research

To gather evidence for a technical feasibility study, this skill performs a multi-axis investigation by aggregating information from arXiv preprints, formal academic literature, web discovery, and practitioner-focused sources. It systematically covers peer-reviewed journals and informal engineering discourse.

The best way to perform a state-of-the-art survey is to use a structured multi-axis framework that maps findings to specific sources. This skill synthesizes evidence across preprints, web documentation, and practitioner material to generate a comprehensive RESEARCH.md artifact.

Yes, you need Python for arXiv API interaction when performing broad literature reviews. The skill requires Python to query preprint servers and web search capabilities for broader discovery across academic and practitioner-focused sources.

To conduct multi-axis discovery for product definition, invoke this skill to investigate your topic across formal academic literature and informal engineering discourse. It generates a RESEARCH.md artifact that maps findings to sources without prematurely locking in product decisions.

Evidence gathering requires mapping findings to specific sources to avoid prematurely locking in product decisions. By aggregating across formal literature and practitioner material, the skill ensures your modeling tasks are grounded in traceable, comprehensive evidence synthesis.