planning

Design Agent Roles & Workflow

Inspect the original prompt language first, then copy or adapt it once you know how it fits your workflow.

Linked challenge: Multi-Agent News Synthesis

Format

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Linked challenge

Multi-Agent News Synthesis

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

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No variables

0 checklist items

Design the core multi-agent architecture using Fetch.ai. Define at least three distinct agent roles (e.g., Researcher, Analyzer, Synthesizer) with clear responsibilities and communication protocols. Map out the end-to-end workflow for generating a news summary from a raw news event. Specify how agents will pass information and coordinate tasks.

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 role framing, objective, and reporting structure so comparison runs stay coherent.

Tune next

Swap in your own domain constraints, anomaly thresholds, and examples before you branch variants.

Verify after

Check whether the prompt asks for the right evidence, confidence signal, and escalation path.

Prompt diagnostics

Variables

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Purpose

planning

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

Linked challenge

Multi-Agent News Synthesis

Develop an advanced multi-agent system designed to revolutionize news content creation for publishers. This system will autonomously gather information from diverse sources, perform in-depth analysis, detect potential biases, and generate structured content drafts tailored to specific publication styles (e.g., concise summaries for social media, detailed analyses for financial news). The challenge emphasizes leveraging modern generative AI for content production, while ensuring accuracy and mitigating bias through robust agent collaboration and validation steps. The core of the solution will involve orchestrating a team of specialized agents, each responsible for distinct tasks such as research, factual verification, stylistic adaptation, and final content generation. The system should be able to process real-time information, adapt to evolving news narratives, and produce high-quality, relevant content that adheres to editorial guidelines.

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