garminconnect-js

get_sleep_daily

Read-only

Fetches per-night sleep statistics for a date range, automatically chunking requests over 28 days and de-duplicating results.

Instructions

Per-night sleep stats over a date range; ranges over 28 days are fetched in chunks. Garmin's endpoint has a documented 28-day-per-request limit; ranges beyond that are auto-chunked, de-duplicated by calendarDate, and sorted.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "start": "<start>",
      "end": "<end>"
    },
    "name": "get_sleep_daily"
  }
}

Input Schema

Name	Required	Description	Default
`end`	Yes	Calendar date, YYYY-MM-DD (UTC)
`start`	Yes	Calendar date, YYYY-MM-DD (UTC)

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 15, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Annotations cover the safety profile (readOnly, openWorld), and the description adds genuinely useful operational behavior beyond them: the 28-day-per-request limit, automatic chunking, de-duplication by calendarDate, and sorting. It stops short of noting latency/rate implications of large ranges, but the disclosure is well above the annotation baseline.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core purpose, then the operational caveat. The chunking behavior is stated twice ('ranges over 28 days are fetched in chunks' and '28-day-per-request limit... auto-chunked'), which is mild redundancy but the sentences otherwise earn their place.

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?

For a read-only two-date-range tool with full schema coverage, complete annotations, and no output schema, the description is sufficient: an agent knows what it returns (per-night stats), what it accepts, and the range behavior. Only the relationship to get_sleep_data 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 coverage is 100% with both date parameters fully documented as YYYY-MM-DD UTC, so the schema carries parameter semantics. The description frames them as a date range but adds no format or edge-case detail beyond the schema, matching the baseline for high coverage.

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?

States a specific verb+resource+granularity: 'Per-night sleep stats over a date range.' The 'per-night' qualifier implies daily aggregation, which hints at differentiation from the sibling get_sleep_data, but that sibling is never named, so the distinction must be inferred.

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?

Usage is only implied through 'over a date range' plus the note that large ranges are chunked, which tells the agent it is safe to pass wide ranges. No when-to-use vs when-not, and the obvious alternative (get_sleep_data) is not mentioned, leaving selection to inference.

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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