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Kydaix

Font Design MCP

by Kydaix

font_analyze

Analyze font outlines, ink, design rules, stroke profiles, spacing, and interpolation to detect coverage gaps and return localized candidates before export.

Instructions

Check visible ink, matching outlines and self crossings by default; measure declared design rules, normal stroke/counter profiles, smooth joins, digit spacing and required coverage. Rules accept master_id or a variable location; variation_profiles measure normal-width progression. interpolation=true adds timed source correspondence and compiled axis-grid checks. Returns regional coverage and localized candidates, not artistic approval. Full reports include measurements and evidence_plan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNosummary
revisionNo
master_idNodefault
project_idYes
interpolationNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
dataNo
errorNo
changedNo
summaryYes
revisionNo
warningsNo
project_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.6.0
    • addedInput schema / properties / interpolation
      Added value: +{
      +  "default": false,
      +  "type": "boolean"
      +}
  2. Addedv0.5.0

TDQS

C2.8/5.0
Behavior3/5

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

Annotations (readOnlyHint=false, destructiveHint=false, idempotentHint=false, openWorldHint=false) already convey the safety/idempotency profile. The description adds useful behavioral context the annotations lack: what is checked by default, what interpolation adds, and that the output is 'regional coverage and localized candidates, not artistic approval' with 'measurements and evidence_plan'. It does not explain why the operation is non-read-only/non-idempotent (likely report generation), leaving a gap.

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?

It is compact and avoids padding, and the default checks are front-loaded. But the semicolon-packed, jargon-heavy prose is hard to parse and buries the top-level purpose, so the structure does not maximize clarity per token.

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?

An output schema exists, so return values need not be re-explained, and the description covers several behavioral/parameter facets. Still, with 5 parameters at 0% schema coverage, no usage routing among siblings, and no explanation of the non-read-only nature, it is only adequately complete.

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 description coverage is 0%, so the description must carry the load: it adds meaning for master_id ('Rules accept master_id or a variable location') and for interpolation ('adds timed source correspondence and compiled axis-grid checks'), and indirectly for detail ('Full reports include...'). It says nothing about revision or project_id, so compensation is only partial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names concrete check categories ('visible ink', 'matching outlines', 'self crossings', 'digit spacing') and implies an analysis/QA role over a font project, so the general purpose is inferable. However it never states plainly what resource is being analyzed or how it differs from siblings like font_validate or font_release_check, and the dense jargon obscures the core purpose.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. The only conditional language ('by default', 'interpolation=true adds...') describes parameter behavior rather than the choice between this tool and its siblings.

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