getting-started-with-research-superpowers

name	Getting Started with Research Superpowers
description	Introduction to literature search & review skills - systematic paper finding, screening, extraction, and citation traversal
when_to_use	At start of each Claude Code session. When user asks literature search questions. When searching scientific literature. When reviewing papers or citations.
version	1.1.0

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)