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nmassi

glyphs-mcp

by nmassi

check_language_support

Check the active Glyphs font's language support by exporting a temporary binary and running Shaperglot, then review supported languages or detailed per-language scores and warnings.

Instructions

Check the open font's language support with Shaperglot.

Exports a temporary binary from the active Glyphs font, then runs Shaperglot against it. With no languages provided, returns the languages whose score meets support_threshold. With languages, returns per-language scores plus warnings/failures.

Args: languages: Optional language IDs or names, e.g. ["en_Latn", "Turkish", "Navajo"] instance_name: Optional Glyphs instance name to export. Empty = first exportable instance. export_format: "otf" (default) or "ttf" support_threshold: Minimum score to count a language as supported in report mode max_results: Max languages to show in report mode

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languagesNo
max_resultsNo
export_formatNootf
instance_nameNo
support_thresholdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that it 'Exports a temporary binary from the active Glyphs font' and runs Shaperglot, which is a side effect. It also describes the two output modes. However, it does not explicitly state whether the tool modifies the font or is read-only, nor does it mention any permissions or rate limits. The temporary binary disclosure is useful, but more detail on side effects would be expected for a tool with zero annotation coverage.

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

Conciseness4/5

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

The description is well-structured: a one-sentence purpose, a two-sentence process explanation, and a bulleted Args section. It is front-loaded with the purpose and the key behavior. It is not overly verbose; every sentence contributes to understanding. The structure is clean and scannable, earning a high score for conciseness.

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 complexity (5 parameters, no annotations, output schema present), the description is quite complete. It explains the process (temp export, Shaperglot run), the two modes, and parameter details. It does not explain return values, but the output schema exists, so that is acceptable. It covers prerequisites implicitly (open font) and describes the threshold behavior. Minor gaps include potential error handling and installation requirements, but these are not critical for basic usage.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must compensate. It does so with an Args section that explains each of the 5 parameters: languages, instance_name, export_format, support_threshold, and max_results. It provides types, defaults, and examples (e.g., 'en_Latn', 'Turkish', 'Navajo'). This adds meaning beyond the schema, though some parameters like support_threshold and max_results could use more context about how they affect the output. Overall, the description effectively documents the parameters.

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?

The description opens with a clear verb+resource: 'Check the open font's language support with Shaperglot.' It is specific about the tool's purpose and mentions the underlying mechanism (Shaperglot). It does not explicitly differentiate from sibling check tools like check_glyphset_coverage, but the unique focus on language support is evident. The description distinguishes between two modes (with/without languages), adding clarity.

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?

The description explains what the tool does and how it behaves in two modes, but it does not provide explicit guidance on when to use this tool versus alternatives, nor any exclusions. Usage is implied by the purpose ('check language support'), but there is no mention of alternatives or when not to use it. This leaves the agent to infer context from the tool name and siblings.

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