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Check a text for AI-sounding phrases

check_text
Read-onlyIdempotent

Run the writer linter behind mikefluff.com/ai-text-checker on a text: it flags the stock phrases and rhythms readers recognise as machine-written ("in today's fast-paced world", "it's important to note", em-dash habits in Russian) and returns a density verdict (clean / borderline / neuroslop suspected), a pass/fail gate for hard bans, and each hit with line, column, category and the matched words. English and Russian only. Up to 20000 characters. It judges the text, not who wrote it. Read-only: the text is not stored.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langYesLanguage of the text: en or ru.
textYesThe text to check (plain text or Markdown).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • removedInput schema / $schema
      Removed value: -"http://json-schema.org/draft-07/schema#"
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations already declare readOnlyHint/idempotent/non-destructive/closed-world, and the description still adds real behavioral context: the text is not stored, the exact tiers returned, the hard-ban gate, and the language and length limits. That is substantial disclosure beyond the structured fields.

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?

Front-loads the purpose before the output details, and every clause carries information. It is long and parenthetical, but the length is justified by enumerating the return shape rather than padding.

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 no output schema, the description carries the burden of describing returns and does so fully: verdict tiers, gate result, and per-hit fields. An agent knows what it gets back and what inputs are valid.

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% and the schema already documents both params including the enum. The description's 'English and Russian only' and 'up to 20000 characters' simply restate the enum and maxLength rather than adding syntax or format meaning.

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?

States a specific verb and resource ('run the writer linter ... on a text') and spells out the concrete output artifacts (density verdict, pass/fail gate, per-hit line/column/category). It is unmistakably distinct from every sibling, which are all book/call/answer tools.

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?

Gives clear conditions for use: English and Russian only, up to 20000 characters, judges the text rather than the author. It does not name an alternative tool or an explicit when-not-to-use, but with no relevant sibling there is nothing to route against.

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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