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get_sleep_summary

Retrieve a concise sleep summary for a given date, returning only essential metrics in a lightweight format to avoid overwhelming context, ideal for daily health checkups and LLM integrations.

Instructions

Get sleep summary with only essential metrics (lightweight version)

This endpoint returns a compact summary of sleep data (~350 bytes) instead of the full granular data (~50KB). Ideal for daily health checkups and LLM integrations where the full time-series data would overwhelm the context window.

Args: date: Date in YYYY-MM-DD format

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": {
      "date": "<date>"
    },
    "name": "get_sleep_summary"
  }
}

Input Schema

Name	Required	Description	Default
`date`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 4, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It states that the endpoint returns a compact summary rather than full time-series data, which is a meaningful behavioral trait. It also explains the payload size tradeoff. It does not mention error behavior or auth, but for a simple read-only getter this is reasonably transparent.

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 and front-loaded: the first line states the purpose and the lightweight nature, followed by a clear use-case sentence and a minimal Args section. Every sentence adds useful information without redundancy.

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?

The tool is simple with one required parameter and an output schema present, so return-value documentation is already covered. The description covers the key tradeoff and parameter format. It could optionally point to get_sleep_summary_range for multi-day needs, but that is not essential for this endpoint's daily-summary purpose.

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

Parameters4/5

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

The schema provides no description for the date parameter (0% coverage), but the description compensates by specifying 'Date in YYYY-MM-DD format.' This adds concrete format guidance beyond the schema's bare string type, though it does not elaborate on timezone or edge-case semantics.

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 verb 'Get', the resource 'sleep summary', and the key differentiator: 'only essential metrics (lightweight version)' versus full granular data. It also quantifies the difference (~350 bytes vs ~50KB), making it easy for an agent to distinguish this from get_sleep_data.

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 gives a clear usage context: 'Ideal for daily health checkups and LLM integrations where the full time-series data would overwhelm the context window.' It implies the alternative is the full-granularity endpoint, though it does not explicitly name get_sleep_data or get_sleep_summary_range as alternatives.

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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