AI Research Skills
AI Research Skills is an open, community-curated library of skills: small, teachable, composable units for doing research work with AI.
If you want the "why" and the bigger picture, read the Rationale.
What This Project Provides
A growing library of composable, teachable instructions for research workflows (from reference formatting to domain-specific methods).
Reproducible evaluations showing how different models perform on real research skills. Powered by BARS (Benchmark for AI Research Skills).
Practical ways to consume skills in real tools (e.g. Claude Code plugins, MCP workflows, CLI helpers), without requiring users to become Git experts.
Categories
- Research - Research methods, reference management, source discovery
- Analysis - Text analysis, data processing, computational methods
Contributing
Want to add a skill? See our contribution guide for easy ways to contribute - no local Git setup required!
Workflow Stages
Skills are organized by where they fit in a typical research workflow:
| Stage | Description |
|---|---|
| discover | Finding sources, literature review |
| digitize | Scanning, OCR, format conversion |
| extract | Text extraction, data scraping |
| annotate | Tagging, labeling, metadata enrichment |
| analyze | Computational analysis, statistics |
| model | Machine learning, topic modeling |
| connect | Linking data, knowledge graphs |
| present | Visualization, publishing |