Literature Review

作者 lingzhi2279e6c085d65e3無授權條款386 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫7 個月前更新

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 產生的概覽

透過模擬多視角專家對話、檢索論文並綜合附引用的發現,完成多角度的文獻回顧。

功能
此技能執行一套結構化的文獻回顧流程:針對主題產生 3-5 個專家角色,模擬多輪問答對話,將問題轉為檢索查詢,並以檢索到的論文搭配行內引用來支撐回答。接著把各段對話合併為統一知識庫,移除重複內容,依主題整理資料,並產出結構化回顧。輸出包含大綱、各節摘要、論文資料庫,以及辨識出的知識缺口。
適用情境
適用於啟動新的研究專案、界定研究主題,或撰寫需要廣泛且有引用支撐的綜述與相關工作章節。也適合需要比較多種研究視角,以及近期與奠基性論文的場合。
執行需求
僅為說明性內容,本身不附帶指令稿。它引用外部檢索指令稿(Semantic Scholar、OpenAlex、arXiv)與兩份參考文件,因此需要這些指令稿、Python 執行環境,以及對文獻 API 的網路存取。

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

來源與署名

來源:lingzhi227/agent-research-skills位於skills/literature-review提交9e6c085

授權條款: 無授權條款

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