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andronaft

health-os

save_meal_template

Idempotent

Save a reusable meal template for meals you eat often, so you can log them later in one call instead of re-entering data.

Instructions

Save (or overwrite) a reusable template for a meal eaten often, so it can later be logged in one call with log_from_template. name: short unique key (e.g. "oatmeal"); meal_type: breakfast / lunch / dinner / snack / drink; description: what it contains; nutrients: {nutrient_code: amount} for ONE portion, same codes as log_meal (energy_kcal, protein, fiber, sodium, vitamin_c, …); glycemic_index: optional. See list_meal_templates for existing ones.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
meal_typeNo
nutrientsNo
descriptionNo
glycemic_indexNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true and destructiveHint=false, and the description reinforces this with '(or overwrite)', so the agent understands repeated saves replace rather than duplicate. It also adds a genuinely useful data semantic — nutrients are for ONE portion — that no annotation conveys. Auth requirements and error behavior are not covered.

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-loads the purpose before walking through parameters, and every clause adds information an agent needs (overwrite behavior, per-portion units, example values). It is dense but could be trimmed marginally in the nutrients enumeration.

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?

A mutation tool with an output schema, so return values need not be described. The annotations cover the safety/idempotency profile, and the description fills the 0%-coverage parameter gap completely, including the nutrient code schema and portion basis.

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 does so well: it defines 'name' as a short unique key with an example, enumerates meal_type values, explains nutrients as a {nutrient_code: amount} map per portion with sample codes, and marks glycemic_index as optional.

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 specific verb and resource ('Save (or overwrite) a reusable template for a meal') and clarifies the create-or-update semantics. It distinguishes itself from siblings by naming log_from_template and list_meal_templates and explaining their relationship.

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 for when to use it ('a meal eaten often, so it can later be logged in one call with log_from_template') and points to list_meal_templates for existing templates. It stops short of explicit when-not-to-use guidance, but the routing between the three template-related tools is clear.

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