verbatim without scraping prose:

ghealth auth login
# → exit 5, JSON on stderr:
# {
#   "error": {
#     "type": "config", "code": 5,
#     "message": "No OAuth client_secret.json configured",
#     "hint":    "Run 'ghealth setup' to create or import OAuth credentials",
#     "next_steps": [
#       "Open https://console.cloud.google.com/apis/credentials",
#       "Create or select a Google Cloud project",
#       "Enable the Google Health API (...)",
#       "Create OAuth client ID with Application type: Desktop app",
#       "Download the client_secret JSON",
#       "Run: ghealth setup --client-secret /path/to/client_secret.json"
#     ]
#   }
# }

Same next_steps are emitted by:

• ghealth auth login (interactive / --non-interactive / --complete)
• ghealth auth status when neither stored creds nor env creds are present
• ghealth auth refresh, ghealth auth export (when nothing to refresh/export)
• ghealth setup --no-prompt when --client-secret is missing

To fetch the checklist without triggering an error (e.g. so an agent can display the bootstrap steps before calling auth at all):

ghealth setup --instructions
# → exit 0, JSON on stdout with status: "instructions" and the next_steps array

Data Types

40 types verified against the live API. Run ghealth schema types for the full list.

Type	Key Values	Operations
steps	(use daily-rollup for countSum)	list, rollup, daily-rollup, reconcile
heart-rate	beatsPerMinute	list, rollup, daily-rollup, reconcile
exercise	type, duration, calories, avgHeartRate, notes	list, get, create, update, delete, reconcile, export-tcx
sleep	minutesAsleep, minutesAwake, stageMinutes	list, get, create, update, delete, reconcile
weight	weightGrams	list, get, create, update, delete, rollup, daily-rollup, reconcile
body-fat	percentage	list, get, create, update, delete, rollup, daily-rollup, reconcile
height	heightMillimeters	list, get, create, update, delete, reconcile
distance	(use daily-rollup for millimetersSum)	list, rollup, daily-rollup, reconcile
heart-rate-variability	RMSSD	list, reconcile
oxygen-saturation	percentage (SpO2)	list, reconcile
altitude	altitude value	list, rollup, daily-rollup, reconcile
active-zone-minutes	activeZoneMinutes, heartRateZone	list, daily-rollup, reconcile
activity-level	SEDENTARY, LIGHT, MODERATE, VIGOROUS	list, reconcile
basal-energy-burned	kcal per interval (BMR)	list, reconcile
active-energy-burned	kcal per interval (activity)	list, rollup, daily-rollup, reconcile
vo2-max	VO2 max value	list, reconcile
total-calories	(use daily-rollup for kcalSum)	daily-rollup
sedentary-period	sedentary intervals	list, daily-rollup, reconcile
swim-lengths-data	swimStrokeType, strokeCount (use daily-rollup for strokeCountSum)	list, rollup, daily-rollup, reconcile
hydration-log	milliliters consumed	list, get, daily-rollup, reconcile
nutrition-log	nutrients, energy, mealType, food	list, get, rollup, daily-rollup, reconcile
food	nutrient profiles, servings (catalog — no time filter)	list, get
food-measurement-unit	displayName (catalog — no time filter)	list, get
blood-glucose	mg/dL, mealType, measurementTiming	list, get, rollup, daily-rollup, reconcile
core-body-temperature	temperatureCelsius	list, get, rollup, daily-rollup, reconcile
electrocardiogram	waveform, resultClassification (requires ecg.readonly)	list
irregular-rhythm-notification	alert windows (requires irn.readonly)	list
daily-resting-heart-rate	beatsPerMinute per day	list, reconcile
daily-heart-rate-variability	daily HRV summary	list, reconcile
daily-oxygen-saturation	daily SpO2 summary	list, reconcile
daily-respiratory-rate	daily respiratory rate	list, reconcile
daily-vo2-max	daily VO2 max	list, reconcile
daily-sleep-temperature-derivations	temp deviation from baseline	list, reconcile
respiratory-rate-sleep-summary	per-stage respiratory rate	list, reconcile
run-vo2-max	VO2 max from running	list, daily-rollup, reconcile
floors	(rollup only — countSum)	rollup, daily-rollup, reconcile
active-minutes	(rollup only)	rollup, daily-rollup, reconcile
time-in-heart-rate-zone	(rollup only)	daily-rollup, reconcile
calories-in-heart-rate-zone	(rollup only — caloriesInHeartRateZones array per bucket)	rollup, daily-rollup, reconcile
daily-heart-rate-zones	(reconcile only)	reconcile

