test-ai-analysis

Automate AI analysis testing by running the provided test suite that validates quota endpoints, cost-related batch analyses, and caching behavior against your Java backend and Python AI service. The Skill orchestrates end-to-end HTTP interactions with token-based authentication to verify cost analysis integrity and quota management across local integration environments.

Yes. This Skill tests AI interaction flows including session handling, follow-ups, and repeat-query caching by executing reproducible test orchestration against localhost services. It validates token retrieval, service health checks, and session management to ensure caching respects quota rules across conversations.

Batch cost analysis testing covers token-based quota validation, cost data extraction from JSON responses, and time-range reporting. The Skill performs error handling and data validation across batch analyses to verify that your AI analysis module correctly tracks and reports costs without quota violations.

Yes. The Skill requires a Java backend running on localhost:10010 and a Python AI service on localhost:8085. It performs functional testing for end-to-end HTTP interactions in local integration environments, making it suitable for development and staging validation of the Cretas food traceability AI analysis system.

Run the AI analysis test suite to validate token retrieval from authentication endpoints and perform service health checks on both backend and AI services. The Skill extracts and validates responses to ensure session management and error handling work correctly before moving to production.

Yes. The Skill tests caching behavior and conversation history management by simulating AI follow-ups and repeat queries. It verifies that your system correctly caches responses, respects quota limits, and maintains session state across multiple interactions without redundant processing.