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humanpen-mcp

humanpen-mcp

Official
by humanpen
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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Read an AI-detection report

read_detection_report
Read-only

Reads a Turnitin or iThenticate AI Writing report PDF to extract the overall AI percentage and flagged passages, so you can identify text for rewriting with humanize_document.

Instructions

Read a Turnitin or iThenticate AI Writing report PDF: returns the overall AI percentage and the flagged passages. Free - reads the file without starting a job. Pass the same report to humanize_document to rewrite only what was flagged.

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": {
      "report_path": "<report_path>"
    },
    "name": "read_detection_report"
  }
}

Input Schema

NameRequiredDescriptionDefault
typeNoWhich product exported it; omit to identify it from the file
report_pathYesAbsolute path to the report PDF
include_segmentsNoInclude the flagged passage texts, which can be long (default false)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the safety profile is covered; the description adds genuine context beyond that — the operation is free, does not start a job, and is the input to humanize_document. It stops short of describing failure modes for malformed or non-AI-writing PDFs, keeping it below a 5.

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?

Three short sentences, front-loaded with the verb, resource, and payload, then cost/side-effect, then the handoff to the sibling tool. No filler and nothing an agent needs is buried.

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

Completeness4/5

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 return-value burden and does so by naming the overall AI percentage and flagged passages. The one gap is error behavior for unreadable or unsupported PDFs, but for a simple read-only parse tool this is close to complete.

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 all three parameters (including the enum and the default-false include_segments) are already documented in the schema. The description mentions the return of flagged passages but adds no format or syntax detail beyond the schema, so baseline 3 applies.

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 ('Read a Turnitin or iThenticate AI Writing report PDF') and explicitly lists the return payload: overall AI percentage and flagged passages. This is clearly distinguishable from siblings like humanize_document or check_job.

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 notes 'Free - reads the file without starting a job,' which tells the agent no job/credit path is involved, and it names the downstream alternative: pass the same report to humanize_document to rewrite only flagged content. Both when-to-use and what-to-do-next are stated.

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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