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tooluniverse-literature-deep-research

Conduct comprehensive literature research with target disambiguation, evidence grading, and structured theme extraction. Creates a detailed report with mandatory completeness checklist, biological model synthesis, and testable hypotheses. For biological targets, resolves official IDs (Ensembl/UniProt), synonyms, naming collisions, and gathers expression/pathway context before literature search. De

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Atualizado há 4 meses

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Literature Deep Research Strategy (Enhanced)

A systematic approach to comprehensive literature research that starts with target disambiguation to prevent missing details, uses evidence grading to separate signal from noise, and produces a content-focused report with mandatory completeness sections.

KEY PRINCIPLES:

  1. Target disambiguation FIRST - Resolve IDs, synonyms, naming collisions before literature search
  2. Right-size the deliverable - Use *Factoid / Verificati

[Description truncada. Veja o README completo no GitHub.]

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