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Check text for plagiarism

check_plagiarism

Plagiarism checker. Use when the user wants to know whether a text, such as an essay, research paper, thesis, article or blog post, copies or closely matches web sources. Starts a check in the background and returns a scan_id with status pending; the result is not in this reply. Then call get_scan_result with that scan_id. Uses one word from the user's balance for each word checked, so calling it again on the same text charges again. The text needs at least 30 words. If it is too short, too long for the user's plan, or the balance is too low, nothing is charged and the reply explains why. For likely AI writing, use detect_ai instead.

Input Schema

NameRequiredDescriptionDefault
textYesThe full text to check, as plain text. Send the whole passage the user wants checked, not a summary.
titleNoOptional label for this check in the user's reports.

Output Schema

NameRequiredDescriptionDefault
statusYes
scan_idYes
word_countNo
words_chargedNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Goes well beyond the annotations (readOnlyHint=false, openWorldHint=true, idempotentHint=false): it discloses that the work happens in the background, that the reply returns only a scan_id with status pending, that charges are per word and repeat on re-calls, and that short/oversized/insufficient-balance requests are not charged and return an explanation. That is exactly the cost and async-safety context an agent needs before invoking a billable mutation.

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?

Front-loaded with a one-line purpose, then usage, then async/cost behavior, then limits and the alternative. Six sentences, each carrying distinct actionable information with no restatement of schema or annotations.

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?

An output schema exists, so return structure need not be explained, and the description still flags the critical fact that the reply contains only a scan_id rather than the result. Combined with cost, limits, and the explicit follow-up tool, nothing an agent needs to call this correctly 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 already 100%, so the baseline is 3; the description adds a real constraint not in the schema - the text needs at least 30 words - plus the billing implication that each word checked consumes balance and re-running on the same text charges again. It does not explain the optional title parameter, keeping it just short of a 5.

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+resource: checks whether text 'copies or closely matches web sources', with concrete examples of text types. It also distinguishes itself from the sibling detect_ai, which handles AI-writing detection, so an agent can route without opening any schema.

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?

Explicitly gives the trigger ('use when the user wants to know whether a text... copies'), the exclusion ('for likely AI writing, use detect_ai instead'), and the follow-up step ('then call get_scan_result with that scan_id'). Alternatives and sequencing are fully spelled out.

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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