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Glama

get_daily_summary

Read-only

Retrieve daily health metrics—steps, calories, resting heart rate, Body Battery, and stress—to identify what drained energy or caused stressful spells on a given day.

Instructions

Daily health summary: steps, calories, resting heart rate, body battery and stress.

With what charged or drained Body Battery and the longest stressful spells: "why is my Body Battery low", "when was I stressed".

Args: date: Day to report on. YYYY-MM-DD, 'today', 'yesterday' or an offset like '-3'. Defaults to today.

Input Schema

NameRequiredDescriptionDefault
dateNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.1.1
    • removedInput schema / properties / date / title
      Removed value: -"Date"
    • removedInput schema / title
      Removed value: -"get_daily_summaryArguments"
    • removedOutput schema / title
      Removed value: -"get_daily_summaryDictOutput"
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the analytical content of the response – body-battery charge/drain drivers and longest stressful spells – which is behavioral detail annotations cannot express. An output schema exists, so no penalty for not detailing the return shape further.

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 resource and metric list, then use cases, then an Args block – a clean structure with no filler. The mid-sentence fragment "With what charged or drained Body Battery and the longest stressful spells" is slightly clunky but still short.

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?

For a single-optional-parameter read tool with full annotations and an output schema, everything an agent needs is present: what it returns, when to reach for it, and exactly how to format the date argument. No material gap remains.

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%, so the description carries the full burden, and it does: the accepted formats (YYYY-MM-DD, 'today', 'yesterday', offset like '-3') plus the default of today are all stated. This goes well beyond the bare string/null schema and removes any ambiguity about valid input.

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 first line names the resource precisely (daily health summary) and enumerates the exact metrics returned: steps, calories, resting heart rate, body battery and stress. That enumeration lets an agent separate it from siblings such as get_heart_rate, get_readiness, get_sleep_data and get_recovery_trends without opening any schema.

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 quoted user questions ("why is my Body Battery low", "when was I stressed") give concrete trigger scenarios, which is real usage guidance. It stops short of naming an alternative or an exclusion, so an agent must infer whether to prefer this over get_heart_rate for a heart-rate question.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.