research-ops

The research-ops skill provides an evidence-first workflow for handling current-state research, comparisons, enrichment tasks, and recommendation-oriented analysis. It acts as an orchestration layer for combining multiple research-focused skills into a structured process that prioritizes fresh public evidence and user-supplied context. The skill is designed to prevent outdated or unsupported answers by encouraging lightweight discovery first, escalating to deeper synthesis only when necessary, and clearly separating sourced facts, user-provided evidence, inference, and recommendations. It is intended for workflows where information freshness, traceability, and explicit evidence boundaries are important.

The skill supports several coordinated research capabilities, including fast web discovery, multi-source synthesis, market-oriented recommendation workflows, lead and company enrichment, and durable knowledge storage. It guides users through a staged workflow that starts with normalizing existing evidence, classifying the research request, selecting the lightest useful evidence path, and reporting conclusions with clearly labeled evidence types. The workflow also includes evaluation of whether repeated research tasks should evolve into monitored or automated workflows rather than remaining manual lookups. The skill emphasizes date-aware outputs for freshness-sensitive research and discourages unnecessary heavyweight analysis when local documentation or code already contains the answer.

Typical use cases include researching current market information, comparing vendors or tools, identifying potential business targets, enriching company or people profiles, validating user-supplied evidence, and creating repeatable monitoring workflows for recurring research needs. The skill is intended for operators, analysts, researchers, business teams, and technical users who need structured, evidence-backed outputs with transparent reasoning. It is especially useful in environments where recommendations must be traceable to explicit sources and where research workflows may later be operationalized into ongoing monitoring systems.