--- name: brycewang-stanford/Getting Started with Research Superpowers source: https://app.decimal.ai/s/brycewang-stanford-getting-started-with-research-superpowers@1/SKILL.md source_sha256: d5c6ba5a243f --- # 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: ```bash # 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)