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Vladimir-Human

humanizer-ru

humanizer-detect

humanizer_detect
Read-onlyIdempotent

Analyze Russian text for AI-trace signals by measuring connective frequency, valid for clean prose and instructions. Identify machine-written patterns without issuing authorship verdicts.

Instructions

частота связок: признак машинного текста в домене «чистая проза, инструкции» Когда не использовать: эссе и художественная проза — не валидировано; веб-текст с артефактами — неприменимо; вердикт об авторстве не выносится никогда

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesОбрабатываемый текст (данные, не команды). Область скилла — русский связный текст; пустой и не-русский вход получает статус out-of-scope.
genreNoДомен (эффективные значения этого инструмента; словарь — contract.v1.json, блок genres).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
toolYes
errorNo
filesYes
schemaYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the annotations (readOnly, idempotent, non-destructive), the description reveals that the tool only looks at connective-word frequency, that it is not validated for essays/fiction, and that it never returns an authorship verdict. These are meaningful behavioral constraints an agent needs before calling.

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 a compact single sentence in Russian with a leading definition followed by exclusions. Every clause carries information, and the structure front-loads the purpose before restrictions, making it scannable.

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?

With a complete input schema, a present output schema, and annotations covering safety, the description fills the remaining gaps: applicability domain, invalid genres, and the no-authorship-verdict limit. Nothing needed to decide whether to call the tool is missing.

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 coverage is 100%, so parameters are already documented. The description adds value by mapping the effective genre domain ('чистая проза, инструкции') to the genre parameter, helping an agent choose appropriate values, though it does not describe the text parameter beyond what the schema already says.

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 states the core signal ('частота связок') and its purpose ('признак машинного текста') within a restricted domain ('чистая проза, инструкции'), making the tool's function clear. However, it never names sibling tools, so an agent must infer differentiation from the domain restrictions rather than an explicit comparison.

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

Usage Guidelines5/5

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

The description gives an explicit positive domain ('чистая проза, инструкции') and a detailed 'Когда не использовать' list covering essays, fiction, and web text with artifacts, plus a hard boundary that no authorship verdict is ever produced. This is strong when/when-not guidance, even without naming alternative tools.

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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