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List Google Health Data Points

google_health_list_data_points
Read-onlyIdempotent

Retrieve granular data points for any Google Health data type (e.g., steps, heart rate) using filter expressions and pagination for efficient access.

Instructions

Query detailed data points for a Google Health data type. Use kebab-case endpoint data types, e.g. steps, sleep, heart-rate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoOptional Google AIP-160 filter expression. Use snake_case field names in filters.
data_typeNoGoogle Health data type in kebab case. Supported slugs (call google_health_list_data_types for units and which verbs each supports): active-energy-burned, active-minutes, active-zone-minutes, activity-level, altitude, blood-glucose, body-fat, calories-in-heart-rate-zone, core-body-temperature, daily-heart-rate-variability, daily-heart-rate-zones, daily-oxygen-saturation, daily-respiratory-rate, daily-resting-heart-rate, daily-sleep-temperature-derivations, daily-vo2-max, distance, electrocardiogram, exercise, floors, food, food-measurement-unit, heart-rate, heart-rate-variability, height, hydration-log, irregular-rhythm-notification, nutrition-log, oxygen-saturation, respiratory-rate-sleep-summary, run-vo2-max, sedentary-period, sleep, steps, swim-lengths-data, time-in-heart-rate-zone, total-calories, vo2-max, weight. Other valid v4 kebab-case slugs are also accepted.steps
page_sizeNo
page_tokenNo
privacy_modeNoOptional per-call privacy override. Defaults to GOOGLE_HEALTH_PRIVACY_MODE or structured. raw returns upstream Google Health JSON.
response_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
endpointYes
privacy_modeYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false, making the tool's safety profile clear. The description adds no further behavioral context (e.g., rate limits, auth needs) but does not contradict annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no wasted words. First sentence states core purpose, second provides a concrete example. Fully front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Though an output schema exists (not shown), the description omits pagination details, filter syntax nuances, and privacy mode effects. Given the tool's complexity (6 parameters, pagination, filtering), the description is adequate but not comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50% (descriptions for filter, data_type, privacy_mode only). The description adds only a brief example for data_type, which is already well-documented in the schema. It does not compensate for the missing descriptions of page_size, page_token, and response_format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool queries detailed data points for a Google Health data type, with an example of kebab-case format. It distinguishes from similar tools like google_health_list_data_types, but could be more specific about the nature of 'detailed data points' (e.g., time series vs. aggregated).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides guidance on parameter format ('Use kebab-case endpoint data types') but lacks explicit when-to-use vs. alternatives. Siblings include data retrieval tools, but no guidance on selecting this one over google_health_data_inventory or google_health_data_type_coverage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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