Literature Review

collaborative-deep-research/agent-papers-cli

This systematically searches academic papers using Semantic Scholar and Google Scholar APIs, triages them for relevance, then produces a thematic literature review organized by research threads rather than individual papers. It walks through multi-query searches with synonyms, citation graph exploration to find seminal work, and deep reading of methods and results sections. The output includes comparative analysis, open questions, and proper BibTeX entries. It's built for actual academic writing, not just collecting abstracts. The approach of organizing by theme instead of chronologically listing papers is the right call, though you'll still need domain knowledge to evaluate what the tools surface.

skills.sh installs: 741
GitHub stars: 50
last updated: Aug 21, 2026

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Install

$ npx -y skills add collaborative-deep-research/agent-papers-cli --skill literature-review --agent claude-code

Installs into .claude/skills of the current project.

Files

Conduct a systematic literature review on "$ARGUMENTS" using the paper and paper-search CLI tools.

1. Define Scope

Before searching, clarify with the user:

Topic boundaries and key terms
Year range (default: last 5 years)
Target venues or communities (if any)
Desired number of papers (default: 15-20 core papers)

2. Multi-Query Search

Search with multiple query variations to maximize coverage:

paper-search semanticscholar papers "<main query>" --limit 20 --year <range>
paper-search semanticscholar papers "<synonym query>" --limit 20 --year <range>
paper-search semanticscholar papers "<related query>" --limit 20 --year <range>
paper-search google scholar "<topic>"

Deduplicate results by title/paper ID.

3. Triage

For each unique paper found:

paper-search semanticscholar details <paper_id>
paper skim <arxiv_id> --lines 2

Categorize as: highly relevant / somewhat relevant / not relevant.

4. Deep Analysis

For highly relevant papers:

paper outline <arxiv_id>
paper read <arxiv_id> introduction
paper read <arxiv_id> method
paper read <arxiv_id> results
paper read <arxiv_id> conclusion

SKILL.md on GitHub