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create_quiz

Create quizzes with multiple question types aligned to Bloom's taxonomy. Specify topic, difficulty, number of questions, and include answer key.

Instructions

Create a quiz with various question types aligned to Bloom's taxonomy.

Args:
    topic: Quiz topic
    num_questions: Number of questions (max 30)
    difficulty: Difficulty level: easy, medium, hard, mixed
    question_types: Types to include: multiple_choice, true_false, short_answer, fill_blank, matching
    age_group: Target age group
    include_answers: Include answer key

Behavior:
    This tool generates structured output without modifying external systems.
    Output is deterministic for identical inputs. No side effects.
    Free tier: 10/day rate limit. Pro tier: unlimited.
    No authentication required for basic usage.

When to use:
    Use this tool when you need structured analysis or classification
    of inputs against established frameworks or standards.

When NOT to use:
    Not suitable for real-time production decision-making without
    human review of results.
Behavioral Transparency:
    - Side Effects: This tool is read-only and produces no side effects. It does not modify
      any external state, databases, or files. All output is computed in-memory and returned
      directly to the caller.
    - Authentication: No authentication required for basic usage. Pro/Enterprise tiers
      require a valid MEOK API key passed via the MEOK_API_KEY environment variable.
    - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are
      included in responses (X-RateLimit-Remaining, X-RateLimit-Reset).
    - Error Handling: Returns structured error objects with 'error' key on failure.
      Never raises unhandled exceptions. Invalid inputs return descriptive validation errors.
    - Idempotency: Fully idempotent — calling with the same inputs always produces the
      same output. Safe to retry on timeout or transient failure.
    - Data Privacy: No input data is stored, logged, or transmitted to external services.
      All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
num_questionsNo
difficultyNomixed
question_typesNo
age_groupNo14-16
include_answersNo
api_keyNo
Behavior5/5

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

Given no annotations, the description fully covers behavioral traits: side effects (read-only, no modifications), authentication (no auth basic, API key for pro), rate limits (10/day free), error handling (structured errors), idempotency, and data privacy. This exceeds expectations.

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 well-structured with clear sections (Args, Behavior, When to use/not use, Behavioral Transparency). While slightly verbose, every section adds value, especially given the absence of annotations.

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?

Covers most aspects but lacks description of the return value format. For a quiz creation tool, specifying the output structure (e.g., JSON quiz object) would enhance completeness. No output schema is provided, so this omission is notable.

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?

The 'Args' section adds meaning beyond the input schema by listing allowed values for difficulty and question_types, default for num_questions, etc. However, the api_key parameter is mentioned in the behavioral section but not in the Args list, slightly reducing clarity.

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 clearly states 'Create a quiz with various question types aligned to Bloom's taxonomy,' which is a specific verb+resource. It distinguishes from sibling tools like analyze_student_progress or generate_lesson_plan, which have different purposes.

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?

Explicit 'When to use' and 'When NOT to use' sections provide guidance, though the 'When to use' text ('structured analysis or classification...') is somewhat generic and could be more directly tied to quiz creation. Still, it offers clear context and exclusions.

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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