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partymola

google-health-mcp

health_get_cardio_fitness

Get cardio fitness (VO2 max) from Google Health. Define date range for cached weekly updates or request live data to re-fetch. Returns single value or range.

Instructions

Get Cardio Fitness Score (VO2 Max estimate).

Estimated from resting HR, HR during walks and runs, and demographics. Updates roughly weekly. Returns from cache by default, auto-syncing if stale.

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.

A reading usually carries a range or a single value; one re-synced across the switchover between providers can hold both. They are different measurements - do not average them together or fill one from the other. vo2_max_low and vo2_max_high are a reported band (e.g. 39-43); vo2_max is a single figure. All in mL/kg/min, higher being better cardiorespiratory fitness.

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?

No annotations exist, so the description must carry the burden. It discloses caching behavior, data freshness, the nature of the values (range vs single), and warns against averaging across sources. It also explains the re-fetch option. This is substantial transparency beyond the bare minimum.

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?

Efficient structure: purpose first, then derivation context, then caching, then parameters, then data interpretation. Each sentence adds value, no redundancy. Well-organized with clear sections.

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 that the output schema exists, the description doesn't need to list return fields, but it does explain the meaning of the values (range vs single, units) and warns against improper use. It also covers caching and refresh behavior. No annotations, so description carries full burden, and it does so admirably.

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 coverage is 0% (schema only says type string/null). The description fills in all gaps: date formats (YYYY-MM-DD, YYYY-MM, 30d), default behavior, and 'live' parameter meaning. It even explains the semantics of the returned values (which is beyond params).

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 tool retrieves Cardio Fitness Score (VO2 Max estimate) with specific derivation (HR, walks/runs, demographics). It distinguishes itself from sibling tools by specifying this is about cardio fitness/VO2 max, not general activity or heart rate.

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 explains when results are stale (weekly update) and how to force fresh data (live=true), but it doesn't explicitly compare to sibling tools or state when not to use it. Some implied guidance via the 'live' parameter but no clear alternatives or exclusions.

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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