Exercise track export

export-tcx writes the raw Google TCX, or — with --as csv — flattens it to one row per trackpoint (time, activity, lap, sport, latitude_deg, longitude_deg, altitude_m, distance_m, heart_rate_bpm, cadence_rpm, speed_mps, watts) for direct pd.read_csv consumption. Indoor activities have no track and yield a header-only CSV; their summary/notes live in data exercise list. Pass --output - to stream to stdout instead of a file.

ghealth data exercise export-tcx --id <id> --output ride.csv --as csv
ghealth data exercise export-tcx --id <id> --output - --as csv | head   # stream to stdout

Usage

Reading data

# Recent heart rate (sample-type: returns individual readings)
ghealth data heart-rate list --from today --limit 10

# Daily step totals for a week (rollup: returns aggregated counts)
ghealth data steps daily-rollup --from 2026-03-22 --to 2026-03-29

# Exercises this month
ghealth data exercise list --from 2026-03-01

# Weight history
ghealth data weight list --limit 20

# Sleep (summary by default, --detail for stage-by-stage breakdown)
ghealth data sleep list --limit 5
ghealth data sleep list --limit 5 --detail

Every read (list, get, rollup, daily-rollup, reconcile) returns the same JSON shape — an object {"dataPoints": [...]} with optional _hints and nextPageToken — so the rows are always under dataPoints.

list returns up to --limit rows (default 500). When more exist it includes a nextPageToken; pass it back with --page-token to fetch the next page losslessly (no rows skipped or repeated):

ghealth data heart-rate list --from 2026-06-15 --limit 500            # → {"dataPoints":[…], "nextPageToken":"ABC"}
ghealth data heart-rate list --from 2026-06-15 --limit 500 --page-token ABC

Important: list vs daily-rollup

Some types (steps, distance) return time intervals without values from list. Use daily-rollup to get totals:

# This returns minute-by-minute intervals (no step count):
ghealth data steps list --from today --limit 5

# This returns daily totals with actual counts:
ghealth data steps daily-rollup --from 2026-03-22 --to 2026-03-29
# → {"dataPoints": [{"date": "2026-03-28", "countSum": "9037"}, ...]}

Gotcha: missing days are NOT zeros

For the presence-aware types — altitude, distance, floors, steps, total-calories — a date that is absent from rollup output means the device was not worn (or did not sync) that day, not that the value was zero. A bucket with countSum: "0" is a true zero: the device was worn and genuinely recorded no activity.

• Missing date → render as "no data", never coalesce to 0
• countSum: "0" → true zero (worn, no activity)
• Never average over absent days as if they were zeros — that silently deflates weekly/monthly stats

Filtering

ghealth data heart-rate list --from 2026-03-28                  # From date
ghealth data heart-rate list --from 2026-03-28 --to 2026-03-29  # Date range
ghealth data heart-rate list --from today --limit 50            # Today, max 50
ghealth data heart-rate list --from yesterday                   # Since yesterday

--filter passes a raw expression to the API (overrides --from/--to). Filter syntax follows AIP-160 — interval types use {type}.interval.civil_start_time (ISO 8601, no Z), sleep uses sleep.interval.civil_end_time (only end-time is filterable), sample types use {type}.sample_time.physical_time (RFC-3339, with Z). Only >= and < comparators are supported.

Writing data

Writable types: exercise, sleep, weight, body-fat, height.

Write operations are asynchronous — the API returns an Operation object. Use list to verify the data was persisted.

To discover the correct JSON format, inspect a real response: ghealth data weight list --raw --limit 1

# Create (use --raw list output to model the payload structure)
ghealth data weight create --json '{"weight": {"weightGrams": 75500, "sampleTime": {"physicalTime": "2026-03-29T10:00:00Z", "utcOffset": "3600s"}}}'

# Update (use --update-mask to specify which fields to change)
ghealth data weight update --id <id> --json '{"weight": {"weightGrams": 76000}}'

# Delete (accepts bare IDs or full resource names)
ghealth data exercise delete --ids 7649353586249326520

Output

Responses are simplified by default — redundant timestamps, empty fields, and repeated metadata are stripped. Timestamps include the user's UTC offset (e.g., +01:00).

ghealth data heart-rate list --from today --limit 2

{
  "dataPoints": [
    {"time": "2026-03-29T16:33:07+01:00", "beatsPerMinute": "80", "source": "Google Pixel Watch 4 (41mm)"},
    {"time": "2026-03-29T16:33:04+01:00", "beatsPerMinute": "80", "source": "Google Pixel Watch 4 (41mm)"}
  ]
}

ghealth data steps daily-rollup --from 2026-03-26 --to 2026-03-29

{
  "dataPoints": [
    {"date": "2026-03-28", "countSum": "9037"},
    {"date": "2026-03-27", "countSum": "2408"},
    {"date": "2026-03-26", "countSum": "6474"}
  ]
}

