testing

Configure and Test the Agent Collaboration

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Linked challenge: Multi-Agent System for Internal Security Anomaly Detection

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Linked challenge

Multi-Agent System for Internal Security Anomaly Detection

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

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0 checklist items

Configure the AutoGen agents to collaborate on a specific anomaly detection scenario. Provide a simulated input scenario (e.g., specific access logs, a suspicious email, and a relevant news headline) and trace the conversation flow between agents. Implement logic for the 'Reporting Agent' to synthesize findings and generate a final report via All Hands AI, suitable for human review. Verify that the agents correctly identify the anomaly and produce a clear, actionable report.

Adaptation plan

Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.

Keep stable

Preserve the rubric, target behavior, and pass-fail criteria as the baseline for evaluation.

Tune next

Adjust fixtures, mocks, and thresholds to the system under test instead of weakening the assertions.

Verify after

Make sure the prompt catches regressions instead of just mirroring the happy-path examples.

Prompt diagnostics

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Purpose

testing

This prompt is mostly narrative and instruction-driven, so adapt examples and output constraints before you rewrite the structure.

Linked challenge

Multi-Agent System for Internal Security Anomaly Detection

This challenge focuses on building a sophisticated multi-agent system using AutoGen to detect potential data leaks or anomalous behavior. Participants will design and implement a collaborative team of AI agents capable of monitoring internal communication logs, system access records, and cross-referencing this data with external news feeds or public information. The system will identify patterns and anomalies that might indicate security incidents or insider threats. The core of the challenge involves orchestrating diverse agents, each with specific roles like 'Log Monitor', 'News Analyst', 'Incident Investigator', and 'Reporting Agent'. These agents will communicate and collaborate autonomously, using o4-mini for reasoning and specific tools to interact with simulated data sources. The goal is to build an intelligent, proactive security monitoring system that can identify subtle indicators of risk and present a consolidated, actionable report.

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