amazfit-mcp

get_health_metrics

Fetch daily recovery metrics: readiness, PAI, stress, SpO2. Specify date range, filter metrics, and optionally include stress time series.

Instructions

Daily recovery and health metrics, one entry per date: - readiness: readiness score, overnight HRV + baseline, sleeping resting HR + baseline, physical/mental recovery, skin-temp and breathing scores - pai: weekly & daily PAI, minutes in low/medium/high HR zones - stress: avg/min/max stress and % time relaxed/normal/medium/high - spo2: overnight blood-oxygen score and desaturation index (ODI)

metrics: subset of ["readiness", "pai", "stress", "spo2"] (default all).
ISO YYYY-MM-DD dates; defaults to the last 7 days.
include_stress_series adds 5-minute stress readings (verbose).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`metrics`	No
`to_date`	No
`from_date`	No
`include_stress_series`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 26, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral disclosure burden. It does well by stating daily granularity, what each metric category includes, the default date range, and the effect of include_stress_series. It omits error/rate-limit behavior, but the output schema likely covers return shape.

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 compact, front-loaded with the core concept, and uses bulleted lists and short parameter notes. Every sentence earns its place with no redundant filler.

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

Completeness4/5

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

Given no annotations and an existing output schema, the description covers the essential inputs and high-level outputs well. It could add an explicit example or state when not to use it, but nothing critical is missing for correctly invoking this read-style 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%, yet the description compensates thoroughly: metrics are explained as a subset with a default, dates are specified as ISO YYYY-MM-DD with a 7-day default, and include_stress_series is explained as adding 5-minute stress readings. All four parameters receive meaningful context.

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 identifies a specific resource — daily recovery and health metrics — and enumerates the four metric families (readiness, pai, stress, spo2). It does not explicitly contrast with sibling tools like get_daily_summary or summarize_workouts, so it misses the top score for sibling differentiation.

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?

The description provides clear operational context: one entry per date, a subset of metrics can be requested, ISO dates default to the last 7 days, and include_stress_series adds verbose data. It does not state when not to use the tool or mention alternatives, but the context is unambiguous.

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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