Claude tech research team: a multi-agent template for technology evaluations

Evaluating technology is one of those tasks that seems simple on the surface but quickly gets complicated. You need to find options, compare features, check compatibility, assess vendor reputation, get pricing, and synthesize it all into a recommendation. I built a multi-agent system to handle exactly this workflow.

The setup

Claude Tech Research Team is a template repository that defines a network of specialized AI agents for technology evaluations. It's designed for Claude Code and uses a hierarchical architecture: a main routing agent at the top, manager agents that coordinate workflows, and specialist agents that handle focused tasks like finding SaaS options, checking open-source alternatives, evaluating Linux compatibility, or sourcing hardware from different geographic markets.

What makes this a non-code project is that the entire system is defined through agent prompts and configuration files — there's no application to build or deploy. You clone the repo, open it in Claude Code, and describe what you need to evaluate. The agents take it from there.

The agent network

The system includes agents for prompt-to-specification conversion, SaaS and open-source discovery, feature evaluation, reputation checking, support quality assessment, Linux compatibility verification, hardware sourcing across multiple markets (US, UK, Israel, AliExpress), comparative analysis, ranking, and report authoring. A research lead manager coordinates the whole flow, and an output manager handles formatting into PDFs and delivery via email or Google Drive.

Why this approach works

The key insight is that technology evaluation is naturally parallelizable. While one agent is discovering SaaS options, another can be looking for open-source alternatives, and a third can be checking Linux compatibility for options already found. The manager agents handle this orchestration, which dramatically reduces the total time for a comprehensive evaluation.

If you find yourself regularly evaluating tech stacks and want a repeatable, thorough process, this template is a good starting point. It's designed to be customized — add your own specialist agents, tweak the evaluation criteria, or extend the geographic sourcing to new markets.