lingzhi227/claude-skills/lingzhi227-literature-review
Claude Code and agent skill by lingzhi227/claude-skills
- community
Checking that the SKILL.md file is still in the repository.
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.
Install
npx vskill@latest install lingzhi227/claude-skills/lingzhi227-literature-reviewSKILL.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)
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:
- Persona asks a question from their unique angle
- Generate search queries from the question
- Search literature using the search scripts
- Synthesize an answer grounded in retrieved papers with inline citations
- Record the dialogue turn with search results
- Repeat for 3-5 turns per persona
- 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:
- Outline — Hierarchical topic structure
- Per-section summaries — Each grounded in retrieved papers
- Paper database — Structured entries for all reviewed papers
- 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
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/literature-review/SKILL.md
Popularity
- Repository stars
- 42
- Repository forks
- 10
- 7-day trend score
- 19
Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 2 May 2026, 6 months ago.
Works with
Any agent vskill installs to: 56 targets in all. These 39 have a page on this site.
- Claude Code
- Cursor
- GitHub Copilot
- Windsurf
- Codex
- Gemini CLI
- Cline
- Amp
- Roo Code
- Goose
- Continue
- Kilo Code
- Junie
- Trae
- OpenHands
- Qwen Code
- AI Agent
- Tabnine Chat
- Sourcegraph Cody
- Amazon Q
- Firebase Genkit
- Sweep
- Devin
- Phind
- Mentat
- Claude Desktop
- Aider
- GPT Pilot
- Plandex
- bolt.new
- v0
- Replit Agent
- Anse
- TypingMind
- BetterChatGPT
- LibreChat
- Warp AI
- Pieces
- Fig AI
Embed badge
[](https://verified-skill.com/skills/lingzhi227/claude-skills/lingzhi227-literature-review)