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nmassi

glyphs-mcp

by nmassi

get_recipe

Retrieve a named workflow recipe with step-by-step instructions and total step count. Enables executing each step sequentially in GlyphsApp.

Instructions

Get a specific workflow recipe by name.

Returns the full recipe with step-by-step instructions, plus totalSteps count. Use get_recipe_step() to read and execute one step at a time.

Args: name: Recipe name (from list_recipes, e.g. 'scale_proportions')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A4.4/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of explaining behavior. It clearly states that the tool returns the full recipe plus totalSteps count but does not mention error handling, permissions, or side effects. For a simple read operation, this is adequate but not rich.

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?

The description is compact and front-loaded with the core purpose, followed by return-value behavior and a clear parameter explanation. Every sentence contributes value, and the Args section is clearly structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

This is a simple one-parameter getter with an output schema, and the description covers the essential context: what the tool returns, how to use the parameter, and when to choose the sibling tool. Nothing needed for correct invocation is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, but the description fully compensates by explaining that 'name' is a recipe name from list_recipes and providing the example 'scale_proportions'. This gives the agent everything it needs to construct a valid invocation.

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 states 'Get a specific workflow recipe by name', using a specific verb and resource. It also differentiates itself from get_recipe_step by noting it returns the full recipe, and from list_recipes by focusing on a single named recipe.

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

Usage Guidelines4/5

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

The description explicitly points to get_recipe_step() for reading and executing one step at a time, implying that get_recipe is for retrieving the full recipe at once. It also directs the agent to list_recipes as the source for valid recipe names, which is practical usage guidance.

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