planning

A2A Communication Protocol Design

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

Linked challenge: Develop a Low-Resource Language Data Generation Crew

Format

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Linked challenge

Develop a Low-Resource Language Data Generation Crew

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

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0 checklist items

Design the A2A communication protocol that your agents will use for task delegation, feedback, and status updates. Specify the message formats, communication channels (e.g., shared queue, direct calls), and error handling strategies. Provide a sequence diagram for a typical data generation and validation flow.

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

Develop a Low-Resource Language Data Generation Crew

Challenge of building LLMs for low-resource languages, this challenge focuses on creating an intelligent agent crew to significantly accelerate and enhance the creation of high-quality, culturally-relevant datasets. The lack of robust training data is a major hurdle for these languages, and traditional methods are slow and costly. Your task is to build a multi-agent system that collaborates to generate synthetic text, translate, and perform linguistic and cultural validation for a specified low-resource language. The system will employ Gemini 3 for advanced generative capabilities and cross-lingual understanding, alongside specialized agents for validation. Crucially, the agents will communicate via an A2A Protocol, ensuring efficient hand-offs and feedback loops, with human-in-the-loop checkpoints for final verification.

Open challenge

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