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gpaul-mcp

Ravelry MCP Server

by gpaul-mcp

How much yarn to buy

yarn_needed
Read-onlyIdempotent

Calculate how many skeins to buy for a knitting or crochet pattern using Ravelry pattern yardage and yarn skein length, plus a safety margin. Adjust for gauge or size.

Instructions

Works out how many skeins to buy for a pattern with a given yarn, with a safety margin. Reads the yardage from a Ravelry pattern (smallest and largest size) and the skein length from a Ravelry yarn, or takes the numbers directly. Can account for a gauge difference or a bigger size (scale).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scaleNoMultiply the yardage, e.g. 1.15 for a bigger size or a looser gauge.
yarn_idNoThe yarn the user will use.
pattern_idNo
pattern_yardsNoTotal the pattern needs for the chosen size (meters: multiply by 1.094).
margin_percentNoSafety margin.
yards_per_skeinNo
meters_per_skeinNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
yarnYes
notesYes
optionsYes
patternYes
yards_per_skeinYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.8.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, openWorld, so safety is covered. The description adds useful context about data sourcing (Ravelry pattern/yarn vs direct numbers) and the safety-margin concept, but says nothing about edge cases or what happens when both direct numbers and IDs are supplied.

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 tightly packed sentences with no filler, and the core computation is front-loaded before the data-source and scale caveats.

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?

An output schema exists, so return values need not be explained. For a 7-parameter, all-optional calculator the description covers the dual input paths and scaling adequately; only the skein-length parameters and mutual exclusivity of inputs are left implicit.

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 57%, so the schema carries roughly half the load. The description clarifies the scale and pattern_yards intent, but largely restates the schema's own wording on scale, and never explains yards_per_skein vs meters_per_skein or the yarn_id/pattern_id pairing, leaving part of the gap unfilled.

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?

States a specific verb and resource: computing how many skeins to buy for a pattern with a given yarn, including a safety margin. The scope (skein count for purchasing) is distinct from siblings like convert_yarn_amount and adjust_for_gauge, though it never names an alternative to sharpen the boundary.

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?

It implies two input modes (pull yardage from a Ravelry pattern/yarn, or supply numbers directly) and mentions optional scale handling, which hints at when the tool applies. It gives no explicit when-not guidance and never routes the agent away from the closely related adjust_for_gauge or convert_yarn_amount siblings.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.