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partymola

google-health-mcp

health_get_irregular_rhythm

Retrieve watch-detected irregular heart rhythm notifications with start/end times and alert windows. See possible atrial fibrillation episodes for review—not a medical diagnosis.

Instructions

Get irregular heart rhythm notifications raised by the watch.

These are background checks the watch runs while the user is still - an alert means it saw a rhythm consistent with atrial fibrillation over one or more windows, not a diagnosis. Most accounts never have one. For a deliberate reading with a trace behind it, use health_get_ecg.

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 notification with start_time, end_time and alert_windows (the periods that triggered it).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
liveNo
end_dateNo
start_dateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently explains that alerts are not a diagnosis, describes the nature of the data (background checks), explains the 'live' parameter's cache behavior, and describes the return structure. No contradictions exist.

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 well-organized with clear sections, each sentence serving a purpose. It opens with a clear purpose statement, then provides contextual guidance, parameter details, and return info. No fluff or redundancy.

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 tool's moderate complexity (3 params, output schema present), the description is complete. It covers the operational context, parameter semantics, and even describes the return format despite the output schema existing. It's both sufficient and effective.

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%, so the description must compensate. It provides detailed semantics for all three parameters: start_date format and default, end_date format and default, and live's purpose. It also clarifies the return fields. This adds significant meaning beyond the generic schema titles.

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 the action: 'Get irregular heart rhythm notifications raised by the watch.' It also distinguishes from sibling health_get_ecg by specifying that ECG is for a deliberate reading with a trace, whereas this tool retrieves background checks. This makes the purpose specific and unambiguous.

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

Usage Guidelines5/5

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

It provides explicit context on when to use: these are background checks, not a diagnosis, and most accounts never have one. It also explicitly directs to use health_get_ecg for deliberate readings. Parameter usage is explained with defaults and formats, leaving no ambiguity for the agent.

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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