research-scout
Dev Research Scout
Scans high-signal research sources for methods, frameworks, and ideas worth applying to your own work, and converts the top finds into idea cards with how-to-apply recipes, evidence quality grades, and reproducibility notes.
Supported sources: arXiv, Hugging Face Papers, Semantic Scholar, Papers with Code (archive only — shut down Jul 2025), conference proceedings (NeurIPS / ICML / ICLR / ACL / EMNLP / KDD), industry research blogs (Anthropic / OpenAI / DeepMind / Google Research / Meta AI / Microsoft Research / Apple ML), and curator newsletters (Lilian Weng, Sebastian Raschka, Eugene Yan, Latent Space, Simon Willison, The Batch, Import AI, Interconnects / Nathan Lambert, Davis Summarizes Papers / Davis Blalock).
Output is a generative toolkit, not a landscape report:
- pattern catalog (methods worth stealing, with how-to-apply)
- anti-pattern catalog (research traps — irreproducibility, benchmark gaming, hype)
- recipes (extraction, validation-before-adoption, kill criteria)
Key distinction from sibling scouts:
- This skill = research-grade idea mining (papers + research blogs + curated synthesis)
startup-painpoint-scanner= community-pain mining (Reddit / HN / GitHub Issues / G2 / Stack Overflow)research-arxiv-scout= arXiv-only deep triage with category taxonomy and attribution; specialist downstreamresearch-git= public GitHub repo research for skills, practices, and code patterns (separate concern)
Use this skill when the question is "what methods or frameworks are worth stealing from recent research?" — escalate to research-arxiv-scout for arXiv-only work where category taxonomy and attribution matter most.