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partymola

google-health-mcp

health_get_sleep

Retrieve nightly sleep data including duration, stages, and efficiency. Specify a date range to analyze sleep patterns or fetch the latest API data for updated records.

Instructions

Get nightly sleep data (duration, stages, efficiency).

Returns sleep data from the local cache by default. Use live=True to fetch from the API. Run health_sync first to populate the cache.

Sleep data is sparse: only nights with watch-tracked sleep are present. Travel, off-wrist nights, or manual logs may be missing.

Args: start_date: Start date as "YYYY-MM-DD", "YYYY-MM", or "30d". Default: last 30 days. end_date: End date as "YYYY-MM-DD". Default: today. live: If true, re-fetch this window from the API before reading the cache.

Returns one entry per night with total_minutes, efficiency, start/end times, and stage breakdown (deep, light, REM, wake minutes).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
liveNo
end_dateNo
start_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description takes on full responsibility for behavioral disclosure. It explains the default cache-read behavior, the live fetch option, and the sparse nature of sleep data (missing nights due to travel, off-wrist, or manual logs). This is significant contextual information beyond a simple 'get' operation, though it doesn't mention auth or rate limits.

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?

The description is appropriately structured: a brief summary sentence, then succinct optional details on cache/live behavior and data sparsity, followed by parameter documentation and return description. Every sentence adds value, and it remains compact despite covering edge cases.

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

Completeness5/5

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

Given the output schema exists, the description still adds meaningful details about return contents (total_minutes, efficiency, start/end times, stage breakdown) and the cache/live data flow. It covers prerequisites, data quality caveats, and parameter formats, making it complete for a data retrieval tool.

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

Parameters5/5

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

Schema description coverage is 0%, and the description fully documents all three parameters: start_date formats ('YYYY-MM-DD', 'YYYY-MM', '30d'), end_date format and default, and live as a boolean controlling API re-fetch. This completely compensates for the minimal schema.

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

Purpose5/5

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

The description clearly states it retrieves nightly sleep data including duration, stages, and efficiency. The verb 'Get' and resource 'nightly sleep data' are specific, and the scope is unambiguous, distinguishing it from sibling health_get_* tools.

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

Usage Guidelines4/5

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

Provides explicit usage context: default reads from local cache, live=True fetches from API, and health_sync must be run first to populate the cache. It also notes data sparsity conditions. However, it does not explicitly mention alternatives or exclusion criteria, though the tool name and sibling list make the domain clear.

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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