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kobaltgit

MCP Typography Audit Server

by kobaltgit

audit_typography

Renders HTML to check typography using Knuth–Plass line breaking, hyphenation, and microtypography; returns diagnostics and a screenshot for CSS refinement.

Instructions

Рендерит HTML-код, применяет Justif (алгоритм Кнута-Пласса) и возвращает скриншот с аудитом верстки

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
htmlYesHTML-код страницы или фрагмента статьи
langNoЯзык текста для правил переноса ('ru', 'en-us' и т.д.)ru
widthNoШирина экрана для проверки в пикселях (например, 375 для мобилки, 800 для планшета)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and it does disclose a useful processing pipeline (render, justify via Knuth-Plass, screenshot output). However, it omits important behavior: whether submitted HTML/scripts are executed, sandbox/permission requirements, latency, and what form the screenshot takes.

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?

A single front-loaded sentence that states the pipeline and the output with no filler. Every clause earns its place and the outcome (screenshot + audit) is stated first.

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?

There is no output schema, so the description must explain the return value; it states a screenshot with a layout audit is returned, but not the concrete form (URL, base64, image part) or contents of the audit. Combined with no annotations, the definition is adequate but leaves real gaps for an agent.

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 100%, so the schema already documents html, lang, and width with examples. The description adds no parameter meaning beyond the schema, so the baseline of 3 applies.

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 gives a concrete verb chain and resource: renders HTML, applies the Justif (Knuth-Plass) algorithm, and returns a screenshot with a layout audit. An agent can tell this is a typography/verstka auditing tool, though there are no siblings to differentiate it from.

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 guidance on when to use this tool, what prerequisites exist, or what alternatives it competes with. The description is entirely about internal processing rather than the conditions that select this tool.

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

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