Flag	Effect
--raw	Return the original API response with no simplification
--format table	Aligned columns
--format csv	CSV output (nested objects flatten to dot-separated columns)
-o, --output <file>	Write data to the file; print only a column schema + 3-row preview to stdout. Prefer this over > file (which gives the file but no schema)
--dry-run	Show the HTTP request without executing

In --format csv and --format table, the data stream stays pure: _hints and a leftover nextPageToken are written to stderr rather than mixed into the rows, and an empty result emits an empty CSV (never a JSON object). Use -o <file> and the stderr signals together to page through a large export without polluting the CSV.

AI Agent Skills

The repo ships 2 Agent Skills (SKILL.md files) — one for shared prerequisites (auth, setup, global flags) and one covering all 40 data types, operations, patterns, and gotchas.

# Install all skills at once
npx skills add https://github.com/Google-Health-API/google-health-cli

# Or pick only what you need
npx skills add https://github.com/Google-Health-API/google-health-cli/tree/main/skills/ghealth
npx skills add https://github.com/Google-Health-API/google-health-cli/tree/main/skills/ghealth-shared

Agents don't need to read the full skill file upfront. The CLI supports progressive self-discovery:

ghealth schema types              # What types exist? What operations?
ghealth schema type heart-rate    # Fields, parameters, scope for one type
ghealth data <type> --help        # What operations does this type support?
ghealth data <type> list --help   # What flags does this operation take?
ghealth --dry-run ...             # What HTTP request would this send?

Other Commands

ghealth user identity                    # User identity
ghealth user profile get                 # Profile (age, stride length)
ghealth user settings get                # Settings (timezone, units)
ghealth auth status                      # Auth state (scopes, expiry)
ghealth schema types                     # All data types + operations
ghealth schema type heart-rate           # Detail for one type
ghealth schema scopes                    # OAuth scopes
ghealth schema endpoints                 # All API endpoints
ghealth config show                      # Show active configuration (project, scopes, format)
ghealth config set timezone <IANA zone>  # Set a config value (keys: project_id, format, timezone)
ghealth webhooks subscribers list        # Manage push-notification subscribers / subscriptions

webhooks (subscribers, subscriptions, verify) manages project-level push notifications and requires the cloud-platform scope plus a configured project ID — see the skill docs for details.

Because a cloud-platform token is rejected by the data-plane endpoints, keep webhook credentials in a separate config dir from your health-data credentials. auth login always writes tokens to the active config dir, so use a dedicated GHEALTH_CONFIG_DIR for webhooks (not GHEALTH_CREDENTIALS_FILE, which only changes where tokens are read from):

export GHEALTH_CONFIG_DIR=~/.config/ghealth-webhooks
ghealth setup                              # its own client_secret + project
ghealth auth login --scopes cloud-platform
ghealth webhooks subscribers list

Timezones

Date arguments (--from/--to, today, yesterday) resolve against exactly one timezone, chosen in this order:

1. the active profile's configured zone — ghealth config set timezone <IANA zone>
2. otherwise, the machine-local timezone

Verifying tokens

ghealth auth status is a fast local check by default — it reports what's configured without making any network calls, and the authenticated field reflects local state only. For env-token / credentials-file modes it is omitted entirely (presence of a token doesn't prove validity).

ghealth auth status --validate

Verifies the access token against Google's tokeninfo endpoint. authenticated then reflects actual validity, and the response includes expires_in and scope from Google.

Exit Codes

Code	Meaning
0	Success
1	API error (4xx/5xx)
2	Auth error (have client_secret, missing or invalid tokens — run ghealth auth login)
3	Validation error
4	Network error
5	Config error (often: no client_secret.json — error carries next_steps for bootstrap)

Errors are always JSON on stderr and may include a next_steps: []string array for multi-step recovery (currently only emitted when no OAuth client is configured).

Environment Variables

Variable	Purpose
GHEALTH_ACCESS_TOKEN	Direct access token
GHEALTH_CREDENTIALS_FILE	Path to credential JSON
GHEALTH_CONFIG_DIR	Config directory override
GHEALTH_PROFILE	Active profile name
GHEALTH_FORMAT	Default output format (json/table/csv)
GHEALTH_BASE_URL	Override the API base URL

License

Apache 2.0 — see LICENSE.