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get_unstructured_abstract_prompt

Convert a structured abstract into a flowing unstructured paragraph for journal submission. Meets requirements of journals like Nature and Science.

Instructions

[PRO] Convert a structured abstract to a flowing unstructured paragraph. Required by many basic science journals (Nature, Science family). DATA SAFETY: Only paste published or approved text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
structured_abstractYes
word_countYes
target_journalYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler function for the 'get_unstructured_abstract_prompt' tool. Takes a structured abstract, word count, and target journal, and returns a formatted prompt string that instructs the LLM to convert a structured abstract into a flowing unstructured paragraph.
    def get_unstructured_abstract_prompt(
        structured_abstract: str,
        word_count: int,
        target_journal: str
    ) -> str:
        """
        [PRO] Convert a structured abstract to a flowing unstructured paragraph.
        Required by many basic science journals (Nature, Science family).
        DATA SAFETY: Only paste published or approved text.
        """
        return f"""Convert the following structured abstract into a single, flowing unstructured
    paragraph of approximately {word_count} words.
    Maintain all key data points. Use smooth transitions.
    Target journal: {target_journal}
    
    {structured_abstract}
    
    ⚠️ DATA SAFETY: Only input published or approved text."""
  • server.py:976-991 (registration)
    The tool is registered as part of the 'pro_tools' list (line 977), which is likely used for dynamic tool listing/registration.
    pro_tools = [
        ("get_unstructured_abstract_prompt", "Convert structured abstract to flowing paragraph"),
        ("get_strengthen_conclusions_prompt", "Rewrite weak abstract conclusions to be data-anchored"),
        ("get_adapt_abstract_audience_prompt", "Rewrite abstract for a different audience"),
        ("get_introduction_section_prompt", "Draft manuscript Introduction/Background section"),
        ("get_methods_section_prompt", "Draft manuscript Methods section"),
        ("get_results_section_prompt", "Draft Results section narrative from approved data"),
        ("get_discussion_section_prompt", "Draft manuscript Discussion section"),
        ("get_rebuttal_disagreement_prompt", "Draft evidence-based rebuttal to reviewer"),
        ("get_revised_manuscript_cover_letter_prompt", "Draft cover letter for revised submission"),
        ("get_congress_abstract_prompt", "Draft ASCO/ASH/ESMO congress abstract"),
        ("get_poster_title_and_takeaways_prompt", "Generate poster titles and take-home messages"),
        ("get_oral_presentation_script_prompt", "Draft timed oral presentation script"),
        ("get_slide_deck_outline_prompt", "Create slide-by-slide deck outline"),
        ("get_speaker_notes_prompt", "Write speaker notes for a data slide"),
        ("get_moa_slide_prompt", "Explain mechanism of action for a slide"),
  • The schema for the tool defined via the function signature and decorator. Parameters: structured_abstract (str), word_count (int), target_journal (str). Return type: str.
    def get_unstructured_abstract_prompt(
        structured_abstract: str,
        word_count: int,
        target_journal: str
    ) -> str:
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It only mentions the conversion and a data safety warning. It does not explain that the tool likely returns a prompt (as implied by the name) rather than performing the conversion directly, nor does it disclose any side effects, auth requirements, or rate limits.

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 concise (three sentences) and front-loaded with the core purpose. Every sentence serves a function: purpose, context, safety warning. However, it sacrifices some needed detail for brevity.

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 the tool has three required parameters, no annotations, and an output schema, the description should provide guidance on parameter usage and output format. It lacks both, leaving significant gaps for the agent to invoke the tool correctly.

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 input schema has three parameters with no description coverage (0%). The description adds no explanation of what each parameter means, its format, or constraints. For example, it does not clarify expected word count range or target journal values.

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's purpose: 'Convert a structured abstract to a flowing unstructured paragraph.' It also specifies the target audience ('Required by many basic science journals (Nature, Science family)'), which helps distinguish it from siblings like get_structured_abstract_prompt or get_congress_abstract_prompt.

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 description provides clear context for when to use the tool (targeting basic science journals), but does not explicitly state when not to use it or mention alternatives. The context is strong enough to guide simple decisions, but lacks explicit exclusion criteria.

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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