
Worked on the IBM/AssetOpsBench repository to expand the meta-agent framework by developing new agent tools and integrating guiding prompts and few-shot examples to enhance agent response quality. Implemented agent interaction templates and introduced an EvaluationAgent with a dedicated script for systematic assessment of AI agent outputs. Established a data handling foundation and migrated local development to CouchDB, updating documentation to support this transition. Leveraged Python, JSON, and SQL for scripting, data retrieval, and database configuration. The work focused on improving automation, agent evaluation, and scalability, enabling faster iteration and more robust agent-assisted workflows without introducing customer-impacting bugs.
2025-05 Monthly Summary for IBM/AssetOpsBench: Expanded the meta-agent framework with new agent tools (FMSR, IoT, RuleLogic, TSFM, WorkOrder), added agent prompts and few-shot guidance, and introduced interaction templates (BMSFewShots). Implemented EvaluationAgent and an evaluation script to QA AI agent responses. Established Data Handling Foundation and migrated local development to CouchDB, with accompanying documentation updates. Documentation covers CouchDB integration and configuration. Maintained internal copy alignment. No customer-impact bugs were reported; minor quality fixes include a few documentation typos corrected. Overall, these changes enhance automation capabilities, improve agent evaluation, and streamline local development, delivering business value through faster iteration, higher QA confidence, and more scalable agent-assisted workflows.
2025-05 Monthly Summary for IBM/AssetOpsBench: Expanded the meta-agent framework with new agent tools (FMSR, IoT, RuleLogic, TSFM, WorkOrder), added agent prompts and few-shot guidance, and introduced interaction templates (BMSFewShots). Implemented EvaluationAgent and an evaluation script to QA AI agent responses. Established Data Handling Foundation and migrated local development to CouchDB, with accompanying documentation updates. Documentation covers CouchDB integration and configuration. Maintained internal copy alignment. No customer-impact bugs were reported; minor quality fixes include a few documentation typos corrected. Overall, these changes enhance automation capabilities, improve agent evaluation, and streamline local development, delivering business value through faster iteration, higher QA confidence, and more scalable agent-assisted workflows.

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