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get_manuscript_edit_prompt

Reviews medical manuscript for scientific accuracy, AMA style, voice, redundancy, and terminology issues. Returns tracked changes with comments.

Instructions

[PRO] Comprehensive medical manuscript edit prompt. Checks: scientific accuracy, AMA style, active/passive voice, redundancy, terminology consistency. Returns tracked-changes notation with brief comments. DATA SAFETY: Only paste published or internally approved text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
text_excerptYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The tool handler function 'get_manuscript_edit_prompt' decorated with @mcp.tool(). Takes a text_excerpt parameter and returns a comprehensive AMA-style manuscript editing prompt covering: scientific accuracy, AMA style, active/passive voice, redundancy, and terminology consistency.
    @mcp.tool()
    def get_manuscript_edit_prompt(text_excerpt: str) -> str:
        """
        [PRO] Comprehensive medical manuscript edit prompt.
        Checks: scientific accuracy, AMA style, active/passive voice, redundancy, terminology consistency.
        Returns tracked-changes notation with brief comments.
        DATA SAFETY: Only paste published or internally approved text.
        """
        return f"""Edit the following medical writing excerpt for:
    1. Scientific accuracy of language (flag overstated or imprecise statements)
    2. AMA style compliance (numbers, abbreviations, units)
    3. Active vs. passive voice (convert passive to active where appropriate)
    4. Redundancy and wordiness (tighten without losing meaning)
    5. Consistency of terminology (flag inconsistent drug names, endpoint names)
    
    Return edited text with tracked changes notation and a brief comment per major edit.
    
    {text_excerpt}
    
    Pro tip: Use this after your own edit pass — a second-pass AI edit catches things fresh eyes miss.
    
    🔒 DATA SAFETY: Only paste published or approved content."""
  • The function signature defines the schema: single 'text_excerpt: str' parameter, returns 'str'.
    def get_manuscript_edit_prompt(text_excerpt: str) -> str:
  • server.py:998-998 (registration)
    Tool registration as a PRO-tier entry in the 'list_all_tools()' tool directory under the name 'get_manuscript_edit_prompt'.
    ("get_manuscript_edit_prompt", "Comprehensive AMA-style manuscript edit"),
Behavior4/5

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

The description discloses what the tool checks (scientific accuracy, style, etc.) and its output format (tracked-changes with comments). The data safety warning adds transparency. However, it does not explicitly state that this is a prompt-generating tool (not directly performing edits), and no annotations are present to fill gaps.

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 brief (four sentences) and front-loaded with the purpose. Every sentence adds value without redundancy. It is well-structured for quick understanding.

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

Completeness4/5

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

Given the tool's simplicity (one parameter, no annotations, but has output schema) and the context of sibling prompt tools, the description covers the core functionality and safety. It is adequate but could mention the output schema nature or provide an example for completeness.

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?

The single parameter 'text_excerpt' has no schema description (0% coverage). The description adds minimal value by advising 'Only paste published or internally approved text' but does not specify expected format, length, or other constraints. The tool's purpose implies the parameter should be manuscript text, but the description does not make this explicit.

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 clearly states the tool is for medical manuscript editing and lists specific checks (scientific accuracy, AMA style, etc.) and output format (tracked-changes). However, there is a slight ambiguity: the tool name suggests it returns a prompt, while the description implies it performs the edit itself, which could confuse an agent.

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 includes a data safety guideline ('Only paste published or internally approved text'), which is helpful but does not explicitly state when to use this tool versus sibling prompt tools (e.g., get_manuscript_outline_prompt) or provide exclusion criteria. Usage context is implied but not fully clarified.

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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