Literature Review

by lingzhi2279e6c085d65e3No license386 starsListed Oct 8, 2026Updated Oct 8, 2026Repository updated 7 months ago

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.

Instructions onlyResearch & Analysis
AI-generated overview

Conducts multi-perspective literature reviews by simulating expert dialogues, searching papers, and synthesizing cited findings.

What it does
This skill runs a structured literature review workflow: it generates 3-5 expert personas for a topic, simulates multi-turn Q&A dialogues, turns questions into search queries, and grounds answers in retrieved papers with inline citations. It then merges the dialogues into a unified knowledge base, removes redundancy, organizes material by theme, and produces a structured review. Outputs include an outline, per-section summaries, a paper database, and identified knowledge gaps.
When to use it
Use it when starting a new research project, scoping a topic, or writing a survey or related-work section that needs broad, cited coverage. It suits situations where multiple research perspectives and recent plus foundational papers should be compared.
Requirements
Instructions only; it ships no scripts of its own. It references external search scripts (Semantic Scholar, OpenAlex, arXiv) and two reference documents, so those scripts, a Python runtime, and network access to the literature APIs are needed.

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

Source and attribution

Source:lingzhi227/agent-research-skillsinskills/literature-reviewat commit9e6c085

License: No license

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