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Skill brycewang-stanford/Auto-Empirical-Research-Skills/skills/05-kthorn-research-superpower/getting-started

๐Ÿ”ฌ A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | ็ฒพ้€‰ 23,000+ AI Agent ๆŠ€่ƒฝๅบ“๏ผŒ่ฆ†็›–8ๅคง็คพไผš็ง‘ๅญฆๅญฆ็ง‘็š„ๅฎž่ฏ็ ”็ฉถใ€‚CoPaper.AI 20ๅˆ†้’ŸๅฎŒๆˆไธ€็ฏ‡ๅฏๅค็Žฐ็š„่ง„่Œƒๅฎž่ฏ่ฎบๆ–‡๏ผŒๅนถๆ”ฏๆŒ็”จๆˆทไธŠไผ  Skillsใ€‚-- Maintained by CoPaper.AI from Stanford REAP.

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npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill getting-started

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Introduction to literature search & review skills - systematic paper finding, screening, extraction, and citation traversal

SKILL.md

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Getting Started with Research Superpowers

Research Superpowers gives Claude Code systematic workflows for literature searching and review.

Focus: Finding, screening, and extracting data from published papers. NOT for analyzing experimental data or designing experiments.

What You Can Do

Use these skills for systematic literature reviews:

  • Search literature - PubMed and Semantic Scholar integration
  • Build screening rubrics - Define and test relevance criteria collaboratively
  • Screen papers - Two-stage screening (abstract โ†’ deep dive) with scoring
  • Extract data - Find specific methods, results, measurements from papers
  • Traverse citations - Smart backward/forward citation following
  • Large-scale screening - Parallel subagent processing for 50+ papers
  • Track findings - Organized research sessions with summaries, PDFs, and deduplication

Available Skills

Literature Search & Review Skills (skills/research/)

  • answering-research-questions - Main orchestration workflow (search โ†’ screen โ†’ extract โ†’ synthesize)
  • building-screening-rubrics - Collaborative rubric design with test-driven refinement
  • searching-literature - PubMed search with keyword optimization
  • evaluating-paper-relevance - Two-stage screening (abstract โ†’ deep dive)
  • subagent-driven-review - Parallel screening for large searches (50+ papers)
  • checking-chembl - Check if medicinal chemistry papers have curated SAR data in ChEMBL
  • traversing-citations - Semantic Scholar citation network traversal
  • finding-open-access-papers - Unpaywall API to find free versions of paywalled papers
  • cleaning-up-research-sessions - Safe cleanup of intermediate files after research complete

Basic Workflow

When user asks a literature search question:

  1. Read answering-research-questions skill - Main orchestration
  2. Announce: "I'm using the Answering Research Questions skill"
  3. Parse query - Extract keywords, data types, constraints
  4. Create research folder - Propose name, initialize tracking
  5. Optional: Build rubric - For large searches (50+ papers), use building-screening-rubrics skill
  6. Search โ†’ Screen โ†’ Extract โ†’ Traverse - Follow the workflow
  7. Check in regularly - Every 10 papers, checkpoint every 50

Research Session Folders

Each query creates a folder in research-sessions/:

research-sessions/YYYY-MM-DD-query-description/
โ”œโ”€โ”€ SUMMARY.md              # Main findings
โ”œโ”€โ”€ papers-reviewed.json    # Deduplication tracking (DOI โ†’ status)
โ”œโ”€โ”€ papers/                 # Downloaded PDFs and supplementary data
โ””โ”€โ”€ citations/              # Citation graph tracking

Core Principles

For systematic literature review:

  • Precision over breadth - Find papers with specific data you need, not just topical matches
  • Test-driven screening - Build and validate rubrics before bulk processing
  • Smart citation following - Only traverse relevant citations to avoid exponential explosion
  • Deduplicate aggressively - Track ALL reviewed papers by DOI (even non-relevant)
  • Cache abstracts - Save for re-screening when rubrics change
  • Report progress - Update user every 10 papers as work proceeds
  • Checkpoint frequently - Ask to continue or stop every 50 papers
  • Reproducible - Save rubrics, queries, and methodology with research sessions

API Information

PubMed E-utilities (no key required):

  • Search: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi
  • Details: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esummary.fcgi
  • Full text: https://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi

Semantic Scholar (free tier works, optional key for higher limits):

  • Paper: https://api.semanticscholar.org/graph/v1/paper/DOI:{doi}
  • References: https://api.semanticscholar.org/graph/v1/paper/{id}/references
  • Citations: https://api.semanticscholar.org/graph/v1/paper/{id}/citations

Finding Skills

Use the find-skills script to search for relevant skills:

# From project directory
./scripts/find-skills              # List all skills
./scripts/find-skills literature   # Search for "literature"
./scripts/find-skills 'cite|ref'   # Regex search

Remember

  • Always start by reading the relevant research skill
  • Announce skill usage when you begin
  • Track everything in the research folder
  • Check in with user regularly during long searches
  • Deduplicate using papers-reviewed.json (DOI as key)

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.