Prediction Market Analyst Team
Create a specialized team of AI agents using CrewAI to analyze real-time data from prediction markets (e.g., sports betting, event futures like Kalshi). The agents, powered by Claude Opus 4.1, will collaborate to identify market trends, perform sentiment analysis on related news, predict potential market movements, and generate concise, actionable market commentary or alerts. The challenge emphasizes implementing robust agent-to-agent (A2A) communication using a custom A2A protocol for secure and structured data exchange between agents. Agents will also leverage MCP (Multi-Agent Coordination Protocol)-enabled tools to access external data sources like market APIs and news aggregators. The system should showcase hybrid reasoning, combining instant analysis for quick alerts with deeper, extended reasoning for comprehensive reports.
What you are building
The core problem, expected build, and operating context for this challenge.
Create a specialized team of AI agents using CrewAI to analyze real-time data from prediction markets (e.g., sports betting, event futures like Kalshi). The agents, powered by Claude Opus 4.1, will collaborate to identify market trends, perform sentiment analysis on related news, predict potential market movements, and generate concise, actionable market commentary or alerts. The challenge emphasizes implementing robust agent-to-agent (A2A) communication using a custom A2A protocol for secure and structured data exchange between agents. Agents will also leverage MCP (Multi-Agent Coordination Protocol)-enabled tools to access external data sources like market APIs and news aggregators. The system should showcase hybrid reasoning, combining instant analysis for quick alerts with deeper, extended reasoning for comprehensive reports.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
What you should walk away with
Master CrewAI for defining roles, tasks, and workflows for a team of specialized AI agents, including `MarketDataAnalyst`, `SentimentAnalyzer`, `TrendPredictor`, and `CommentaryGenerator` agents.
Implement a custom A2A (Agent-to-Agent) Protocol for structured, secure, and authenticated communication between CrewAI agents, ensuring data integrity and traceability of shared insights.
Design and integrate MCP (Multi-Agent Coordination Protocol)-enabled tools within CrewAI agents to access external, real-time data sources such as prediction market APIs (e.g., Kalshi if accessible, or simulated), financial news APIs (e.g., Bloomberg, Reuters), and social media sentiment feeds.
Build hybrid instant/deep reasoning mechanisms for Claude Opus 4.1 agents: instant for real-time alerts on significant market shifts, and deep for comprehensive, extended analysis reports requiring more cognitive effort.
Develop robust RAG pipelines that allow agents to retrieve historical market data, economic indicators, and expert analysis for contextualizing current trends.
Orchestrate the flow of information and decision-making within the CrewAI team, ensuring agents effectively share findings, critique analyses, and synthesize information into coherent outputs.
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[ok] Wrote .versalist.json
[ok] Wrote eval/examples.json
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