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tresor4k

macalc

calculate_fabric_needed

Calculate fabric meters required for sewing a garment based on garment type, size, and fabric width. Get precise fabric needs for shirt, pants, dress, or curtains.

Instructions

Compute fabric meters needed for a garment by pattern. Use for sewing. Inputs: garment type, size, fabric width. Returns meters of fabric. See list_bundles for related 'textile-mode' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
garment_typeYesGarment type
sizeYesGarment size
fabric_width_cmYesFabric roll width cm

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.
Behavior3/5

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

No annotations are provided, so the description carries full burden. It states the tool computes fabric meters and returns the result, but does not disclose any behavioral traits such as edge cases, limitations (e.g., only standard pattern formulas), or side effects. The description is minimally adequate but lacks richness.

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?

Two sentences that are front-loaded with the core purpose. Every sentence earns its place; no filler or repetition.

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 simple tool with 3 parameters (all required, 2 enums) and an output schema, the description covers the basic usage. It could mention that the calculation uses specific pattern formulas or standard industry averages, but overall it is sufficient for an agent to understand and invoke correctly.

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 100%, so the descriptions for each parameter are already in the schema. The tool description merely lists the input fields without adding extra meaning beyond the schema. Baseline of 3 is appropriate.

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 the tool's purpose: 'Compute fabric meters needed for a garment by pattern. Use for sewing.' It specifies verb (compute), resource (fabric meters), and domain (garment by pattern). It also distinguishes from siblings by referencing list_bundles for related 'textile-mode' calculators.

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

Usage Guidelines5/5

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

The description explicitly says 'Use for sewing' and directs to list_bundles for related calculators, providing clear guidance on when to use this tool and alternatives.

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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