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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.

Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

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.

Datasets

Shared data for this challenge

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Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks, how much each dimension matters, and which criteria separate a passable run from a strong one.

Max Score: 6
Dimensions
6 scoring checks
Binary
6 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1sentimentaccuracy

SentimentAccuracy

At least 85% accuracy in identifying sentiment for given brand mentions.

binary
Weight: 1
Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2brandextractioncompleteness

BrandExtractionCompleteness

Identifies all relevant brand mentions (80% recall).

binary
Weight: 1
Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 3koreaiintegration

KoreAiIntegration

Kore.ai workflow is successfully triggered on specified conditions.

binary
Weight: 1
Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 4voiceflowresponsiveness

VoiceflowResponsiveness

Voiceflow agent provides coherent and relevant responses to queries.

binary
Weight: 1
Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 5averagesentimentaccuracy

AverageSentimentAccuracy

Average accuracy of sentiment classification across all extracted brands. • target: 0.9 • range: 0.75-1

binary
Weight: 1
Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 6toolusageeffectiveness

ToolUsageEffectiveness

Percentage of tasks where tools were correctly invoked and utilized. • target: 0.95 • range: 0.8-1

binary
Weight: 1
Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

Master CrewAI for building robust, role-based agent teams with defined responsibilities and collaborative workflows for data analysis.

Implement advanced sentiment analysis and entity extraction using DeepSeek R1's API for nuanced understanding of brand mentions in diverse prompts.

Design and build custom tools for CrewAI agents to programmatically interact with Zapier Interfaces for data ingestion and event triggering.

Integrate Kore.ai to define and execute complex workflow automations based on agent-detected insights and threshold breaches.

Develop a Voiceflow project to create an intuitive voice-enabled or chat-based interface for querying system status and brand analytics.

Leverage Blaxel's capabilities for monitoring agent interactions, managing agent lifecycles, and ensuring system resilience in production environments.

Start from your terminal
$npx -y @versalist/cli start agents-for-prompt-driven-brand-sentiment-affinity

[ok] Wrote CHALLENGE.md

[ok] Wrote .versalist.json

[ok] Wrote eval/examples.json

Requires VERSALIST_API_KEY. Works with any MCP-aware editor.

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Challenge at a glance
Host and timing
Vera

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Timeline and host

Operating window

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Tool Space Recipe

Draft
Action Space
CrewAIFramework for orchestrating
required
ZedHigh-performance code editor
Policy Serving
DeepSeek R1
Evaluation
Rubric: 6 dimensions
·SentimentAccuracy(1%)
·BrandExtractionCompleteness(1%)
·KoreAiIntegration(1%)
·VoiceflowResponsiveness(1%)
·AverageSentimentAccuracy(1%)
·ToolUsageEffectiveness(1%)
Gold items: 3 (3 public)

Frequently Asked Questions about Agents for Prompt-Driven Brand Sentiment & Affinity