🎯 Response Accuracy Troubleshooting

Ensuring your AI receptionist provides accurate, relevant responses is critical for a positive user experience. This guide addresses common response accuracy issues and how to resolve them.

📊 Factual Accuracy Problems

Issue: Agent provides incorrect or outdated information

Potential causes and solutions:

1. Prompt instructions

   • Add specific guidelines about factual accuracy to your prompt
   • Include instructions to express uncertainty rather than guessing
   • Use the default template to start over if required

2. Model limitations

   • Some complex domains may require specialized knowledge
   • Consider using domain-specific knowledge bases

🔄 Relevance Issues

Issue: Agent responses don't directly address user queries

Potential causes and solutions:

1. Context understanding

   • Improve your prompt with examples of staying on topic
   • Add instructions to request clarification when queries are ambiguous
   • Enable the "Focus Mode" feature to prioritize query relevance

2. Query classification

   • Create category examples in your prompt to help the agent classify queries
   • Use the "Intent Recognition" feature to better identify user needs
   • Add fallback responses for out-of-scope questions

3. Response structure

   • Template response formats in your prompt for different query types
   • Include examples of concise, direct answers
   • Use the "Response Templates" feature for consistent formatting

🔍 Detail Level Problems

Issue: Responses are too vague or overly detailed

Potential causes and solutions:

1. Response length settings

   • Adjust the "Maximum Response Length" in agent settings
   • Include explicit instructions about detail level in your prompt
   • Create examples of ideal response length for different query types

2. Audience calibration

   • Specify your intended audience in the agent prompt
   • Include instructions about technical language usage
   • Use the "Audience Setting" feature to target specific knowledge levels

3. Context awareness

   • Train the agent to ask follow-up questions about detail preferences
   • Add instructions to match detail level to query complexity

Remember that improving response accuracy is an ongoing process that requires regular attention and refinement based on real-world performance.