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Study Tools MCP

Study Tools MCP

by francis-rf
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

create_flashcards

Generate flashcards for any topic to aid study and review. Specify the number of cards for tailored learning.

Instructions

Generate flashcards for a topic

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": {
      "topic": "<topic>"
    },
    "name": "create_flashcards"
  }
}

Input Schema

NameRequiredDescriptionDefault
topicYes
num_cardsNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

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 full burden but only says 'Generate flashcards for a topic'. It does not disclose whether this creates new data, requires any permissions, or has side effects. The default number of cards (10) is not mentioned.

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 sentence, concise and front-loaded. However, it could include more useful information without significantly increasing length, such as mentioning the default number of cards or that output is structured.

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 low complexity and presence of an output schema, the description is too sparse. It omits behavioral traits, parameter details, and usage guidance, making it insufficient for reliable agent invocation despite the schema covering output structure.

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%, and the description does not elaborate on the parameters ('topic', 'num_cards') beyond their names. No details on format, constraints, or the meaning of 'num_cards' default are provided, leaving the agent to infer from parameter names alone.

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 'Generate flashcards for a topic' clearly states the verb (generate) and resource (flashcards) with a topic context, distinguishing it from sibling tools like create_quiz or summarize_topic. However, it lacks specificity on whether it generates from scratch or from existing content.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool vs alternatives like create_quiz or compare_two_concepts. There is no mention of prerequisites, exclusions, or contexts where other tools would be more appropriate.

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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