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get_author_review_request_prompt

Drafts a professional email to request author review, including a clear deadline and specific questions for the author.

Instructions

[PRO] Draft a professional email requesting author review with a clear deadline. Concise (<150 words), friendly but firm on deadline, with a specific ask.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
author_nameYes
document_typeYes
deadlineYes
contextYes
specific_questionsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The actual tool handler function 'get_author_review_request_prompt' — a decorated @mcp.tool() that returns a prompt string for drafting a professional email requesting author review with a deadline.
    @mcp.tool()
    def get_author_review_request_prompt(
        author_name: str,
        document_type: str,
        deadline: str,
        context: str,
        specific_questions: str = ""
    ) -> str:
        """
        [PRO] Draft a professional email requesting author review with a clear deadline.
        Concise (<150 words), friendly but firm on deadline, with a specific ask.
        """
        return f"""Write a professional email to {author_name} requesting review of {document_type}
    with deadline: {deadline}.
    
    Context: {context}
    Specific questions for author: {specific_questions if specific_questions else "General review requested"}
    
    Email should be:
    - Concise (under 150 words)
    - Friendly but clear on deadline
    - Include a specific ask (e.g., 'please track changes directly in the document')"""
  • server.py:996-996 (registration)
    Tool registration entry in the tool directory listing — maps the tool name to its description 'Draft author review request with deadline'.
    ("get_author_review_request_prompt", "Draft author review request with deadline"),
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the output style (professional, concise, friendly but firm, with a deadline and specific ask). However, it does not mention any behavior like token limits, return format, or that it is a read-only operation. For a simple text generation tool, the description is adequate but minimal.

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, front-loaded with the core action and tone. Every word adds value, and it is appropriately sized for the tool's simple purpose.

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 0% schema coverage and no annotations, the description should provide more context about parameter usage and output. It describes the output's tone and length but not how to populate the input fields. The presence of an output schema does not excuse the lack of input guidance, making the tool less complete for the agent.

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% with 5 parameters (4 required). The description does not explain the meaning or usage of any parameter beyond the overall purpose. While parameter names like author_name and deadline are self-explanatory, context and specific_questions lack guidance. The description fails to compensate for the missing schema descriptions.

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 the tool drafts a professional email requesting author review with a deadline. The verb 'Draft' and resource 'professional email requesting author review' are specific. Among siblings like get_author_invitation_email_prompt and get_author_revision_response_prompt, this tool is distinctly for review requests.

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

Usage Guidelines3/5

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

The description implies the tool is for drafting a review request email but does not explicitly state when to use it versus alternative prompt tools. No exclusions or when-not scenarios are provided, leaving the agent to infer from the name and purpose.

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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