research-ops

Orchestrate structured research workflows to gather, verify, and synthesize public information.

1|Updated Apr 6, 2026

Search Tags:#workflow #research #monitoring #analysis #evidence #synthesis

Ready to run

npx skills add https://github.com/vrcms/everything-qwen-code --skill research-ops-vrcms

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-ops
Source: https://github.com/vrcms/everything-qwen-code/tree/main/.qwen/skills/research-ops
Command: npx skills add https://github.com/vrcms/everything-qwen-code --skill research-ops-vrcms

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill solves the problem of fragmented or stale information gathering by providing a structured, evidence-based framework for conducting research, comparisons, and market analysis.

Core Features & Use Cases

Evidence-Based Synthesis: Ensures all research outputs clearly distinguish between sourced facts, user-provided context, and AI inferences.
Workflow Orchestration: Integrates specialized research tools like exa-search and deep-research into a cohesive, repeatable process.
Use Case: When you need to compare multiple software vendors or technologies, this Skill guides the AI to gather current public data, synthesize it with your specific project requirements, and provide a ranked recommendation with citations.

Quick Start

Use the research-ops skill to compare the latest features and pricing of the top three cloud database providers for our current project.

Frequently Asked Questions about research-ops

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I structure an evidence-based research workflow for comparative analysis?▼

An evidence-based research workflow orchestrates specialized search tools to gather, verify, and synthesize current public information. It ensures data freshness and citation accuracy by clearly distinguishing between sourced facts, user-provided context, and AI inferences for decision-making.

What is the best way to compare multiple software vendors using current public data?▼

Comparing software vendors requires a structured synthesis workflow that gathers current public data and integrates it with your specific project requirements. This method produces a ranked vendor recommendation complete with accurate source citations.

How does evidence synthesis handle AI inferences versus sourced facts?▼

Evidence synthesis handles AI inferences by strictly separating them from sourced facts and user-provided context in the research output. This transparency ensures you can trust the decision-making process by verifying the origin of every data point.

Do I need a search-capable agent for market intelligence and evidence-based reporting?▼

Yes, market intelligence and evidence-based reporting require integration with a search-capable agent. This integration ensures data freshness, retrieves current public information, and maintains citation accuracy throughout the research workflow.

Can I use this research workflow to compare cloud database providers for a specific project?▼

Yes, you can use this research workflow to compare cloud database providers for a specific project. It guides the AI to gather current public data on features and pricing, synthesize it with your requirements, and provide a ranked recommendation with citations.

What are the limitations of using automated synthesis for market intelligence gathering?▼

A limitation of automated synthesis for market intelligence is its reliance on integrated search-capable agents to retrieve current public information. Without this integration, the workflow cannot ensure data freshness or maintain citation accuracy for reporting.