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Hemosoo

learning-tool-mcp

by Hemosoo

ingest_material

Store a PDF's text as structured study material, returning document ID, title, and concept count. Retrieve the stored content next to generate flashcards or quizzes.

Instructions

Ingest a PDF and store its text as study material. Returns document_id, title and concept_count. Call get_material next to read the stored material before generating any flashcards or quiz questions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNo
pdf_pathYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral burden. It discloses that the operation persists the PDF's text as study material, returns document_id/title/concept_count, and positions get_material as the next read step. It does not cover error cases, duplicates, or permissions, but the core side effect and expected output are explicit.

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 two sentences with no filler. The core action is front-loaded, followed by return values and a concrete next-step instruction. Every sentence earns its place.

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

Completeness3/5

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

An output schema is present, so return-value details are partially covered elsewhere, and the description adds valuable storage and next-step context. However, with no annotations and 0% schema description coverage, the missing input semantics around title and pdf_path leave the definition incomplete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description should compensate by explaining pdf_path and the optional title parameter. It mentions 'PDF' and title only as a return value, not as input semantics, and never clarifies that title is an optional label or how pdf_path should be supplied.

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?

The description states a specific action and resource: 'Ingest a PDF and store its text as study material.' It also names the return values, making the tool's function distinct from read/list/save siblings like get_material, list_documents, and save_flashcards.

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?

The description gives clear workflow context by telling the agent to call get_material next before generating flashcards or quiz questions. It does not explicitly state when not to use this tool or compare it to alternative ingestion/listing tools, so it falls just short of full exclusion guidance.

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