Operator-ready prompt for reuse, tuning, and workspace runs.
This item is set up for developers who want to inspect the original language, fork it into Workspace, and adapt the evidence model without losing the source prompt structure.
Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.
Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.
Swap domain facts, examples, and any hard-coded entities for your own context.
Tighten the evidence or verification requirement if this is headed toward production.
Decide which failure mode you want to evaluate first before you branch the prompt.
This prompt already carries implementation detail, tool context, and a final-output instruction. Keep that structure intact when you tune it, or your comparison runs get noisy fast.
Open this prompt inside Workspace when you want a live iteration loop.
Copy for quick reuse, or run it in Workspace to keep prompt variants, model settings, and prompt-history changes in one place.
Structured source with 1 active lines to adapt.
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Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Design and implement a basic Voiceflow project that allows a user to query the status of the brand sentiment analysis system. This interface should be able to ask for the current sentiment of a specific brand (e.g., 'What is the sentiment for Product X?'). The Voiceflow agent will need to communicate with your CrewAI system to retrieve real-time data. Outline the necessary API endpoints or data structures your CrewAI system will expose to facilitate this interaction. Provide example Voiceflow intents and responses.
Adaptation plan
Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.
Hold the task contract and output shape stable so generated implementations remain comparable.
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.
Copy once for a pristine source snapshot, then move the prompt into Workspace when you want variants, run history, and side-by-side tuning without losing the original.
Prompt diagnostics
Quick signals for how structured this prompt already is and where adaptation work is likely to happen first.
This prompt is mostly narrative and instruction-driven, so you can adapt examples and output constraints first without disturbing the structure.
Agents for Prompt-Driven Brand Sentiment & Affinity
This challenge focuses on building a sophisticated multi-agent system using CrewAI to analyze brand mentions and sentiment within a stream of AI-generated prompts. The system will orchestrate specialized agents to monitor, categorize, and report on brand affinity. The core idea is to simulate an intelligent monitoring platform that provides actionable insights into brand perception and recommendation patterns from diverse data sources, leveraging CrewAI's role-playing architecture. Developers will design a collaborative agent team, where each agent has a distinct role, tools, and goals. For instance, a 'Prompt Ingestor' agent, a 'Brand Analyst' agent, and a 'Report Generator' agent will work in concert. The system will use DeepSeek R1 for its advanced reasoning capabilities to accurately interpret nuanced sentiment and complex brand associations. Integration with Zapier Interfaces will enable seamless data ingestion from various sources, while tool can facilitate custom workflow automation for alert triggers and data processing. Voiceflow will provide a conversational interface for real-time query and status updates, making the system highly interactive. Blaxel will serve as the underlying agent orchestration backbone, ensuring robust agent management.
Use the challenge page to recover the original task boundaries before you tune the prompt. That keeps your variants grounded in the same evaluation target instead of drifting into a different problem.