AI SummarySystematic literature survey for positioning a research contribution. Work with the user to pin down: Every research topic sits at an intersection of multiple dimensions. Identify 2-4 axes:
Install
Copy this and paste it into Claude Code, Cursor, or any AI assistant:
I want to install the "related-work-survey" skill in my project. Please run this command in my terminal: # Install skill into your project mkdir -p .claude/skills/related-work-survey && curl --retry 3 --retry-delay 2 --retry-all-errors -o .claude/skills/related-work-survey/SKILL.md "https://raw.githubusercontent.com/jxtse/scientific-research-skills/main/skills/related-work-survey/SKILL.md" Then restart Claude Code (or reload the window in Cursor) so the skill is picked up.
Description
Conducts a systematic related-work / literature-survey / state-of-the-art review for a research question by defining survey dimensions, searching each axis, building a taxonomy of prior work, identifying the gap, and producing a positioning narrative for a paper's Related Work section. Goes beyond a flat paper list to deliver structured analysis. Use when the user is starting a new research project and needs to map the landscape, asks "what's been done on X?" or "how does my idea compare to existing work?", needs to write or revise a Related Work / Background / Prior Art section, wants to identify a research gap or position their contribution, or asks to build a taxonomy of approaches in a research area.
Related Work Survey
Systematic literature survey for positioning a research contribution.
When to Use
• User starts a new research project and needs landscape understanding • User asks "what's been done on X?" • User needs to write a related work section • User wants to identify the gap their work fills
Step 1: Define the Research Question
Work with the user to pin down: • Core question: What specific problem are we solving? • Key concepts: What are the 3-5 key terms/concepts? • Scope boundaries: What's in scope vs. adjacent but out of scope?
Step 2: Identify Survey Dimensions
Every research topic sits at an intersection of multiple dimensions. Identify 2-4 axes: Example for "Neural-Symbolic Decomposition in LLM Agents": • Axis 1: Neuro-symbolic integration approaches • Axis 2: LLM agent architectures (harness, scaffolding) • Axis 3: Adaptive/metacognitive planning • Axis 4: Text analysis at scale (specific application)
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