Cronometer MCP

list_nutrients

Read-onlyIdempotent

List every nutrient add_custom_food accepts, with units and categories, so you can build correct nutrient dictionaries for custom foods.

Instructions

Every nutrient add_custom_food accepts, with its unit and category.

Read from the account's own catalog, so it stays right as Cronometer adds nutrients. Use the returned keys for the add_custom_food nutrients dict.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "list_nutrients"
  }
}

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.1.0Nov 14, 2026

TDQS

A4.5/5.0

Behavior4/5

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

The description adds useful behavioral context beyond the annotations: it reads from the account's own catalog and stays current as Cronometer adds nutrients. This informs the agent that results may change over time and are account-specific. Annotations already cover read-only, open-world, and idempotent behavior, so the added context is a meaningful bonus.

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?

Three concise sentences with no wasted words. The core purpose is first, followed by useful context and a direct usage instruction. Every sentence earns its place.

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?

With no parameters, an output schema present, and annotations covering safety and idempotency, the description fully equips an agent to call the tool correctly and use its results. There are no meaningful gaps.

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 tool has zero parameters, so there is nothing for the description to clarify. This is an appropriate baseline score for a parameterless tool.

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 what the tool does: it lists every nutrient that add_custom_food accepts, including unit and category. It differentiates itself from sibling tools like list_custom_foods by scoping the output to nutrients accepted by add_custom_food.

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?

It explicitly instructs the agent to use the returned keys for the add_custom_food nutrients dict, which establishes a clear use case. It does not explicitly mention when not to use it or name alternatives, but its purpose is distinct enough among siblings.

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

Deploy Server