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shkyyy18

Mi Fitness Data Bridge

by shkyyy18
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_data_coverage

Read-onlyIdempotent

Check cached health data coverage by dataset, showing date ranges with available records to determine if sync_data is needed before querying.

Instructions

Inspect which date ranges already exist in the local cache before choosing query dates or requesting sync_data. Returns data.coverage [{data_type, first_date, last_date, days_with_data}] for nonempty datasets; omitted/empty data_types means all datasets. Empty datasets are omitted, and first/last dates do not guarantee uninterrupted coverage between them. This does not test cloud connectivity or report a background job; use get_connection_status or get_sync_status respectively. Read-only local SQLite query; no cloud request or automatic sync. Requires a configured local account/cache. Returns JSON text with status, source=cache, generated_at and data; empty lists mean no cached matches, not zero measurements. Use sync_data to refresh with user consent.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
data_typesNoOptional dataset names to inspect; omit or [] for all cached datasets.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.3.2
    • addedInput schema / additionalProperties
      Added value: +false
    • addedInput schema / properties / data_types / description
      Added value: +"Optional dataset names to inspect; omit or [] for all cached datasets."
    • addedInput schema / properties / data_types / items / enum
      Added value: +[
+  "daily_activity",
+  "heart_rate",
+  "body_measurements",
+  "sleep",
+  "workouts",
+  "spo2",
+  "stress",
+  "abnormal_heart_beat"
+]
  2. First observedv0.3.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations declare readOnlyHint, idempotentHint, destructiveHint, openWorldHint. The description adds valuable behavioral context: read-only local SQLite query, no cloud request, requires configured account/cache, and important caveats about date coverage and empty-list meaning. It enhances rather than contradicts 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?

Every sentence earns its place: purpose, usage timing, exclusions, behavior, caveats, prerequisites, and return format are all covered without redundancy. It is front-loaded with the core purpose and then provides necessary details.

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?

Despite having only one optional parameter and no output schema, the description fully explains the return structure, meaning of empty lists, the non-guarantee of uninterrupted coverage, and the distinction from related tools. Nothing needed for correct invocation is missing.

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

Parameters3/5

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

Schema description coverage is 100% for the single data_types parameter, which already explains 'Optional dataset names to inspect; omit or [] for all cached datasets.' The description restates this in prose but adds no new semantic meaning beyond the schema, so the baseline of 3 applies.

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 states a specific verb 'Inspect' and resource 'date ranges in the local cache', and immediately differentiates from siblings by naming get_connection_status and get_sync_status for other concerns. It leaves no ambiguity about what this tool does.

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 explicitly states when to use ('before choosing query dates or requesting sync_data') and when not to use it, naming the exact alternatives for cloud connectivity and background job status. This is model usage guidance.

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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