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tresor4k

macalc

calculate_fabric_needed

Calculate the fabric meters needed for sewing a garment. Input garment type, size, and fabric width to get the required meter amount.

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 provided, so description carries the burden. Describes computation and return (meters of fabric) but does not disclose assumptions (e.g., standard pattern efficiency, seam allowance, or waste). Behavior is simple and expected for a calculator, but more details would improve transparency.

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: first states core function, second guides to related tools. No fluff, front-loaded, efficient.

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?

Given the simple calculator nature (3 params, straightforward output), the description adequately covers purpose, inputs, and output. Output schema exists but is not provided; description implies meters. Could mention return unit or more edge cases, but sufficient for a basic tool.

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% with basic descriptions for each param. Description only lists inputs without adding extra meaning beyond schema. No elaboration on units or constraints, but baseline 3 is appropriate.

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?

Clear verb+resource: 'Compute fabric meters needed for a garment by pattern.' Specifies inputs and output. Mentions related 'textile-mode' calculators via list_bundles, but doesn't explicitly differentiate from siblings like calculate_fabric_yardage or calculate_curtain_fabric.

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?

States 'Use for sewing' as context, and directs to list_bundles for related tools. However, no explicit when-to-use or when-not-to-use guidance, nor comparison with alternatives. Usage is implied rather than explicit.

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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