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Canada's Food Guide MCP Server

Canada's Food Guide MCP Server

Get Pal Descriptions

get_pal_descriptions

Get explanations and practical examples for Physical Activity Level (PAL) categories to help users choose the right activity level for accurate EER calculations.

Instructions

Get descriptions and examples for Physical Activity Level (PAL) categories.

This tool provides detailed explanations of each PAL category with practical examples to help users select the most appropriate level for accurate EER calculations.

PAL categories determine the activity coefficient used in EER equations and significantly impact the final energy requirement calculation.

Use this tool when:

  • Helping users choose appropriate activity level

  • Understanding PAL category definitions

  • Educational purposes about physical activity

  • Reviewing activity level options before profile creation

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

A4/5.0
Behavior4/5

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

No annotations are supplied, so the description must carry the behavioral load, and it does: it is a read-only reference lookup with no inputs and returns explanations plus practical examples. It does not discuss output format or how many categories are returned, but the output schema covers return values, so the remaining gap is small.

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?

Purpose is front-loaded in the first line, followed by useful context on why PAL matters, then a scannable bullet list. A couple of bullets ('Educational purposes about physical activity') are slightly fluffy, but nothing is redundant enough to hurt.

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?

For a zero-parameter reference tool with an output schema, the description supplies the needed context: what PAL categories are, why they matter for EER, and when to consult them. Complete enough to invoke confidently.

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 takes zero parameters, so the baseline is 4; there is no parameter meaning for the description to add. It correctly implies a parameterless, enumerate-everything lookup.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Get descriptions and examples for Physical Activity Level (PAL) categories.' It also frames the downstream purpose (EER activity coefficients), so an agent can distinguish this reference tool from calculation tools like get_eer_equations. It stops short of explicitly naming a sibling to contrast against, so a 4 rather than a 5.

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?

An explicit 'Use this tool when' list covers four concrete scenarios (choosing activity level, understanding definitions, education, reviewing options before profile creation). That is clear positive guidance, but there is no statement of when NOT to use it or which alternative to pick for adjacent needs.

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