PluginBench
Skill
Review
Audit score 70

literature-review

lingzhi227/agent-research-skills

Conduct comprehensive literature reviews through multi-perspective expert dialogue and systematic paper synthesis.

What is literature-review?

This skill generates diverse expert personas to simulate multi-turn Q&A conversations about a research topic, searches academic literature for each perspective, and synthesizes findings into a structured review. Use it when starting a new research project or writing a survey section to ensure broad coverage and grounded claims.

  • Generate 3-5 diverse expert personas representing different research angles and perspectives
  • Simulate multi-turn Q&A conversations where each persona asks questions and receives literature-grounded answers
  • Search academic databases (Semantic Scholar, OpenAlex, arXiv) to retrieve papers relevant to each question
  • Synthesize persona conversations into a unified knowledge base organized by theme
  • Generate hierarchical outlines and structured literature reviews with inline citations
  • Identify knowledge gaps and areas requiring further investigation

How to install literature-review

npx skills add https://github.com/lingzhi227/agent-research-skills --skill literature-review
Prerequisites
  • Python environment with access to academic search APIs (Semantic Scholar, OpenAlex, arXiv)
  • literature-search or deep-research skill installed for search scripts
  • Access to reference files: dialogue-prompts.md and review-workflow.md
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How to use literature-review

  1. 1.Run the skill with your research topic: provide the topic as $0 and optional focus as $1
  2. 2.Review the generated expert personas and their perspectives
  3. 3.For each persona, the skill will conduct 3-5 Q&A turns: persona asks question → search literature → synthesize answer with citations
  4. 4.Review the multi-perspective dialogue output and collected papers
  5. 5.Use the synthesized knowledge base and generated outline to write your literature review
  6. 6.Ensure every claim in your final review is supported by citations from the gathered papers

Use cases

Good for
  • Starting a new research project to understand the landscape and key papers in a domain
  • Writing a related work or survey section with comprehensive coverage of diverse approaches
  • Exploring a topic from multiple disciplinary or methodological angles simultaneously
  • Building a structured knowledge base of papers with organized summaries and citations
  • Identifying gaps in existing literature to inform research direction
Who it's for
  • Researchers beginning new projects
  • Survey and review paper authors
  • Graduate students conducting literature reviews
  • Interdisciplinary researchers seeking multiple perspectives
  • Research teams planning new investigations

literature-review FAQ

What if the search doesn't find papers on my specific topic?

The skill explicitly identifies and reports knowledge gaps. You can refine search queries, broaden the topic angle, or note the gap as an area for future research.

How many papers will be reviewed?

The number depends on search results per query. The workflow searches up to 20 results per Semantic Scholar query, 20 per OpenAlex, and 10 per arXiv, across multiple persona-generated queries.

Can I customize the expert personas?

Yes, the skill uses persona generation prompts from the references. You can modify these prompts to create personas aligned with your specific research needs.

How are citations formatted in the output?

The skill uses inline citations in the format 'Author et al. [#]' where # refers to entries in a structured paper database included in the output.

What makes this different from a simple literature search?

This skill uses multi-perspective dialogue to ensure comprehensive coverage from different angles, synthesizes across viewpoints to reduce redundancy, and organizes findings into a structured knowledge base rather than a flat list of papers.

Full instructions (SKILL.md)

Source of truth, from lingzhi227/agent-research-skills.


name: literature-review description: 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. argument-hint: [topic]

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..."

Related Skills

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

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