yzxoi/paperly-codex/gap-detection

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Use when the user wants to identify open research gaps, unresolved questions, or methodological blind spots across a literature corpus.

Install

npx vskill@latest install yzxoi/paperly-codex/gap-detection

SKILL.md

Gap Detection

Overview

Analyzes a team's literature base to identify what has NOT been studied, contested, or resolved. Surfaces research gaps, contradictions left unaddressed, and methodological blind spots — helping teams identify novel contributions before writing.

When to Use

  • User asks "what hasn't been done yet in this area?"
  • User is preparing a manuscript introduction or contribution framing section
  • User asks "where are the open questions in [topic]?"
  • Lab wants to avoid duplicating work already done elsewhere
  • User wants to position a new project in the existing literature landscape

Key Capabilities

  • Scan a paper corpus for explicitly stated limitations and future work sections
  • Cluster unstudied conditions, populations, datasets, or modalities
  • Cross-reference claimed gaps against actual recent work (via arXiv/PubMed)
  • Identify methodological monocultures (everyone uses the same dataset/approach)
  • Generate a structured "gap map" organized by type: empirical, theoretical, applied
  • Suggest 3–5 concrete research directions with supporting evidence

Usage Examples

Find gaps in a topic area
python
gaps = gap_detection.analyze(
topic="self-supervised learning for genomics",
corpus=review.get_papers(),
include_future_work_sections=True
)
Cross-check a proposed contribution against the literature
python
gap_detection.validate_novelty(
claim="We are the first to apply contrastive learning to single-cell RNA-seq",
search_depth="comprehensive"
)
Generate gap map for manuscript framing
python
gap_detection.gap_map(
topic="federated learning in clinical settings",
format="structured_markdown",
audience="paper_reviewer"
)

Output Format

Returns categorized gap list with: gap description, supporting evidence (paper excerpts), estimated research effort, and a novelty confidence score. Optionally formatted as a gap map table.

Best Paired With

  • claim_auditor for novelty-risk checks
  • related_work_scout when positioning the contribution against nearby prior work

Notes

  • Explicitly stated limitations in papers are the highest-signal source of gaps
  • Combine with contradiction-detection to find gaps created by conflicting findings
  • Novelty validation is probabilistic — always verify manually before submission claims

Security

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