implementation

Agent Communication Logic

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

Linked challenge: Autonomous Elite Chauffeur Fleet Orchestration with CrewAI and Fetch.ai

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Linked challenge

Autonomous Elite Chauffeur Fleet Orchestration with CrewAI and Fetch.ai

Prompt source

Original prompt text with formatting preserved for inspection.

1 lines

1 sections

No variables

0 checklist items

Write the task definitions for CrewAI where the LogisticsAgent must call a Fetch.ai protocol to check vehicle availability and the ConciergeAgent must validate the plan against Giskard evaluation criteria. Use Swimm-style comments to document the integration points.

Adaptation plan

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.

Prompt diagnostics

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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

Autonomous Elite Chauffeur Fleet Orchestration with CrewAI and Fetch.ai

Inspired by Uber's acquisition of Blacklane, this challenge requires building a multi-agent system to manage an elite chauffeur service. You will design a collaborative team of agents that handle high-end booking requests, real-time route optimization for luxury standards, and concierge-level client interactions. The system must use role-playing agents to simulate the complex logistics of a global elite transport network, ensuring that high-net-worth requirements are met through autonomous negotiation and planning. The implementation focuses on the collaboration between specialized agents to handle the end-to-end lifecycle of a luxury ride from booking to completion without human intervention.

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Initial Assessment Prompt

planning

Content Classification Prompt

implementation

Problem Definition and Requirements Gathering

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