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get_publication_plan_framework_prompt

Construct a structured publication plan framework table with columns for publication type, study source, target venue, timeline, priority, and status from inputs on drug, indication, studies, audience, congresses, and journals.

Instructions

[PRO] Build a publication plan framework as a structured table. Columns: Publication Type | Study/Data Source | Target Venue | Timeline | Priority | Status.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drug_nameYes
indicationYes
available_studiesYes
target_hcp_audienceYes
key_congressesYes
target_journalsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The MCP tool handler function 'get_publication_plan_framework_prompt' decorated with @mcp.tool(). Returns a formatted prompt string for building a publication plan framework table. Takes parameters: drug_name, indication, available_studies, target_hcp_audience, key_congresses, target_journals.
    @mcp.tool()
    def get_publication_plan_framework_prompt(
        drug_name: str,
        indication: str,
        available_studies: str,
        target_hcp_audience: str,
        key_congresses: str,
        target_journals: str
    ) -> str:
        """
        [PRO] Build a publication plan framework as a structured table.
        Columns: Publication Type | Study/Data Source | Target Venue | Timeline | Priority | Status.
        """
        return f"""Create a publication plan framework for {drug_name} in {indication}.
    
    Available studies: {available_studies}
    Target audience: {target_hcp_audience}
    Key congresses: {key_congresses}
    Target journals: {target_journals}
    
    Output as table:
    Publication Type | Study/Data Source | Target Venue | Timeline | Priority | Status
    
    Pro tip: Build the framework first, then layer in specific timelines.
    Easier to get buy-in from medical affairs leadership that way."""
  • server.py:992-992 (registration)
    Registration entry in the pro_tools list within the tool directory. Maps the tool name to its description 'Build a publication plan framework table'.
    ("get_publication_plan_framework_prompt", "Build a publication plan framework table"),
Behavior2/5

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

With no annotations, the description carries full burden for behavioral disclosure. It states the tool 'builds' a table, but it's unclear if this is a read-only prompt generation or an actionable output. There is no mention of side effects, permissions, or whether the tool modifies any state. The description is ambiguous as to what the tool actually outputs.

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 sentence plus a column list, which is efficient and front-loads the purpose. However, it omits parameter details and behavioral nuance, which would improve completeness without harming conciseness.

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?

The description covers the output format (a structured table with listed columns) but does not explain the nature of the output (is it a prompt? a ready-to-use table?). With 6 required params and no annotations, the description lacks guidance on inputs and fails to clarify behavioral aspects. An output schema exists, so return values are partially covered, but the description should still bridge the gap.

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%, meaning none of the 6 required parameters are documented in the schema. The tool description completely fails to mention or explain any parameters (drug_name, indication, etc.). The user receives no guidance on how to fill these inputs, severely limiting the tool's usability.

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 that the tool builds a publication plan framework as a structured table, specifying the exact columns. This verb+resource combination distinguishes it from sibling prompt-generation tools like get_pub_plan_executive_summary_prompt or get_congress_abstract_prompt, which serve 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 Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, preferred scenarios, or when to avoid it. Sibling tools are not referenced, and no context is given for choosing this tool over others.

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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