Skip to main content
Glama
tresor4k

macalc

calculate_knitting_yarn

Calculate yarn needed for knitting scarves, hats, sweaters, blankets, or socks. Returns meters and number of 50g/100m balls based on size (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.
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic function and return format, but does not explain the calculation method, assumptions, or any side effects. This is insufficient for a tool with no annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, consisting of one clear sentence and a reference. However, it is too brief and lacks structured detail, such as parameter explanations or usage context. It is front-loaded with purpose and output but omits essential information.

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 the tool's low complexity (2 enum parameters, no annotations, no output schema), the description is minimally viable. It states the core function and output, but lacks usage guidelines and parameter semantics, making it only partially complete for effective agent use.

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?

The input schema has 2 required enum parameters (project and size) with 0% schema description coverage. The description does not explain what these parameters mean or how they influence the calculation. It only mentions the output, failing to add meaning beyond the schema.

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: calculate yarn needed for a knitting project, specifying output in meters and number of 50g/100m balls. It also references list_bundles for related calculators, helping distinguish from the numerous sibling calculate_* tools.

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

Usage Guidelines2/5

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

The description does not provide explicit guidance on when to use this tool versus alternatives. It only references list_bundles for related calculators, but does not specify why one would choose this tool over others 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.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tresor4k/macalc-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server