literature-survey

What problem does it solve?

This Skill automates the end-to-end process of conducting academic literature surveys by systematically finding, verifying, and summarizing relevant publications so researchers can quickly understand a field's landscape without missing key works.

Core Features & Use Cases

• Systematic multi-tier search: Recent-first exhaustive search, high-impact established works, and foundational seminal works.
• Paper-level structured annotations: For each paper record thesis, core, diff, and limit fields to enable transparent synthesis.
• Verification and reproducibility: Requires DOI or URL for each paper and includes a hallucination check and execution log for auditability.
• Use Case: Produce a 30–60 paper survey on a machine learning subtopic, grouped by themes, with a survey-level thesis, foundation, progress, and gap analysis and an exportable Markdown report.

Quick Start

Summarize the recent and foundational literature on "self-supervised learning for medical image segmentation" into a categorized Markdown survey with paper-level thesis/core/diff/limit and verified DOIs or URLs.