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get_gap_analysis_prompt

Identify scientific, data, communication, and competitive gaps in your publication strategy by analyzing literature and available data.

Instructions

[PRO] Conduct a literature and data gap analysis for a publication strategy. Identifies scientific, data, communication, and competitive gaps with rationale.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drug_or_classYes
indicationYes
current_publication_landscapeYes
available_data_packageYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The tool handler function that executes the gap analysis logic. It takes drug_or_class, indication, current_publication_landscape, and available_data_package as parameters and returns a formatted prompt string identifying scientific, data, communication, and competitive gaps.
    def get_gap_analysis_prompt(
        drug_or_class: str,
        indication: str,
        current_publication_landscape: str,
        available_data_package: str
    ) -> str:
        """
        [PRO] Conduct a literature and data gap analysis for a publication strategy.
        Identifies scientific, data, communication, and competitive gaps with rationale.
        """
        return f"""Perform a gap analysis for publications on {drug_or_class} in {indication}.
    
    Current landscape: {current_publication_landscape}
    Our data package: {available_data_package}
    
    Identify:
    1. Scientific gaps: questions not yet answered in the literature
    2. Data gaps: analyses possible from available data but not yet conducted
    3. Communication gaps: topics well-studied but underrepresented in publications
    4. Competitive gaps: areas where competitor data exists but ours does not
    
    Output as a prioritized gap list with rationale.
    
    Pro tip: Present gap analyses visually as a matrix — much more impactful in steering committees."""
  • server.py:993-993 (registration)
    Registration of the tool in the tool listing, mapping 'get_gap_analysis_prompt' to its description 'Conduct literature and data gap analysis'.
    ("get_gap_analysis_prompt", "Conduct literature and data gap analysis"),
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits. It states the tool 'conducts' an analysis and 'identifies' gaps, but does not mention that it returns a prompt (as implied by the tool name), any side effects, or authentication needs. The description is too vague to set proper expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is brief at two sentences, which is generally positive, but it includes an unnecessary '[PRO]' prefix that may confuse agents. It lacks structure such as bullet points or sections. While concise, it could be better organized or omit the prefix.

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?

Despite having an output schema (as indicated by context signals), the description does not mention the output format or expected return value. Given the tool's complexity (4 required parameters, gap analysis task), the description is too minimal to provide complete context for an agent to use it effectively without guessing.

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?

The schema has 0% parameter description coverage, meaning the schema itself provides no parameter documentation. The description does not mention or explain any of the four required parameters (drug_or_class, indication, etc.), failing to add meaning beyond the schema. For example, it does not clarify what 'current_publication_landscape' should contain.

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 'Conduct a literature and data gap analysis for a publication strategy' and specifies it 'Identifies scientific, data, communication, and competitive gaps with rationale'. This provides a specific verb ('conduct') and resource ('gap analysis'), making the purpose clear. However, it does not explicitly differentiate from sibling tools like 'get_publication_plan_framework_prompt', though the gap analysis focus is distinct.

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?

The description offers no guidance on when to use this tool versus alternatives. It simply states what it does without any context about its place in a workflow, prerequisites, or exclusions. Given the many sibling tools, an agent would have no basis for selecting this one 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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