getting started with research superpowers

📁 kthorn/research-superpower 📅 Jan 1, 1970
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安装命令
npx skills add https://github.com/kthorn/research-superpower --skill Getting Started with Research Superpowers

Skill 文档

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 → 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 → screen → extract → 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 → 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 → Screen → Extract → 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/
├── SUMMARY.md              # Main findings
├── papers-reviewed.json    # Deduplication tracking (DOI → status)
├── papers/                 # Downloaded PDFs and supplementary data
└── 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)