implementation

CrewAI Role Definition

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Linked challenge: Geo-Compliance Satellite Swarm

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Linked challenge

Geo-Compliance Satellite Swarm

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Original prompt text with formatting preserved for inspection.

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Define a CrewAI crew with three agents. Agent 1: 'Compliance Officer' using Claude Sonnet 4.6.6. Agent 2: 'Geo-Strategist' using GPT-5.4 Pro. Agent 3: 'Image Analyst' utilizing a Hugging Face Inference tool for object detection. Set the process to 'Process.hierarchical'.

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

Keep stable

Hold the task contract and output shape stable so generated implementations remain comparable.

Tune next

Update libraries, interfaces, and environment assumptions to match the stack you actually run.

Verify after

Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.

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Purpose

implementation

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

Linked challenge

Geo-Compliance Satellite Swarm

Inspired by Planet Labs' recent decision to withhold satellite imagery of conflict regions at the request of the US government, you will design a multi-agent 'Compliance Swarm'. Using CrewAI, you will define three distinct roles: a Geo-Strategist, a Legal Compliance Officer, and an Image Analyst. The swarm will automate the process of reviewing satellite image requests against dynamic international conflict zone databases and government directives. The system will use GPT-5.4 Pro for high-level synthesis and strategic reasoning, while Claude Sonnet 4.6.6 handles the detailed regulatory text analysis. You will host the specialized image classification models on the Hugging Face Inference API and use Text Generation Inference (TGI) for high-speed local processing of the agentic communication. The agents must collaborate to decide if an image of a specific coordinate can be released, ensuring that all military and law enforcement anti-drone operations.

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To establish a clear understanding of the problem space and define comprehensive requirements for the AI solution.