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get_cmpp_practice_questions_prompt

Generate CMPP certification exam practice questions with detailed explanations covering GPP guidelines, authorship, publication ethics, and statistical concepts.

Instructions

[PRO] Generate CMPP certification exam practice questions with explanations. Topics: GPP guidelines, authorship criteria, publication ethics, statistical concepts. Multiple choice format with correct answer and explanation of distractors.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYes
num_questionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The main tool handler: @mcp.tool() decorated function 'get_cmpp_practice_questions_prompt' that generates CMPP certification exam practice questions. Takes 'topic' (str) and 'num_questions' (int, default 5) and returns a formatted prompt string.
    @mcp.tool()
    def get_cmpp_practice_questions_prompt(
        topic: str,
        num_questions: int = 5
    ) -> str:
        """
        [PRO] Generate CMPP certification exam practice questions with explanations.
        Topics: GPP guidelines, authorship criteria, publication ethics, statistical concepts.
        Multiple choice format with correct answer and explanation of distractors.
        """
        return f"""Generate {num_questions} practice questions for the CMPP certification exam
    covering: {topic}
    
    Format each question as:
    - Question (multiple choice with 4 options)
    - Correct answer
    - Explanation of why the other options are incorrect
    - Reference to relevant guideline or resource
    
    Focus on application-level questions, not just recall."""
  • server.py:1002-1002 (registration)
    Tool registration in the tool directory listing, mapping the function name to its description for generating CMPP exam practice questions.
    ("get_cmpp_practice_questions_prompt", "Generate CMPP exam practice questions"),
  • The schema/inference for parameters is handled by the Python type hints: 'topic: str' and 'num_questions: int = 5'. The docstring explains the tool's purpose and topics covered.
    @mcp.tool()
    def get_cmpp_practice_questions_prompt(
        topic: str,
        num_questions: int = 5
    ) -> str:
Behavior3/5

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

With no annotations, the description carries full burden. It discloses the tool generates questions, the topics, and the multiple-choice format. However, it does not mention any side effects, required permissions, or potential output size. The behavior is reasonably clear but lacks depth.

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 brief with two sentences and a list of topics. It is front-loaded with the core purpose. The '[PRO]' prefix adds minimal value but does not detract. Could be slightly more structured (e.g., bullet points) but overall efficient.

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?

Given the existence of an output schema, return values need not be described. The description covers main functionality and required parameter, but lacks constraints on topic values and default behavior for num_questions. Adequate for a straightforward tool but leaves some ambiguity.

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 0%, so the description compensates by listing example topics for the 'topic' parameter. However, it does not explain the 'num_questions' parameter or its default value of 5. Partial improvement over schema alone.

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?

Clearly states the tool 'Generate CMPP certification exam practice questions with explanations', specifying verb and resource. The listed topics and format further clarify the scope. Although sibling tools exist, the unique focus on CMPP questions distinguishes it effectively.

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 on when to use this tool versus alternatives. The description does not mention prerequisites, when to avoid it, or suggest other tools for related tasks. An agent must infer usage from the name and context alone.

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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