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Read body measurement changes

get_body_measurements
Read-onlyIdempotent

Track how body measurements changed over a chosen period by returning first, last, and difference values per body part, including fat percentage.

Instructions

Read how the user's body measurements changed over a period: per body_part (neck, chest, waist, stomach, hips, thigh, calf, biceps, fat_percentage) the first and last value of the period (start_value, end_value) and the difference. Sizes are in the user's size unit (cm unless changed in the app), fat_percentage in %. Parts with nothing logged are left out. Pass from_date and to_date to choose the period; without them the server picks it. Body weight is get_weight_history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
to_dateNoDay as YYYY-MM-DD; when the user says today, yesterday, this week or a weekday, call get_today and count from its date.
from_dateNoDay as YYYY-MM-DD; when the user says today, yesterday, this week or a weekday, call get_today and count from its date.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
dataNo
errorNodescribe_error() of what went wrong; docs/AGENTS.md, Results and errors.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful behavior: units (cm unless changed in app, fat_percentage in %), the omission rule for parts with nothing logged, and the default-period fallback when dates are absent.

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?

Four compact sentences, front-loaded with the return shape and followed by the scoping parameters and the sibling pointer. Dense and mostly waste-free, though the body-part enumeration is long and edges toward schema duplication.

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?

An output schema exists, so return structure need not be re-explained, yet the description still supplies the unit conventions and the 'parts with nothing logged are left out' caveat that schemas typically miss. Nothing needed to call or interpret this tool correctly is missing.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning beyond the schema by explaining that from_date/to_date define the period and that omitting them makes the server choose the range. That behavior is not stated anywhere in the schema property descriptions.

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?

States a precise verb+resource ('read how the user's body measurements changed over a period') and enumerates the exact body parts and returned fields (start_value, end_value, difference). It is immediately distinguishable from raw-history siblings like get_measurement_history and from get_weight_history, which it names explicitly.

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?

Gives clear context: pass from_date/to_date to choose the period, otherwise the server picks it, and routes body weight to get_weight_history. It never explicitly contrasts with get_measurement_history (raw entries vs. period deltas), so the sibling-boundary is only partially drawn.

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