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tresor4k

macalc

calculate_glycemic_load

Calculate glycemic load per food and total for a meal. Obtain GL values with thresholds to assess blood sugar impact and support dietary planning.

Instructions

Calculate glycemic load (GL) per food and total for a meal. Returns: {thresholds}. See list_bundles for related 'cuisine' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
foodsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultNoComputed result. Object whose fields depend on the tool (e.g. {tax, marginal_rate, brackets} for tax tools, {volume_l, gallons} for volume tools).
formulaNoHuman-readable formula or method used (e.g. "I=P·r·t", "Magnus formula").
sourceNoAuthoritative source for the rule or formula (e.g. "Article 197 CGI", "NF DTU 21").
reference_urlNoLink to a calcul2 page documenting the calculation in detail.
Behavior2/5

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

With no annotations, the description carries full burden. It mentions returns thresholds but does not disclose any behavioral aspects like side effects, prerequisites, or limitations beyond a vague output hint.

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?

Two compact sentences with no fluff. The first sentence delivers the core purpose, and the second provides a useful cross-reference. Could be slightly improved by front-loading key details.

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?

Given an output schema exists, the description can be brief. However, it omits parameter descriptions and usage contexts, which are critical for correct invocation, making it moderately incomplete.

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

Parameters2/5

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

Schema description coverage is 0% and the description adds no meaning to parameters beyond listing the tool's purpose. It does not explain what GI, carbs_g, portion_g represent or their constraints, leaving the agent to infer from field names.

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?

Clearly states it calculates glycemic load per food and total for a meal, distinguishing from sibling tools by specifying the scope and referencing related cuisine calculators via list_bundles.

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?

Provides a minimal hint to see list_bundles for cuisine calculators, but does not explicitly state when to use this tool vs alternatives or when not to use it.

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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