Skip to main content
Glama
andronaft

health-os

log_from_template

Log a frequent meal from a saved template in one call, scaling nutrients by portion factor and recording eaten time, symptoms, or wellbeing.

Instructions

Log a meal from a saved template (nutrients × portion_factor). eaten_at=ISO (default — now). Quick entry of frequent meals in one call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
eaten_atNo
symptomsNo
wellbeingNo
portion_factorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations cover the safety profile (not read-only, not idempotent, not destructive), so the description only needs to add context. It discloses the portion scaling semantics and that eaten_at defaults to now, but says nothing about what happens when the template name doesn't exist or whether logging is reversible.

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?

Three dense clauses with no filler, and the core action is front-loaded. The parenthetical multiplication is compact and informative rather than bloated.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists so return values need no explanation, and the write semantics are covered by annotations. Still missing the failure mode for an unknown template name and the timezone/format expectation for eaten_at.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description carries the burden and only partially compensates: it explains portion_factor as a multiplier and eaten_at as an ISO timestamp defaulting to now, but leaves symptoms and wellbeing entirely undefined in both schema and description.

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?

States a specific verb and resource ('Log a meal from a saved template'), and the parenthetical '(nutrients × portion_factor)' clarifies the computation. The 'from a saved template' qualifier implicitly separates it from log_meal and save_meal_template, though neither sibling is named explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Quick entry of frequent meals in one call' implies the intended use case (repeat meals) but never states when to prefer this over log_meal or how to discover valid template names via list_meal_templates. Usage is inferable but not spelled out.

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