Debug & Optimize Google Opal Agent
Budget: $10 – $30 USD
My current au agent built on Google Opal intermittently refuses to answer. It does not mis-understand or give wrong information; instead it stays silent at unpredictable moments, which users naturally read as “incorrect” behaviour. I need you to trace why these random no-response events occur, patch the underlying cause, and then tune the agent so it delivers consistent, timely replies.
You will start by inspecting the existing Opal configuration, intent handling, webhook logic and any external API calls. Once the fault is isolated and corrected, I also want recommendations—and, where practical within the same engagement, direct improvements—to overall response reliability and speed.
Deliverables
• Root-cause report outlining what was broken and how you fixed it
• Updated code / Opal settings applied in my project repo
• Verification test results demonstrating that the agent no longer fails to respond across a representative question set
• Brief hand-off notes so I can maintain the solution going forward
Acceptance criteria: after your fix the agent must answer 100 % of queries in a 50-prompt regression test without silent failures, and average latency should remain at or below its current level.
If you have hands-on experience with Google Opal, conversational AI routing, or similar cloud NLP stacks, please let me know—those skills will get this wrapped up faster.
You will start by inspecting the existing Opal configuration, intent handling, webhook logic and any external API calls. Once the fault is isolated and corrected, I also want recommendations—and, where practical within the same engagement, direct improvements—to overall response reliability and speed.
Deliverables
• Root-cause report outlining what was broken and how you fixed it
• Updated code / Opal settings applied in my project repo
• Verification test results demonstrating that the agent no longer fails to respond across a representative question set
• Brief hand-off notes so I can maintain the solution going forward
Acceptance criteria: after your fix the agent must answer 100 % of queries in a 50-prompt regression test without silent failures, and average latency should remain at or below its current level.
If you have hands-on experience with Google Opal, conversational AI routing, or similar cloud NLP stacks, please let me know—those skills will get this wrapped up faster.