You are helping me build the following AI agent workflow.

## Goal
Multi-Agent Research Workflow: Multi-agent research workflow using Proplexity and Open AI to aggregate and synthesize information in minutes instead of hours.

## Specification
- What it does: You get consolidated research insights in minutes instead of hours by letting this workflow automatically pull knowledge from Proplexity and Open AI. It handles the entire aggregation process for you so you can focus on using those findings immediately.
- Trigger: Run manually (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: about an afternoon
- Tools/services involved:
  - Proplexity: Knowledge retrieval
  - Open AAI: Knowledge processing

## Known pitfalls, handle each one explicitly in your implementation
1. Token limits can truncate long research summaries so implement a chunking strategy for large inputs.
2. Inconsistent data formats from different tools will break the parser so enforce strict JSON schema validation early in the pipeline.
3. Circular dependencies between agents can deadlock the workflow so ensure a clear linear or directed acyclic graph structure for agent communication.

## Reference implementation
https://www.youtube.com/watch?v=UIf-SlmMays (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/multi-agent-research-workflow/ via usecasesforagents.com