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Record Plagiarism Result

record_plagiarism_result

Logs plagiarism and AI detection scores for a content chunk within a session, capturing the checking tool used and any additional notes.

Instructions

⭐ USER records results from external plagiarism check

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "session_id": "<session_id>",
      "chunk_id": "<chunk_id>",
      "plagiarism_score": "<plagiarism_score>",
      "ai_detection_score": "<ai_detection_score>",
      "tool_used": "<tool_used>"
    },
    "name": "record_plagiarism_result"
  }
}

Input Schema

Name	Required	Description
`notes`	No	Additional observations
`chunk_id`	Yes	Which chunk was checked
`tool_used`	Yes	Name of tool used
`session_id`	Yes	Active session ID
`plagiarism_score`	Yes	Percentage (0-100)
`ai_detection_score`	Yes	Percentage (0-100)

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

C2.7/5.0

Behavior2/5

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

With no annotations, the description carries the full burden of behavioral transparency. It only states that results are recorded, but does not disclose side effects (e.g., whether it appends or overwrites), potential errors, permissions, or any other behavioral aspects beyond the basic action.

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?

The description is a single, concise sentence that front-loads the core action. It is appropriately sized for a simple record operation, though it lacks some detail that could be included without becoming verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's role within a larger workflow (evidenced by numerous sibling tools), the description lacks contextual information about how this fits into the process. It does not explain the purpose of recording results, how they will be used later, or any dependencies, making it incomplete for a user unfamiliar with the overall system.

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%, with each parameter having its own description. The tool description adds no additional parameter-specific meaning, but since the schema is complete, the baseline score of 3 is appropriate.

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 clearly states the action ('records') and the resource ('results from external plagiarism check'), providing a specific verb-object pair. It implicitly distinguishes from sibling tools like 'prepare_plagiarism_chunks' (preparation) and 'get_plagiarism_summary' (retrieval), though no explicit comparison is made.

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

Usage Guidelines1/5

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

There is no guidance on when to use this tool versus alternatives. The description does not mention any conditions, prerequisites, or scenarios where this should be invoked, leaving users to infer context from the sibling tool list.

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