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rollecode

Cronometer MCP server

by rollecode

get_daily_nutrition

Read-onlyIdempotent

Retrieve daily nutrition totals for every nutrient eaten on a specified date, including tracked and untracked values. Returns summary macros and per-nutrient amounts to assess intake against targets.

Instructions

Get daily nutrition totals for every nutrient eaten that day.

The response has:

  • summary: flat macro totals (energy, protein, carbs, net_carbs, fat, fiber, alcohol). A value is null if nothing that day contained it.

  • nutrients: each with id, name, amount, unit, category, confidence and tracked.

  • tracked_count and untracked_count.

tracked says whether that nutrient has a target set in Cronometer. Untracked nutrients are still eaten and still counted here; they simply have nothing to measure against, and Cronometer's own summary leaves them out. So an absent nutrient means none was eaten, rather than none being tracked.

Report an untracked amount as a plain figure. It has no target, so never describe it as over, under or on track, and offer set_nutrient_target if a target would be useful.

Args: date: Date as YYYY-MM-DD (defaults to today). include_untracked: Leave true for everything eaten. False restricts the response to nutrients with targets, matching the app's own summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dateNo
include_untrackedNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.9.2

TDQS

A4.8/5.0
Behavior5/5

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

The description adds significant behavior beyond annotations: it explains that null means nothing contained a nutrient, distinguishes 'untracked' from 'not eaten', and clarifies that Cronometer's summary excludes untracked nutrients. This is exactly the kind of contextual behavior an agent needs to interpret results correctly.

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 detailed but well-organized with a clear opening sentence, bulleted response structure, and a dedicated Args section. Every section adds meaningful information, and the most important behavioral caveat about untracked nutrients is given prominent treatment.

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 tool with two optional parameters and an output schema, the description covers all essentials: defaults, parameter effects, response fields, edge-case semantics, and reporting guidance. There are no meaningful gaps for an agent to misuse the tool.

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 must carry the full semantic burden. It does: date is specified as YYYY-MM-DD with a default of today, and include_untracked is explained with concrete consequences for the response. This fully compensates for the empty schema 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?

The first sentence states a specific verb and resource: 'Get daily nutrition totals for every nutrient eaten that day.' This clearly separates it from related tools like get_nutrition_scores and get_macro_targets by focusing on per-nutrient daily totals. The scope is unambiguous.

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 explains how to use the include_untracked parameter and when the false setting matches Cronometer's own summary. It also advises when to suggest set_nutrient_target. However, it does not explicitly name sibling tools as alternatives or state when not to use this tool.

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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