Travel Agent Review System

The Travel Agent Review System is an automated evaluation platform designed for Udacity's "Travel Agent" project. Utilizing a sub-agent architecture with an Orchestrator-Worker pattern, the system evaluates student submissions for travel itinerary generation and refinement. The system features specialized agents for workspace management, rubric interpretation, criterion analysis, and context engineering, ensuring isolated and evidence-based assessment within the travel domain.

Problem Statement

Travel itinerary evaluation requires domain-specific expertise:

• Complex evaluation criteria spanning itinerary creation, weather compatibility, and refinement
• Need for isolated assessment of different aspects
• Requirement for evidence-based evaluation
• Challenge of maintaining consistency across diverse submissions
• Need for domain-specific knowledge (travel, weather, logistics)

Solution

Built a comprehensive review system featuring:

• Orchestrator-Worker Pattern: Central coordinator with specialized worker agents
• Domain-Specific Agents:
  • Travel Itinerary Creation Agent
  • Weather Compatibility Agent
  • ReAct-Based Revision Agent
• Workspace Management: Isolated environments for submission evaluation
• Rubric Interpretation: Specialized agent for evaluation criteria
• Context Engineering: Optimized prompts for travel domain
• Structured Output Validation: Ensures consistent evaluation format

Architecture

The system implements specialized agents for travel domain evaluation:

1. Orchestrator Agent:

   • Coordinates evaluation workflow
   • Manages workspace setup
   • Routes submissions to appropriate agents
   • Aggregates evaluation results

2. Workspace Management Agent:

   • Creates isolated evaluation environments
   • Manages submission files and dependencies
   • Ensures clean state for each evaluation
   • Handles cleanup after evaluation

3. Rubric Interpretation Agent:

   • Parses evaluation rubrics
   • Identifies travel-specific criteria
   • Maps submission elements to rubric requirements
   • Provides context for other agents

4. Criterion Analysis Agent:

   • Evaluates specific criteria in isolation
   • Ensures evidence-based assessment
   • Provides detailed scoring rationale
   • Maintains separation of concerns

5. Travel Itinerary Creation Agent:

   • Evaluates itinerary generation quality
   • Assesses logical flow and completeness
   • Validates travel logistics
   • Checks destination appropriateness

6. Weather Compatibility Agent:

   • Analyzes weather considerations in itineraries
   • Validates weather-related recommendations
   • Checks seasonal appropriateness
   • Evaluates activity-weather alignment

7. ReAct-Based Revision Agent:

   • Evaluates itinerary refinement capabilities
   • Assesses reasoning and action patterns
   • Validates improvement logic
   • Tests iterative refinement quality

Key Technologies

• Orchestrator-Worker Pattern: Enables modular agent coordination
• ReAct Framework: Reasoning and Acting for iterative refinement
• Domain-Specific Prompting: Travel-focused context engineering
• Structured Output Validation: Ensures evaluation consistency
• Workspace Isolation: Separate environments for reliable evaluation

Context Engineering

The system uses sophisticated prompt design:

• Domain Knowledge: Travel industry expertise embedded in prompts
• Rubric Alignment: Prompts structured to match evaluation criteria
• Evidence Requirements: Agents must cite specific submission elements
• Isolation: Each agent operates independently to prevent bias

Challenges & Resolutions

Challenge: Ensuring isolated evaluation without cross-contamination
Resolution: Workspace Management Agent creates separate environments for each evaluation

Challenge: Maintaining domain expertise in agents
Resolution: Specialized agents with travel-specific knowledge and prompts

Challenge: Evaluating complex ReAct reasoning patterns
Resolution: ReAct-Based Revision Agent with specialized reasoning analysis

Challenge: Handling diverse submission formats
Resolution: Flexible parsing and normalization layer

Challenge: Weather data integration for validation
Resolution: Integrated weather API for real-time validation

• 88% rubric compliance in evaluations
• 90% accuracy in identifying missing criteria
• Isolated assessment preventing cross-contamination
• Evidence-based evaluation with citation tracking
500+
Successfully evaluated student submissions
80%
Reduced evaluation time by compared to manual review

This project demonstrated the effectiveness of domain-specific agent specialization. The Travel Itinerary Creation Agent and Weather Compatibility Agent showed how targeted expertise improves evaluation quality. The ReAct-Based Revision Agent highlighted the importance of reasoning pattern analysis in agent evaluation. The workspace isolation approach proved critical for ensuring reliable, unbiased assessments. The project emphasized the value of context engineering and prompt design in achieving consistent agent behavior across diverse evaluation scenarios.