Research "$ARGUMENTS" in depth using the paper and paper-search CLI tools. Follow this workflow:

1. Broad Discovery

Start with broad searches to map the landscape:

paper-search google web "$ARGUMENTS" paper-search semanticscholar papers "$ARGUMENTS" --limit 10

Scan titles, snippets, and citation counts. Identify the most relevant papers and key terms.

2. Narrow and Filter

Refine based on what you found:

paper-search semanticscholar papers "<refined query>" --year 2023-2025 --min-citations 10 paper-search semanticscholar snippets "<specific question>" paper-search pubmed "<query>" # if biomedical

3. Deep Read

For the most relevant papers (at least 3-5), read in depth:

paper outline <arxiv_id> # understand structure first paper skim <arxiv_id> --lines 3 # quick overview paper read <arxiv_id> <section> # read key sections

For web sources:

paper-search browse <url>

4. Follow the Citation Graph

For key papers, explore their context:

paper-search semanticscholar citations <paper_id> --limit 10 # who cites this? paper-search semanticscholar references <paper_id> --limit 10 # what does it build on? paper-search semanticscholar details <paper_id> # full metadata

5. Synthesize

Combine findings into a structured report with:

• Key findings and themes

• Areas of agreement/disagreement

• Gaps in the literature

• Citations for all claims (include paper titles and URLs)

• BibTeX entries for key papers (use paper bibtex <arxiv_id> to generate)

Guidelines

• Always start broad, then narrow. Don't read deeply until you've scanned widely.

• Read at least 3-5 primary sources before synthesizing.

• Cross-reference web sources against academic papers when possible.

• Use paper-search semanticscholar snippets to find specific evidence for claims.

• Track what you've already searched/read to avoid redundancy.

• If a search returns arxiv papers, use paper read to get the full text rather than just the snippet.