Overview
Properly testing and debugging your AI agents ensures they function as intended and deliver reliable performance for your team. This article provides a systematic approach to evaluating agent behavior, identifying issues, and implementing solutions to optimize agent performance.
Learning Objectives:
Set up effective test scenarios for agent evaluation
Identify and diagnose common agent problems
Apply debugging techniques to improve agent performance
Implement best practices for ongoing agent maintenance
Prerequisites
You'll Need:
Access to your workspace
An agent you've created or have edit permissions for
Basic understanding of your agent's intended purpose and instructions
Sample queries representative of expected user interactions
Creating a Controlled Testing Space
Navigate to the agent you want to test located in the Agents section
Click on the "Agents" option in the left sidebar
Locate your agent in the list and access its chat interface
Prepare a testing protocol
Document expected responses for key test queries
Create a set of diverse test questions covering different agent capabilities
Include edge cases that might challenge the agent's understanding
Tip: Create a dedicated spreadsheet or document to track test queries and results for easier comparison.
Running Basic Functionality Tests
Test core functionality first
Start with simple, straightforward queries central to the agent's purpose
Verify responses match your expectations
Document any unexpected behaviors or deviations
Expand to more complex scenarios
Test queries that require multiple steps or reasoning
Try different phrasings of the same question
Test queries at the boundaries of the agent's knowledge domain
Result: A baseline understanding of your agent's performance and potential problem areas.
Evaluating Tool Usage
Test each enabled tool individually
If your agent uses web search, test queries requiring internet research
For data retrieval tools, verify the agent properly references connected data sources
Test code interpreter functionality if enabled
Verify image generation capabilities if applicable
Observe tool selection decisions
Check if the agent chooses the appropriate tool for each query
Note instances where the agent fails to use tools when it should
Document cases where the wrong tool is selected
Warning: Agents sometimes fail to use available tools even when appropriate for the query.
Identifying Instruction Problems
Look for patterns in incorrect responses
Note whether errors relate to tone, content accuracy, or process
Check if the agent follows all parts of multi-step instructions
Identify knowledge gaps or misunderstandings in the agent's responses
Review your agent instructions
Navigate to the agent settings by clicking the edit icon near your agent's name
Access the instructions section
Analyze instructions for clarity, completeness, and potential contradictions
Tip: Reading your instructions aloud can help identify confusing or ambiguous directions.
Examining Data Connection Issues
Verify data retrieval functionality
Ask questions directly related to your connected knowledge bases
Check if the agent acknowledges or references your data sources
Note whether information from your documents appears in responses
Diagnose data access problems
Review data hub connections in your agent settings
Verify that document collections are properly indexed
Check for any error messages related to data retrieval
Note: Website-synced data updates monthly, which may impact information currency.
Refining Agent Instructions
Access the agent edit interface
Navigate to the agent in the Agents list
Click the edit button to access configuration settings
Select the instructions section
Enhance instructions based on test results
Add explicit directions for problem areas identified during testing
Include examples of correct responses for challenging queries
Clarify tool usage expectations with specific scenarios
Remove any contradictory or confusing language
Result: More precise agent behavior aligned with your expectations.
Adjusting Tool Configuration
Optimize tool settings based on test findings
Navigate to the tools section of your agent's configuration
Enable or disable tools based on testing observations
Adjust any tool-specific parameters (like search domains)
Save changes and republish your agent
Tip: Sometimes limiting tool options can lead to more focused and reliable performance.
Establishing Regular Testing Cycles
Implement scheduled review processes
Set calendar reminders for periodic agent testing
Create a standardized set of test queries to track performance over time
Document changes in agent behavior after updates
Collect and incorporate user feedback
Ask team members about their experiences with the agent
Look for patterns in reported issues or limitations
Use real-world usage examples to inform further refinements
Result: Continuously improving agent performance based on actual use patterns.
Best Practices
Test with realistic scenarios: Use actual questions your team is likely to ask rather than artificial test cases.
Document everything: Keep detailed records of tests, issues found, and changes made to track improvement over time.
Use version control: Make one change at a time to your agent and test before making additional changes.
Test across different users: Different people may phrase questions differently, revealing blind spots in your agent's understanding.
Create challenging edge cases: Intentionally test the boundaries of your agent's capabilities to identify improvement opportunities.
Common Questions
Q: Why does my agent ignore parts of my instructions?
A: Agent instructions may be too lengthy or contain contradictions. Try breaking complex instructions into clear, sequential steps and prioritize critical directions.
Q: How can I tell if my agent is using my connected data sources?
A: Ask specific questions about information only found in your data sources. The agent should reference or cite these sources in its responses.
Q: My agent was working correctly but suddenly changed behavior. What happened?
A: Check if underlying AI models have been updated, review recent changes to agent instructions, or verify that data sources are still properly connected.
Q: How often should I test my agent?
A: Test thoroughly after any configuration changes, and schedule monthly check-ups for agents in regular use to ensure continued performance.
Q: Can I A/B test different versions of my agent?
A: Yes, create duplicate agents with different configurations to compare performance, then implement the most effective approach in your primary agent.