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.
Already linked to a challenge workflow.
Sign in to keep private prompt variations.
Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Define the roles and responsibilities for your CrewAI agent team (e.g., 'Memory Keeper Agent', 'Wellness Monitor Agent', 'Social Connector Agent'). For each agent, specify which MCP-enabled tools they will utilize (e.g., 'CalendarSync', 'HealthDataAPI', 'FamilyMessageRelay') and how they will interact with Claude Opus 4.1 for empathetic reasoning.
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.
Empathetic Elderly Companion Network with CrewAI & Claude Opus 4.1
Inspired by the growing market for AI solutions addressing loneliness among the elderly, this challenge focuses on building a sophisticated multi-agent system. The system will leverage CrewAI to orchestrate a team of specialized, empathetic companion agents. Each agent will interact with the user and external enterprise systems (e.g., health trackers, family communication apps, scheduling services) via an MCP (Multi-Agent Communication Protocol) enabled tool layer. The core of the system will utilize Claude Opus 4.1 for its advanced empathetic reasoning and nuanced conversational capabilities, combined with Gemini 2.5 Pro for potential multi-modal input processing (e.g., analyzing user tone or sentiment from simulated voice/video). The system must employ RAG for personalized memory recall and implement hybrid instant/deep reasoning with adaptive thinking budgets to provide contextually rich and timely support.
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.