Deep Research
Run a structured literature and web deep-dive with academic search, paper reading, and citation-graph traversal via the paper CLI.
Install
npx skills add https://github.com/collaborative-deep-research/agent-papers-cli --skill deep-researchWhat is this skill?
- Four-step workflow: broad discovery, narrow/filter, deep read (3–5 papers), citation graph exploration
- Semantics Scholar, Google web, PubMed, and browse commands for landscape mapping and snippets
- Paper CLI depth: outline, skim, and section reads for arXiv-style sources
- Citation and reference queries to surface influential prior and follow-on work
- Allowed agent tools: Bash, Read, Glob, Grep, Write for CLI-driven research sessions
Adoption & trust: 1 installs on skills.sh; 44 GitHub stars; 2/3 security scanners passed (skills.sh audits); trending (+100% hot-view momentum).
Recommended Skills
Paper Context Resolverlllllllama/ai-paper-reproduction-skill
Repo Intake And Planlllllllama/ai-paper-reproduction-skill
Env And Assets Bootstraplllllllama/ai-paper-reproduction-skill
Minimal Run And Auditlllllllama/ai-paper-reproduction-skill
Analyze Projectlllllllama/rigorpilot-skills
Ai Research Reproductionlllllllama/rigorpilot-skills
Journey fit
Primary fit
Canonical shelf is Idea because the skill’s default job is mapping an unfamiliar topic before you commit to build or validate bets. Research subphase matches broad discovery, filtered paper search, deep reads, and citation follow-ups—not shipping or growth work.
Common Questions / FAQ
Is Deep Research safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.
SKILL.md
READMESKILL.md - Deep Research
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.