Operator-ready prompt for reuse, tuning, and workspace runs.
This item is set up for developers who want to inspect the original language, fork it into Workspace, and adapt the evidence model without losing the source prompt structure.
Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.
Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.
Swap domain facts, examples, and any hard-coded entities for your own context.
Tighten the evidence or verification requirement if this is headed toward production.
Decide which failure mode you want to evaluate first before you branch the prompt.
This prompt already carries implementation detail, tool context, and a final-output instruction. Keep that structure intact when you tune it, or your comparison runs get noisy fast.
Open this prompt inside Workspace when you want a live iteration loop.
Copy for quick reuse, or run it in Workspace to keep prompt variants, model settings, and prompt-history changes in one place.
Structured source with 1 active lines to adapt.
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Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Design a multi-agent system for CRE analysis using AutoGen. Define at least four specialized agents (e.g., Data Fetcher, Financial Modeler, Risk Assessor, Report Writer) with their respective roles and responsibilities. Outline their communication protocols, including how they will pass information, refine tasks, and collaborate to produce a final investment report. Consider using a GroupChat and GroupChatManager for orchestration. Detail the tools each agent might need, such as an API for market data or a financial calculation engine.
Adaptation plan
Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.
Preserve the role framing, objective, and reporting structure so comparison runs stay coherent.
Swap in your own domain constraints, anomaly thresholds, and examples before you branch variants.
Check whether the prompt asks for the right evidence, confidence signal, and escalation path.
Copy once for a pristine source snapshot, then move the prompt into Workspace when you want variants, run history, and side-by-side tuning without losing the original.
Prompt diagnostics
Quick signals for how structured this prompt already is and where adaptation work is likely to happen first.
This prompt is mostly narrative and instruction-driven, so you can adapt examples and output constraints first without disturbing the structure.
Multi-Agent System for Commercial Real Estate Analysis
Develop a sophisticated multi-agent system using AutoGen to act as an expert commercial real estate (CRE) analyst for institutional investors. The system will comprise specialized agents (e.g., a 'Data Fetcher', an 'Economic Analyst', a 'Valuation Specialist', a 'Report Generator') that collaborate autonomously to research, analyze, and synthesize insights on CRE investment opportunities. This challenge emphasizes complex agent-to-agent communication, tool orchestration, and the generation of comprehensive, data-driven reports. The agents should be able to query external (simulated) CRE data APIs, perform financial modeling, and provide reasoned investment recommendations. Focus on designing robust communication protocols between agents to resolve conflicts and refine analyses. The solution must also incorporate an observability framework to trace the multi-agent deliberation process and provide a user-friendly interface for querying the system and visualizing its output.
Use the challenge page to recover the original task boundaries before you tune the prompt. That keeps your variants grounded in the same evaluation target instead of drifting into a different problem.