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tresor4k

macalc

calculate_knitting_yarn

Calculate yarn required for knitting projects: get meters and number of 50g/100m balls for scarves, hats, sweaters, blankets, and socks in sizes S, M, L.

Instructions

Calculate yarn needed for a knitting project (meters and number of 50g/100m balls). Returns: {meters_of_yarn, balls_50g_100m}. See list_bundles for related 'textile-mode' calculators.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectYes
sizeYes

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 present, so description carries full burden. It discloses output format but does not mention side effects, determinism, or any limitations beyond the schema.

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, front-loaded with purpose and output format, no wasted words. Highly concise.

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 tool's low complexity (2 enums, output schema hinted), the description is adequate. It covers purpose and return format but lacks edge cases or additional context.

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 coverage is 0%, so description should add meaning. It does not describe the two parameters (project, size) beyond the enum values in the schema, adding no additional semantics.

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?

Description clearly states 'calculate yarn needed for a knitting project' with specific verb and resource, and explicitly lists the return format. It distinguishes from siblings by being knitting-specific and referencing list_bundles for related calculators.

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?

Description mentions 'See list_bundles for related textile-mode calculators' which hints at alternatives but does not explicitly state when to use this tool vs others.

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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