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literature-review

该 skill 模拟多位领域专家围绕研究选题的多轮对话流程。每次对话中，系统从不同视角生成问题、检索 Semantic Scholar 与 arXiv 等来源、基于真实文献合成回答，最后跨角色去重归并成统一知识结构。适用于新课题立项前快速建立文献图景，或写 survey 章节时先用对话方式理清脉络。

Conduct comprehensive literature reviews using multi-perspective dialogue simulation. Generate diverse expert personas, conduct grounded Q&A conversations, and synthesize findings into structured knowledge. Use when starting a new research project or writing a survey section.

Repo
Chanw-research/claude-code-paper-writing
skills.sh
/Chanw-research/claude-code-paper-writing/literature-review
Slug
literature-review
skills.sh 详情页GitHub 源目录

SKILL.md

Literature Review

Conduct deep literature reviews through multi-perspective dialogue and systematic search.

Input

  • $0 — Research topic or question
  • $1 — Optional: specific focus or angle

References

  • Multi-perspective dialogue prompts (STORM): ~/.claude/skills/literature-review/references/dialogue-prompts.md
  • Literature review workflow (AgentLaboratory): ~/.claude/skills/literature-review/references/review-workflow.md

Scripts (from literature-search skill)

# Search Semantic Scholar
python ~/.claude/skills/deep-research/scripts/search_semantic_scholar.py --query "topic" --max-results 20

# Search OpenAlex
python ~/.claude/skills/literature-search/scripts/search_openalex.py --query "topic" --max-results 20

# Search arXiv
python ~/.claude/skills/deep-research/scripts/search_arxiv.py --query "topic" --max-results 10

Workflow

Step 1: Generate Expert Personas (from STORM)

Given the topic, create 3-5 diverse expert personas:

  • Each represents a different perspective, role, or research angle
  • Example: "ML systems researcher focused on efficiency", "Theoretical statistician concerned with guarantees"
  • Use the persona generation prompts from references

Step 2: Multi-Perspective Dialogue

For each persona, simulate a multi-turn Q&A conversation:

  1. Persona asks a question from their unique angle
  2. Generate search queries from the question
  3. Search literature using the search scripts
  4. Synthesize an answer grounded in retrieved papers with inline citations
  5. Record the dialogue turn with search results
  6. Repeat for 3-5 turns per persona
  7. End when persona says "Thank you so much for your help!"

Step 3: Synthesize Knowledge

  • Combine all persona conversations into a unified knowledge base
  • Remove redundancy across personas
  • Organize by theme/subtopic
  • Generate an outline based on the collected information

Step 4: Generate Literature Review

  • Write a structured review organized by the generated outline
  • Every claim must be supported by a citation
  • Include a summary table of key papers (method, contribution, limitations)

Output

A structured literature review with:

  1. Outline — Hierarchical topic structure
  2. Per-section summaries — Each grounded in retrieved papers
  3. Paper database — Structured entries for all reviewed papers
  4. Knowledge gaps — Identified areas needing further investigation

Rules

  • Every sentence in the review must be supported by gathered information
  • If information is not found, explicitly state the gap
  • Cite broadly — cover diverse approaches, not just the most popular
  • Include recent papers (last 2-3 years) alongside foundational work
  • Use inline citations: "Smith et al. [1] propose..."

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