Literature Review

作者 lingzhi2279e6c085d65e3无许可证386 个星标收录于 2026年10月8日更新于 2026年10月8日仓库7个月前更新

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.

AI 生成的概览

通过模拟多视角专家对话、检索论文并综合带引用的发现,完成多角度文献综述。

功能
该技能执行一套结构化的文献综述流程:针对主题生成 3-5 个专家角色,模拟多轮问答对话,将问题转化为检索查询,并用检索到的论文以行内引用支撑回答。随后把各段对话合并为统一知识库,去除重复内容,按主题组织材料,并产出结构化综述。输出包括大纲、各节摘要、论文数据库以及识别出的知识空白。
适用场景
适用于启动新研究项目、界定研究主题,或撰写需要广泛且有引用支撑的综述与相关工作章节。也适合需要比较多种研究视角以及近期与奠基性论文的场景。
运行要求
仅为说明性内容,本身不附带脚本。它引用外部检索脚本(Semantic Scholar、OpenAlex、arXiv)和两份参考文档,因此需要这些脚本、Python 运行环境以及对文献 API 的网络访问。

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)

bash
# Search Semantic Scholarpython ~/.claude/skills/deep-research/scripts/search_semantic_scholar.py --query "topic" --max-results 20
# Search OpenAlexpython ~/.claude/skills/literature-search/scripts/search_openalex.py --query "topic" --max-results 20
# Search arXivpython ~/.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..."

Related Skills

  • Upstream: literature-search, deep-research
  • Downstream: related-work-writing, research-planning
  • See also: survey-generation

来源与署名

来源:lingzhi227/agent-research-skills位于skills/literature-review提交9e6c085

许可证: 无许可证

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