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get_journal_selection_rationale_prompt

Recommends top 3 journals for manuscript submission with rationale on impact factor, fit, decision time, requirements, and acceptance likelihood.

Instructions

[PRO] Recommend the top 3 journals for a manuscript submission with full rationale. Includes impact factor, fit rationale, time to decision, submission requirements, and likelihood of acceptance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
study_descriptionYes
indicationYes
target_hcp_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The @mcp.tool() decorated function that implements the get_journal_selection_rationale_prompt tool. It takes study_description, indication, and target_hcp_type as parameters and returns a prompt string recommending top 3 journals with rationale.
    @mcp.tool()
    def get_journal_selection_rationale_prompt(
        study_description: str,
        indication: str,
        target_hcp_type: str
    ) -> str:
        """
        [PRO] Recommend the top 3 journals for a manuscript submission with full rationale.
        Includes impact factor, fit rationale, time to decision, submission requirements,
        and likelihood of acceptance.
        """
        return f"""Recommend the top 3 journals for submitting a manuscript on {study_description}
    in {indication}.
    
    For each journal:
    - Journal name and impact factor (approximate)
    - Rationale for fit (scope, audience, recent similar publications)
    - Typical time to first decision
    - Key submission requirements
    - Likelihood of acceptance (High/Medium/Low) with reasoning
    
    Primary target audience: {target_hcp_type}
    
    Pro tip: Always verify impact factors and submission guidelines directly on the journal
    website — they change annually."""
  • server.py:995-995 (registration)
    The tool is registered in a tool directory listing as ("get_journal_selection_rationale_prompt", "Recommend top 3 journals with rationale"), used to generate a directory of all available tools.
    ("get_journal_selection_rationale_prompt", "Recommend top 3 journals with rationale"),
  • The entire tool definition uses FastMCP's @mcp.tool() decorator to register the function as an MCP tool. No separate schema file exists; the schema is derived from the function signature and docstring by FastMCP.
    @mcp.tool()
    def get_journal_selection_rationale_prompt(
        study_description: str,
        indication: str,
        target_hcp_type: str
    ) -> str:
        """
        [PRO] Recommend the top 3 journals for a manuscript submission with full rationale.
        Includes impact factor, fit rationale, time to decision, submission requirements,
        and likelihood of acceptance.
        """
        return f"""Recommend the top 3 journals for submitting a manuscript on {study_description}
    in {indication}.
    
    For each journal:
    - Journal name and impact factor (approximate)
    - Rationale for fit (scope, audience, recent similar publications)
    - Typical time to first decision
    - Key submission requirements
    - Likelihood of acceptance (High/Medium/Low) with reasoning
    
    Primary target audience: {target_hcp_type}
    
    Pro tip: Always verify impact factors and submission guidelines directly on the journal
    website — they change annually."""
Behavior2/5

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

No annotations are provided, so the description must fully explain behavior. It lists output elements (impact factor, fit rationale, etc.) but fails to clarify that the tool likely generates a prompt for a human or AI, not the actual recommendations. The name includes 'prompt', but the description does not state this explicitly, leaving ambiguity about the tool's action and return value.

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 concise sentence listing key output features. However, it lacks structure (e.g., bullet points) and could be slightly reorganized for clarity. Overall, it earns its place with minimal verbosity.

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?

The description omits several crucial details: the tool's behavior (outputting a prompt vs. direct recommendations), parameter descriptions, and how the output schema (which exists) is structured. Despite the clear purpose, the lack of behavioral and parameter information leaves the tool incomplete for effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%. The description mentions the three required parameters (study_description, indication, target_hcp_type) but provides no details on expected format, examples, or constraints. Without any guidance, an agent cannot correctly populate these fields.

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 recommends top 3 journals for manuscript submission with full rationale, listing specific elements like impact factor, fit rationale, time to decision, etc. It distinguishes from sibling tools that focus on other medical writing tasks (e.g., abstracts, outlines), so purpose is specific and unambiguous.

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?

The tool's purpose is well-defined and distinct from siblings, which cover different tasks (e.g., abstract generation, outline creation). While no explicit 'when to use' or 'alternatives' are given, the context of journal selection is clear and unlikely to overlap with other tools. A brief exclusion statement could improve clarity.

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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